literature review on economic development

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A Literature Review of Pandemics and Development: the Long-Term Perspective

• Original Paper
• Published: 27 January 2022
• Volume 6 , pages 183–212, ( 2022 )

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• Beniamino Callegari   ORCID: orcid.org/0000-0001-5513-7299 1 , 2 &
• Christophe Feder   ORCID: orcid.org/0000-0002-1239-513X 3 , 4  

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Pandemics have been a long-standing object of study by economists, albeit with declining interest, that is until COVID-19 arrived. We review current knowledge on the pandemics’ effects on long-term economic development, spanning economic and historical debates. We show that all economic inputs are potentially affected. Pandemics reduce the workforce and human capital, have mixed effects on investment and savings, but potentially positive consequences for innovation and knowledge development, depending on accompanying institutional change. In the absence of an innovative response supporting income redistribution, pandemics tend to increase income inequalities, worsening poverty traps and highlighting the distributional issues built into insurance-based health insurance systems. We find that the effects of pandemics are asymmetric over time, in space, and among sectors and households. Therefore, we suggest that the research focus on the theoretical plausibility and empirical significance of specific mechanisms should be complemented by meta-analytic efforts aimed at reconstructing the resulting complexity. Finally, we suggest that policymakers prioritize the development of organizational learning and innovative capabilities, focusing on the ability to adapt to emergencies rather than developing rigid protocols or mimicking solutions developed and implemented in different contexts.

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Introduction

As the COVID-19 emergency appears to slowly and unevenly recede in the wake of medical breakthroughs and the development of more effective prevention and treatment protocols, the question of the long-term impact of the pandemic grows more urgent. There is little doubt that this global health crisis found economists mostly unprepared, as the analysis of the pandemic’s effects has hardly found its way into the discipline’s most central publication avenues (Noy and Managi 2020 ). However, this does not mean that the economic analysis of pandemics is starting from scratch, as economists and economic historians have never ceased to expand our knowledge on the subject.

The connection between pandemics and economic theory has historically been so relevant that it has directly contributed to labeling economics as the ‘dismal science’. Cipolla ( 1974 ) illustrates how reflections on the plague and its consequences led many scholars to develop Malthusian ideas on the complex long-term relationships between population growth, economic growth, and diseases, well in advance of the Essay on the Principle of Population (Malthus 1798 ). However, the Industrial Revolution and the concomitant development of medical knowledge led to a decreased incidence of catastrophic plagues in the West, and a corresponding decline in the interest in pandemics on the part of economists (Easterlin 1995 ). The demographic boom of the West and the visible lack of corresponding pestilence and famine further discredited Malthusian perspectives, leading to a disconnection between the demographic and economic disciplines. Furthermore, from 1900 to 2019, pandemics were either eclipsed by more disruptive events or had a relatively limited economic impact (Garrett 2008 ; Lee and McKibbin 2004 ; Noy and Managi 2020 ). Finally, the marginalist revolution greatly focused economists’ attention on purely economic elements, eliminating from the discipline those elements perceived as spurious, like the study of pandemics’ effects (Schumpeter 1954 ), relegating it to a debate of mainly historical interest.

The expansion of economic analysis beyond its traditional boundaries that has occurred in the last two decades has gradually re-included the consequences of pandemics within economic theory, although most contributions remain on the periphery of academic debate and are relatively hidden (Arora 2001 ; Dunn 2006 ; Weil 2014 ). As Noy and Managi ( 2020 ) observed, the inherently multidisciplinary nature of pandemics, combined with its poor fit with what are called “hard” methods, have both conspired to make the contribution made by economists to the analysis of pandemics modest. The efforts of economists have been greatly augmented by the continuous work done by economic historians to understand the impact of past pandemics on the long-term development of various socioeconomic systems. Yet, while the total contribution to the economic analysis of the long-term impact of pandemics is significant, it is scattered across different journals, disciplines, academic approaches, and debates, making a review work necessary in order for all these contributions to become accessible.

This paper reviews the long-term economic effects of pandemics, defined as health shocks arising from infectious diseases with global diffusion. Within the definition of long-term effects, we include both those mechanisms that are immediately present and persist for a significant amount of time and those effects that arise in the long term. Due to the focus of our analysis, transient short-term effects are not part of our study. To the best of our knowledge, few literature reviews have studied the connection between pandemics and economic development. Bleakley ( 2010 ) critically reviews how diseases, rather than pandemics specifically, affect human capital formation and income growth at the micro and macro levels. Costa ( 2015 ) describes how health improvements affect economic growth, with a specific focus on the US, concluding that improved health is not sufficient to foster growth. Finally, Boucekkine et al. ( 2008 ) formally analyze how and which growth models are better able to mathematically describe the epidemics’ effects. Moreover, some scholars have also reviewed the long-term economic effects of particular health shocks, like the preindustrial epidemics (Alfani 2021 ), Spanish flu (Beach et al. 2021 ), HIV (Gaffeo 2003 ; Zinyemba et al. 2020 ), and modern pandemics (Bloom et al. 2021 ). We differ from these works because we analyze the long-term impact of pandemics in general on economic development. A similar approach has been adopted by Gries and Naudé ( 2021 ) and Callegari and Feder ( 2021a ), but with an entrepreneurship and not a macroeconomic focus.

Our broad approach has led us to review a large number of studies in order to identify recurrent results across very different pandemic events. Pandemics could affect aggregate demand, aggregate supply, and productivity growth (Basco et al. 2021 ; Dieppe 2021 ; Guerrieri et al. 2020 ; Jinjarak et al. 2021 ; Rassy and Smith 2013 ; World Bank 2020 ). Recalling the Solovian framework, we divide the long-term pandemic economic effects into three categories: labor and human capital; investments and physical capital; and knowledge and innovation. We find that all productive inputs are affected in the long term by the pandemic. More specifically, labor and human capital are negatively affected directly by health shocks. However, the intensity of this effect is heterogeneous among countries, labor markets, and industries. Investments and physical capital are affected by pandemics through complex, interacting, and often contrasting mechanisms, leaving long-term effects ambiguous and usually marginal and non-linear. However, the asymmetric impact of pandemics on the capital market and household income leads to the poverty trap and highlights the weakness of the health insurance system in coping with these shocks. Finally, pandemics could positively affect innovations in public and private institutions and bring about relevant technological changes in industries. The scope and direction of these socioeconomic changes appear to mediate the long-term effects of pandemics, determining both their direction and scope. However, relevant and radical institutional changes are necessary if the impact of pandemics on development is to be positive. We therefore suggest that scholars should develop meta-analysis to understand the complex tapestry of long-term pandemic mechanisms. Many policy implications follow directly: an efficient public intervention must be characterized in the long term by flexibility, pro-market orientation, and design customization.

The paper is structured as follows. Section 2 explains the selection methodology used in the review. Sections 3 , 4 , and 5 describe, respectively, the long-term effects of pandemics on: labor and human capital; investment and physical capital; and knowledge and innovation. Section 6 critically discusses the survey and summarizes the main lessons drawn from the literature for researchers and policymakers. Section 7 concludes.

Methodology

This literature review aims to illustrate, compare, and discuss the mechanisms through which pandemics affect long-term economic development. To achieve this goal, we adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology (Moher et al. 2009 ). First, we defined a list of keywords that express the main aspects of the “pandemic” and “economic development” concepts. Second, we identified which data sets to search: JSTOR, IDEAS/RePEc, Google Scholar, and EconLit. We excluded working papers and unpublished articles from our search, to ensure that the mechanisms presented are accepted by the scientific community. Moreover, we restricted our focus to the fields of economics and economic history, to ensure the economic relevance of the mechanisms described. Finally, we excluded papers focused on the COVID-19 pandemic, as it is too early for a comprehensive evaluation of its long-term effects. Applying these criteria, we obtained a first sample of more than 4800 potential articles. Important contributions were not missed due to excessively strict methodological adherence, we also parsed the references lists of the most influential contributions within our initial corpus, identifying in this way 178 additional relevant manuscripts to potentially include in our review.

From this corpus of potential articles, we operated a further selection by analyzing their abstracts and, in uncertain cases, by searching the main body of the paper concerned for evidence of relevant discourse, thereby identifying 805 potential contributions. We then proceeded to evaluate the selected articles for inclusion according to their relevance to our research topic and their relative originality, evaluated in terms of the mechanisms analyzed. We then proceeded to summarize the resulting papers according to their research questions and aims, their theoretical references, their methodology, and their results, focusing on the featured economic mechanisms, in order to identify the structure of our corpus in terms of the main debates, the empirical object of study, the methods applied, and the theoretical foundations. In this way, after eliminating redundant contributions, we selected 88 articles, each describing specific mechanisms through which pandemics may affect the economic system in the long term. Finally, we identified a criterion to organize the resulting mechanisms, inspired by the well-known Solovian model of long-term growth, dividing them into the following three broad categories: labor, capital, and innovation.

We then identified a corpus of high-quality contributions, each offering a specific contribution to the academic debate in terms of one or more relevant mechanisms, supported by either theoretical or empirical arguments. Figure  1 summarizes the main steps of the selection process by using a PRISMA diagram.

The PRISMA process

Labor and Human Capital

The most intuitive and direct effect of pandemics is the adverse shock to the population and the labor market. Delfino and Simmons ( 2005 ) propose a Lotka-Volterra model showing that a negative demographic effect could become persistent if the pandemic is not eradicated. The magnitude of this effect is, however, mediated by contextual factors. Alfani ( 2013 ) shows that, in southern Europe, the plagues of the XVII century had higher mortality and territorial pervasiveness compared with those affecting northern Europe in the same period and the southern Europe plagues of the previous century. Furthermore, the rate of mortality and territorial pervasiveness was heterogeneous among Italian regions and cities. Using a long-term perspective, Rodríguez-Caballero and Vera-Valdés ( 2020 ) find that pandemics reduced the unemployment rate persistently from 1854 to 2016 in Italy, Spain, the Netherlands, the UK, and the US. They also observe that, in the UK, pandemics reduced the GDP per capita over 1270–2019, and that this effect was increasingly persistent in the last 300 years. Fiaschi and Fioroni ( 2019 ) have built a model which shows how pandemics’ impact on growth trajectories is mediated by the production structure and the mortality reduction brought by technological progress. Bloom and Sachs ( 1998 ) observe that the mortality and morbidity of pandemics are highest in tropical regions. They explain that differences in climate and nature, together with anthropomorphic factors, affect the spread of the virus over the population. However, this direct effect on labor and population could decline in the long term.

The long-term effects of pandemics on the labor supply also depend on their impact on fertility. By analyzing 15 relevant infectious diseases from 75 countries between 1940 and 2000, Acemoglu and Johnson ( 2007 ) find that pandemics reduce demographic equilibria in the long term through their impact on fertility rates. Birth rates are influenced directly, as the pandemic reduces the number of fertile women, and indirectly, as future life expectancy influences decisions to have children in the long term. They empirically confirm that the higher mortality of those affected by infectious diseases sharply reduces births and slightly reduces the share of the young in the population because of their lower life expectancy. Lorentzen et al. ( 2008 ) show that a pandemic affects not only fertility, i.e. the number of births, but also the net fertility, i.e. the fertility of the surviving population. Parents care about the number of surviving newborns: higher infant mortality increases births. Moreover, parents invest time and money in their children, who become irreplaceable when they grow up. Therefore, higher adult mortality increases fertility, even more than infant mortality. Finally, given the family budget constraint, parents must choose between the quantity and quality of their children. Consequently, the uncertainty of the pandemic reduces the investment rent in human capital, leading parents to rationally prefer quantity to quality. The authors find empirical support for these hypotheses, observing that the probability of contracting malaria negatively affects adult and infant life expectancy, and that both expectations improve the fertility rate.

Fertility mechanisms interact with human capital accumulation. Lagerlöf ( 2003 ) describes an overlapping-generations model where adults confront the children’s quality-quantity trade-off. Infant survival is negatively affected by both the chance of random pandemics and population density, which both increase the risk of contagion, but is positively affected by human capital (higher medical knowledge), which is cumulative in time and positively affected by population density (knowledge spillovers). They find that, when pandemics are frequent, where the decision to have children is concerned, parents prefer quantity to quality; human capital does not increase; and population density remains low. When sufficient human capital has accumulated, however, the growth path of the economy is no longer affected by new pandemic waves. Consequently, only if, by chance, pandemics do not strike for a sufficiently long time, will parents then increase their investments in future generations, thus reaching the human capital threshold necessary to achieve robust growth trajectories. Gori et al. ( 2020 ) integrate all previously described mechanisms in a three-stage overlapping-generations growth model, including adolescent, adult, and elderly agents. In this model, only the elderly are sexually inactive and are, therefore, not exposed to HIV infection. The probability of dying from the pandemic is negatively associated with human capital endowment and positively associated with the number of virus-spreaders. The pandemic increases both infant and adult mortality. Adult mortality reduces both labor supply and life expectancy. If life expectancy is reduced below a certain threshold level, parents prefer to have more children; otherwise, they prefer to invest in human capital. Parameterizing the model for the Sub-Saharan African countries, Gori et al. ( 2020 ) find that HIV reduces labor supply and human capital but increases fertility. Cervellati and Sunde ( 2015 ) model an economy where parents confront the children’s quality-quantity trade-off, given the child mortality and the inborn ability of the offspring. Also in this model, higher human capital leads to an improvement in both medical care and adult life expectancy: intensive economic growth follows an initial quasi-stagnation. Cervellati and Sunde ( 2015 ) observe, like Lorentzen et al. ( 2008 ), that adult mortality and human capital affect the economic dynamics more than fertility and child mortality. Cervellati and Sunde ( 2011 ) combine Lorentzen et al. ( 2008 )‘s life expectancy effects on mortality and fertility with the Acemoglu and Johnson ( 2007 )‘s model and find non-monotonic patterns of demographic growth. Before the demographic transition, more newborns could compensate for higher mortality, leaving the overall demographic effect ambiguous; after the demographic transition, parents prefer quality over quantity in regard to children, making pandemic demographic effects definitively negative in the long term.

A pandemic’s negative demographic impact reduces the number of available workers. However, its long-term impact is mixed. Gori et al. ( 2020 ) and Dauda ( 2019 ) provide a comprehensive literature review of the complex link between HIV and growth. They conclude that, while strong evidence exists for a negative link at the micro level, the empirical support for the macro effects is weaker. Keogh-Brown et al. ( 2010 ) find four ways in which the pandemic can affect the work supply. Death and infection of workers result in a temporary reduction of the workforce, partially persistent in the long term. However, they observe that these effects could be mitigated by migration (see also Alfani 2013 ), labor market inefficiencies (see also Bloom and Mahal 1997 ), and inventories. Using a structural econometric model of the UK to estimate the economic effects of a modern pandemic, they conclude that it would reduce production and increase firms’ costs, leading to the emergence of inflation in the long term. Voigtländer and Voth ( 2013 ) describe a model where pandemics reduce population but increase labor in the manufacturing sectors. Since the land supply remains constant, labor productivity increases, and therefore survivors’ wages are higher than they would be without the pandemic in the long term. If the welfare increase is sufficiently high, the demand for manufactured goods increases trade and population density. Moreover, manufactured goods are easily taxable, thus enabling the financing of more wars. All these mechanisms increase the transmission of disease, leading to long-term demographic stagnation. Using data on the Black Death, the calibrated model correctly approximates the growth of both the European urbanization and per capita GDP from 1000 to 1700.

Historical research provides further support for the hypothesis. Herlihy ( 1997 ) confirms that wages and the demand for manufactured goods increased after the Plague; however, he observes higher lethality for adults than for both the young and the elderly. The Black Death first reduced the number of available workers and the length of their productive life. Additionally, the Plague took away both the skill and experience of previous workers and the parent’s investment in the education of their children. Moreover, high turnover increased labor demand, further reducing the productivity of new workers in the long term. Low labor supply increased wages, as land rents decreased. Finally, consumption grew quantitatively, shifting qualitatively towards higher-quality goods, leading to the emergence of a positive long-term impact on the real wages and welfare of the survivors. Pamuk ( 2007 ) supports all Herlihy ( 1997 )‘s results. Moreover, he finds that the great difference in economic growth between North and South Europe, which is observed only some centuries later, originates from the Black Death of the fourteenth century. Indeed, if at first the Plague increased wages across Europe, afterwards, when the population began to grow again, the real wages remained persistently higher in North Europe. The higher flexibility of institutions and guilds allowed a better economic and social response to the Black Death in the North, for example by obtaining lease contracts more advantageous for farmers, or making it easier for women to enter the labor market, and then structurally and radically changing the fertility rate and demographic trends in those countries. Alfani and Percoco ( 2019 ) produce empirical evidence that the plagues that infested Italy in the XVII century also led to long-term reductions in real wages. Indeed, although the population remained below pre-plague levels for more than two centuries, the reduction of skills (as well as of capital and technologies) was particularly large for various reasons. First, these plagues were particularly severe compared with the outbreaks in other European countries. Second, these plagues hit all population strata equally, including the poor, nobles, and bourgeois alike. Moreover, the demographic impact was not compensated by migration flows. Finally, the destruction of human capital reduced the competitiveness of the Italian economy.

Economists disagree on the intensity of the long-term effect of pandemics on the accumulation of human capital. Bleakley ( 2010 ) shows that the effect of the pandemic on schooling is uncertain due to the simultaneous decrease in both benefits (following lessons is more difficult) and opportunity costs (labor productivity is lower). Moreover, he observes that the pandemic could already have negative effects on the intellectual development of the child during gestation. Almond ( 2006 ) supports this argument using 1960–80 decennial microdata to analyze the long-term effects on those US children who were conceived during the Spanish flu. He observes that, if the mother was infected during pregnancy, then her offspring had lower educational attainment and a higher probability of being physically disabled. Both factors reduce their future wages and then increase their participation in illegal activities and, more generally, harm their socioeconomic status 40, 50, and 60 years after the pandemic. Parman ( 2015 ) resizes the effect, affirming that in the US the Spanish flu did not affect human capital in aggregate because parents redirected their investments towards older siblings. Meyers and Thomasson ( 2021 ) show that in 1916 the negative effect of polio on human capital differed between the US states and also depended on the age of students and the family income. However, the effect is usually nonlinear on age and more damaging to the richest because of the specific characteristics of polio.

The relationship between pandemics and human capital accumulation has been studied not only in the US. Odugbesan and Rjoub ( 2019 ) show that, for 26 sub-Saharan African countries from 1990 to 2016, the link between a pandemic and human capital is negative and bidirectional due to persistent short-term effects. Using two Tanzanian databases, Wobst and Arndt ( 2004 ) show that the HIV pandemic has decreased human capital (and then wages and income per capita) in at least four ways. First, the pandemic has directly and persistently reduced labor supply and skills availability. Second, the number of teachers has also decreased, worsening the quality of the process of accumulation of human capital. Third, the lower labor supply has increased the demand for new workers, raising the opportunity cost of education for the young, thus reducing the need for human capital investments. Finally, the pandemic has also reduced the long-term demand for education through an increase in the number of orphans. Novella ( 2018 ) confirms the last link using a Zimbabwean survey for 2007–8. This revealed that orphans leave (secondary) school early and hence enter the labor market early compared with non-orphans. The worst effects emerge when both parents are dead or when the household is blended, i.e., when orphans and non-orphans live together. He also observes that this lower household income after a parent’s death only partially explains the lower investment in the orphans’ human capital. Evans and Miguel ( 2007 ) extend previous results for Kenya. Analyzing an extensive database of over 20,000 children, they observe that not only are orphans more likely to quit primary school, but the probability is higher in those cases where the mother dies and/or their academic performance was already weak. Therefore, they conclude that the inability to pay school fees and the need to find work seem less significant in the long term than the lack of emotional support and the presence of psychological trauma. Fortson ( 2011 ) models the schooling decision that maximizes the expected present value of lifetime utility, considering that HIV reduces its discount rate. He uses data of 15–49-year-olds covering the birth cohorts 1952–91 in 15 sub-Saharan African countries in order to confirm that HIV reduces longevity and human capital investments persistently in the long term. Moreover, the author suggests that both orphans and non-orphans are affected by pandemics, and that decreased schooling provision does not play a key role. Many scholars have analyzed the effects of HIV on educational achievements. Bell and Gersbach ( 2009 ) confirm all previous results by using an overlapping-generations model where both parents and children decide how much to invest in human capital. Moreover, they observe that (i) selective health and educational policies are more effective than comprehensive ones; and (ii) simultaneous health and educational policies are more (less) efficient than sequential ones if disease mortality is above (below) a threshold level.

Young ( 2005 ) combines two fertility effects with the orphan effect. First, if the virus is sexually transmitted, e.g. by HIV infection, then unprotected sexual activities and births are reduced. Second, the labor supply contraction, induced by the pandemic, improves wages and then reduces the mothers’ fertility. Third, lack of parental guidance reduces the human capital of orphans. These emerging long-term effects are mixed. Calibrating the model with South African microdata, he finds that: the female labor supply is more elastic than the male labor supply; fertility effects always prevail in the long term despite pessimistic assumptions; and per capita income tends to increase. Some scholars find that, in addition to human capital, pandemics depress other types of intangible capital. Aassve et al. ( 2021 ) show that the Spanish flu decreased social capital for many generations in the US. They use a long-term social trust survey and discover that: (i) the immigrants born after the Spanish flu and their heirs have lower social trust than those born before; and (ii) the effect is higher for those from countries with less uncensored information on pandemic effects. Using a behavioral experiment in Uganda, McCannon and Rodriguez ( 2019 ) find that grown-up orphans tend to have lower social capital. The probability of prosocial behavior is lower because orphans are more pessimistic about the community’s social contributions. McDonald and Roberts ( 2006 ) analyze data for 112 countries from 1960 to 1998 to determine how much HIV and malaria affect health capital and, consequently, income per capita growth in the long term. They observe that the degree of HIV prevalence in a country negatively affects health capital directly and economic growth indirectly. Moreover, they observe that this mechanism is significant in Africa, through both HIV and malaria, and in Latin America, only through HIV, but not in OECD and Asian Countries. Focusing on sub-Saharan Africa, Odugbesan and Rjoub ( 2019 ) confirm that income plays a key role in explaining the long-term effects of a pandemic. However, the direction of their results is reversed: the bidirectional link between a pandemic and human capital for upper-middle-, low-middle-, and low-income countries is, respectively, negative, positive, and insignificant.

Finally, the majority of effects described in this section are generally more severe in low-income countries. Here, reduced access to medical care, undernourishment, and the presence of other diseases could induce a poverty trap (Beach et al. 2021 ; Bloom et al. 2021 ; Lorentzen et al. 2008 ). A Malthusian equilibrium with low income, underinvestment in schooling and health, and high fertility emerge for tuberculosis (Delfino and Simmons 2005 ) but only partially for malaria (Bloom and Sachs 1998 ; Gallup and Sachs 2001 ). Moreover, the poverty trap is unclear for HIV, where both positive and negative pandemic effects on income distribution could emerge (Bloom and Mahal 1997 ; Bloom and Sachs 1998 ; Mahal 2004 ). Alfani ( 2021 ) suggests that high-mortality pandemics, like the plague, could reduce poverty by either exterminating the poor or redistributing income to the poor. Vice versa, Karlsson et al. ( 2014 ) suggest that low-mortality pandemics, like the Spanish flu, increase poverty due to pandemic-induced unemployment, inability to work for long periods, and general loss of income. As these effects are particularly severe and persistent for poor households, pandemics could aggravate inequality. Therefore, the long-term effects of pandemics on income distribution appear to depend on the medical profile of the disease.

Investments and Physical Capital

While pandemics affect the long-term dynamics of labor supply and human capital also through durable short-term mechanisms, their impact on capital and savings arise in the long term specifically. Acemoglu and Johnson ( 2007 ) argue that, since land and physical capital are not affected in the short term, the lower levels of labor supply and human capital reduce GDP but have an unclear effect on per capita income. Since pandemics reduce GDP and income growth, they also reduce physical capital accumulation, thereby triggering a long-term negative loop between GDP and capital. The authors hypothesize that, in the long term, GDP per capita should drop in high-income countries but not in low-income countries, where land is more relevant than physical and human capital, and the negative loop effect is weaker.

Bai et al. ( 2021 ) confirm that the long-term pandemic effect differs among countries. They show that infectious diseases in the last 15 years have increased permanent volatility in the US, UK, China, and Japan capital markets. However, public policies of correct timing and intensity could reduce the effect. Ru et al. ( 2021 ) find that countries that have already experienced similar pandemics react better and more readily to future pandemics, especially if past pandemics have led to deaths. Analyzing the 65 largest financial markets in the world, the authors note that countries with firsthand SARS experienced the deepest fall in the stock market during the COVID-19 pandemic. This reaction is positively correlated to the pandemic’s mortality. Donadelli et al. ( 2017 ) confirm that, from 2003 to 2014, disease-related news had adversely affected the returns of the pharmaceutical stock market. Analyzing 102 pharmaceutical firms listed on the US stock market, the authors note that investors were too optimistic about the future liquidity of pharmaceutical sector flows after the shock. This irrational behavior has a positive and persistent effect on the returns of the pharmaceutical stock portfolio. Cakici and Zaremba ( 2021 ) extend the previous results outside the pharmaceutical sector. They observe that pandemics induce irrationality among investors, impacting assets across countries and firms heterogeneously. Analyzing 19 international stock markets, they observe that the stock trend signals to investors the firms’ resilience and ability to react to negative shocks, leading to increased future share performance. Summarizing, the literature analyzing the effects of pandemics on equity markets concludes that these health shocks induce irrational behavior of investors, causing positive and negative long-term effects, heterogeneous among countries, sectors, and firms.

Consensus among scholars is lacking in regard to both the size and direction of the long-term pandemic effects on investments and physical capital. Cuddington ( 1993a ) observes that pandemics affect labor demand and capital markets. The total effect on wages is uncertain: supply shock increases wages, but the demand shock reduces them, because infected workers are less effective, as they need to take sick leave and are less productive. Pandemics also affect domestic capital accumulation because health care costs reduce savings. Therefore, the total impact on capital per capita, GDP, and GDP per capita is uncertain; however, calibrating the model with Tanzanian data, he finds that both GDP and GDP per capita sharply decreased from 1985 to 2010. Cuddington and Hancock ( 1994 ) confirm the result for Malawi, although the lower number of infected people reduced the long-term effects on the economy. Moreover, Cuddington (Cuddington 1993b ) observes that previously predicted effects also hold when formal and informal productive sectors coexist, and formal wages are sticky. Basco et al. ( 2021 ) affirm that the Spanish flu in Spain was primarily a demand shock but confirm that the pandemic impact on the real return of capital is ambiguous in the long term. Although at the theoretical level Karlsson et al. ( 2014 ) confirm the ambiguity of the long-term effect of the Spanish flu on the per capita return on capital, this ambiguity is not observed in the empirical analysis of the Swedish counties. Indeed, by analyzing the effects in the decade following the pandemic, the authors estimate no statistically significant effect on earnings per capita, but clear negative effects emerge on capital returns per capita. Finally, Jinjarak et al. ( 2021 ) show that the H3N2 pandemic reduces GDP, consumption, and the investments of 52 countries.

Other scholars demonstrate that the effect of pandemics is heterogeneous among sectors, a trait shared with most disasters (Halkos and Zisiadou 2019 ). In Egypt, pandemics depleted the rural workforce necessary for the maintenance of the crucial centralized irrigation system, which remained in a state of disrepair, hampering the well-being of the region for centuries (Borsch 2005 , 2015 ). Herlihy ( 1997 ) shows that the rise in wages following the Black Death increased demand for more nutritious and elaborate goods, diversifying consumption and improving welfare. Similarly, Pamuk ( 2007 ) shows that the Plague increased the demand for luxury goods in particular. Moreover, he observes a reduction in interest rates and increased investments, although with asymmetric components. Indeed, Alfani ( 2013 ) shows that the XVII century plague depressed Italian industries, in particular, the wool, flax, silk, and construction sectors, due to the loss of skills and the impossibility of procuring raw materials. Alfani and Percoco ( 2019 ) highlight that the shift of investments from urban to rural activities in this period reoriented the post-plague Italian manufacturing sector towards the production of semi-finished and low-quality goods. Summarizing, scholars observe that short-term changes in the relative composition of both demand and supply structures can lead to long-term sectoral effects.

Similar sectoral asymmetric effects have been recorded for more recent pandemics. Analyzing the potential effects of SARS in Asia, Lee and McKibbin ( 2004 ) find that countries specializing in trade and the tertiary sector are more damaged by both temporary and persistent pandemic shocks. Indeed, in these sectors, close contact with other people is often necessary. The retail and tourism sectors are particularly vulnerable. Gallup and Sachs ( 2001 ) provide further support by showing that Mediterranean and Caribbean countries benefited from the rapid and stable development of the tourism industry after the eradication of malaria. Finally, Mahal ( 2004 )‘s literature review on HIV effects shows a similar, although weaker, effect for sub-Saharan tourism. Moreover, the author shows that health, transport, and the primary sectors are also negatively affected by HIV. Pandemics affect the health sector by increasing costs for healthcare services and insurance. Moreover, he shows that workers in the transport and primary sectors belong to the social classes most affected by HIV. Oster ( 2012 ) finds that export is an essential explanation of the spread of HIV in Africa because more truckers and miners, among others, stay away from home for more extended and more numerous periods. As a result, they and their partners are more likely to engage in risky sexual intercourse, putting themselves and their stable partners in danger. She also affirms that trade could further aggravate the effect in the long term, as additional income could increase the amount of money spent on prostitution, or mitigate it, if money is spent on preventive measures. Using a quasi-experimental variation, Adda ( 2016 ) confirms that the new transportation networks and inter-regional trade accelerated disease diffusion in France from 1984 to 2010. Delfino and Simmons ( 2005 ) combine the effect of capital and labor, using a Lotka-Volterra predator-prey model where only healthy individuals are productive. The authors observe that the introduction of capital makes the path more complex, but that the economy still cyclically converges to a stationary equilibrium. Indeed, when labor supply decreases, GDP decreases. Therefore, both savings and investments are lower, and GDP per worker also decreases. Lower welfare reduces health services consumption, but the impact on the disease transmission is uncertain: it increases as the share of infected rises, but it decreases as the contagion period became shorter. When the labor supply increases again, the cycle restarts. Augier and Yaly ( 2013 ) show that complex growth paths could emerge even in a model where the pandemic affects only capital accumulation. The authors describe an overlapping-generations model where the pandemic increases premature deaths, and then only the survivors will use savings previously accumulated. The government proposes a funds system that redistributes rents among the survivors. Young people must decide how much to invest in this public fund, and how much to spend on health or other goods, knowing that better health reduces the chance of dying prematurely. They observe that the pandemic, capital, and health investments are linked in an articulated and recursive way: (i) the pandemic causes health investment to drop; but (ii) health investment reduces the diffusion of the pandemic; (iii) capital directly affects the investment; and then (iv) it indirectly affects the spread of the pandemic. Therefore, the economy converges to a long-term equilibrium only when contagion rates are low. Finally, Stiglitz and Guzman ( 2021 ) show that pandemics act as an unanticipated technology shock, generating unemployment that government intervention can effectively counteract. In the long term, uncertainty does not decline, thus further increasing the desirability of government intervention.

In Section 3 , we showed that, after a pandemic, life expectancy decreases because a healthy lifespan becomes more uncertain than before, leading to decreased investments in human capital. Similarly, scholars observe that the pandemic also reduces investments in physical capital. Lorentzen et al. ( 2008 ) show that the indirect effects of malaria on life expectancy are higher on physical rather than on human capital investments. Analyzing different databases and case studies, Gallup and Sachs ( 2001 ) conclude that the effects on per capita and total income are negative because both foreign investments and the revenues from tourist and business travelers are drastically lower in those countries affected by malaria. Analyzing the effects of HIV on 43 Asian countries from 1990 to 2015, Fawaz et al. ( 2019 ) conclude that investments and savings are usually inversely related to that pandemic. However, they show that both the sign and the intensity of the effect could differ depending on how far-sighted people are. Additionally, in low income countries, the negative effect of investment is independent of gender, but the pandemic affects men’s saving propensity more than women’s. Vice versa, in high income countries, when life expectancy decreases because of pandemic mortality, men save more but do not increase their investments, while women save less but invest more. Bloom and Mahal ( 1997 ) also focus on savings behavior, using it to explain the insignificant effect of HIV on the income per capita growth rate in 51 countries from 1980 to 1992. First, they observe that poor people are most affected by HIV, and that expensive medical treatments further aggravate their disadvantaged situation. However, social and economic mechanisms partially compensate for the high costs of official health services. Second, higher care costs cause both consumption and savings to drop. Moreover, lower life expectancy may increase precautionary savings in favor of surviving family members. Garrett ( 2008 ) studies the economic and social effects of the influenza pandemic 1918–9 in the US, analyzing newspaper articles and academic papers to draw lessons for modern pandemics. He observes that health care is relevant only with ideal health systems that certainly do not collapse after a pandemic, no matter how serious it is. Moreover, he concludes that, although a higher percentage of life insurance mitigates the adverse financial effects of a pandemic on households, the wealthiest households that will need it least will also be the more protected. Gustafsson-Wright et al. ( 2011 ) show that, in the case of pandemics, the private insurance system can be unfair and distortive, even in countries like Namibia, where the quality of public health care is relatively high, and most people have health insurance. The poor who cannot afford health insurance suffer from higher medical expenditure during a pandemic. There are no substantial effects on medical expenditure and family income until the virus starts affecting working capabilities; then, the economic consequences for the poorer strata worsen severely.

The comprehensive review from Hallegatte et al. ( 2020 ) confirms that poor people are disproportionately affected by natural hazards and disasters. Pandemics are no exception. Gaffeo ( 2003 ) provides additional support for the idea that pandemics can lead households into a poverty trap. Higher care costs and physical weakness reduce income capacity: for poor households, this leads to malnutrition, further reducing their physical capabilities, and increasing the pandemic’s morbidity and mortality. Physical and human capital trends reinforce this adverse and cumulative loop. Finally, he observes that pandemics worsen market failures for health insurance and local credit availability. Due to adverse selection and moral hazard, the higher uncertainty and information asymmetries inherent to pandemics lead to higher insurance premiums and reduced access to credit for the needy. Habyarimana et al. ( 2010 ) show that, while private firms could invest in their workers’ medical care, they are unlikely to do so. They describe the case of the pioneering firm Debswana Diamond Company in Botswana, which, since 2001, has invested in a program to improve the health of its workers affected by HIV. They observe that the treatment works, but the investment is unprofitable as the costs are too high, supporting the idea that African firms can only bear a small share of their workers’ health costs, if any.

While the previous literature shows that a pandemic increases income inequalities, Odugbesan and Rjoub ( 2019 ) argue that pandemics could hinder sustainable development. In this connection, these authors analyze the link between HIV and both public and private adjusted net savings, as an indicator of sustainable economic development, for 26 sub-Saharan African countries from 1990 to 2016. They show that HIV negatively and unidirectionally affects saving, and that the effect is particularly intense for upper-middle- and low-income countries. HIV also negatively affects the perception of government efficiency in low-middle-income countries. Odugbesan and Rjoub ( 2020 ) show that, for 23 sub-Saharan African countries from 1993 to 2016, the adverse relationship is bidirectional because the HIV control program and sustainable development compete for the same public spending budget. Keerthiratne and Tol ( 2017 ) show that the financial impact of disasters, pandemics included, is country- and time-specific. Moreover, Chakrabarty and Roy ( 2021 ) propose a model where the future pandemic uncertainty reduces government allocation of non-health expenditures in favor of the health ones. In 143 countries from 2000 to 2017, they found that higher-debt countries present a public misallocation and delay due to public constraints. A similar effect also emerges in low-income countries, but this is due to asymmetric information. Bai et al. ( 2021 ) show that, up to a point, the effects of pandemics could be efficiently mitigated with fiscal and monetary policies. Finally, Cavallo et al. ( 2013 ) confirm that governments and institutions could play a key role in the economic effects of a pandemic. Using a database from the Centre for Research on Epidemiology and Disasters, they observe that natural disasters, such as a pandemic, have a long-term negative economic impact only when they simultaneously cause a high number of deaths and are followed by institutional and political revolutions.

Knowledge and Innovation

Historians have identified numerous cases of pandemics being catalysts of significant, systemic change. In his comprehensive overview of the impact of the Black Death on Europe, Herlihy ( 1997 ) argues that it led to larger economic diversification, improved technology, and better lives, breaking the XIII century Malthusian deadlock by directing technological change towards the now cheaper input, i.e. capital. Although educational institutions were gravely hit, with one-sixth of European universities closed, as a long-term reaction to this short-term impact, a number of new educational institutions were built in reaction to the dearth of scholars. The new universities adopted more flexible curricula, contributing to the revival of classical studies. The need to face the Plague also forced the acceptance and diffusion of anatomical studies, fostering the development of the scientific approach in medicine. Epstein ( 2000 ) offers a similarly positive account, underlining how the Black Death brought much needed renewal. European feudalism was locked in a low-growth pattern, not because of lacking innovative capabilities, or market institutions, but rather due to the intensity of seigniorial rights, and the jurisdictional power of towns and lords, which were used to maximize the extraction of resources, mostly for military purposes, greatly hampering development. The scarcity of workforce caused by the Plague shock reduced the bargaining power of the landowner in favor of the worker. The resulting political and economic struggle is described as a process of “creative destruction”. The centralization process was greatly accelerated, leading to the consolidation of internal markets, the standardization of legal procedures and business norms, and the progressive rationalization of hierarchies. As a result, in the long term, transaction costs and economic uncertainty declined significantly, as testified by the structural decline in interest rates, which quickened the pace of innovation and trade growth. One of the long-lasting consequences of the pandemic for Europe was a more centralized, less predatory authority, able to support the process of economic development.

The institutionally “liquidationist” account of pandemics also applies to other centuries. For example, Alfani ( 2013 ) observes how plagues irrevocably affected the balance of power in Italy, favoring the rise of the House of Savoy, which eventually led to the Italian unification. Pamuk ( 2007 ) describes how the Plague created local skilled labor scarcity, incentivizing migration and fostering the dissemination of knowledge in the long term. Higher wages stimulated the substitution of land and capital for labor, creating conditions favorable to the implementation and diffusion of labor-saving innovations across all economic fields: the printing press, firearms, and high-capacity maritime transportation can all be linked to this general trend. Voigtländer and Voth ( 2013 ) offer what is perhaps the more optimistic view of the long-term impact of the Black Death, arguing that the positive impact of the persistently high European mortality rates dwarfed the effects of technological change for the entire 1500–1700 period. Clark ( 2007 ) provides a useful counterfactual, analyzing how the Far East, relatively less affected by plagues, maintained a growth regime characterized by both low income and low mortality. Not all plagues, however, are described in such a positive light.

Alfani and Percoco ( 2019 ) document the significant negative impact of the plague of 1629–30 on the long-term development of the Italian cities and the Italian economy. In addition to the mechanisms already explored in the previous sections, the authors argue that the significant losses suffered by the urban economic elite, who controlled most of the advanced manufacturing activities, caused an “ingenuity shock”, i.e. decreased both the availability and the willingness of the surviving elite to innovate in the urban industry, preferring agricultural investments instead. The latter took a dramatic hit in terms of production capabilities, which recovered only after decades. The exceptionally late recovery slowed the process of recovery and urbanization, weakening the Italian competitive position vis-à-vis Northern Europe in manufacturing. The almost uniform lack of wage increases signals how the long-term reduction in supply capabilities was not a consequence of lacking a skilled workforce, but rather a significant long-term change in the pattern of capitalist investments. This argument is important to underline how general, systemic renewal might encompass significant relative changes. The hypothesis that the plague did not damage, and perhaps even fostered, European development as a whole, is entirely consistent with the description of significant short- and long-term harm being wrought to large sections of the continental socioeconomic system. This is also consistent with Pamuk ( 2007 )‘s description of the divergence between North and South Europe, which emerged in response to the Plague as a consequence of the greater entrenchment of Southern political and economic elites, and the associated slower degree of institutional flexibility and, consequently, innovation and knowledge diffusion. In his recent overview of the subject, Alfani ( 2021 ) provides further evidence for the relevance of institutional change and policy choices on the long-term impact of pandemics on economic distribution and growth, illustrating how pandemics create opportunities for institutional change while also creating issues that, if not effectively tackled, can severely worsen the economic conditions of the poorer sections of the population.

On the negative side of the debate, Bar and Leukhina ( 2010 ) argue that epidemics have the capability to disrupt knowledge transfer across generations, leading to significant reductions in total factor productivity growth over time. They show that the long-term loss is moderated by the possibility of knowledge diffusion from regions that were spared negative health shocks, implying that the scope of this negative mechanism would be much greater in the case of a pandemic. Karlsson et al. ( 2014 ) document the impact of the Spanish flu on the Swedish economy, finding a long-term negative effect on capital income and a positive effect on the rate of poverty, both possibly driven by a significant persistent loss of skilled workers and consequently a decline in labor productivity. Jinjarak et al. ( 2021 ) show that the H3N2 epidemic can have permanent negative effects on productivity. Indeed, also when the productivity rate returns to its pre-shock level, some opportunities are lost or delayed forever, and then the innovation path will be always lower than without pandemics. Chen et al. ( 2021 ) even state that epidemics have the worst impact on innovation among natural disasters. Indeed, they affirm that epidemics reallocate public expenditure from innovation to health, reducing patent applications and innovation in 49 countries over 1985–2018. In Eastern Europe, feudal lords reacted to epidemics by re-enslaving the peasantry, greatly hampering the diffusion and implementation of new agricultural techniques, and locking the regions in a relative underdevelopment pattern called “second serfdom” (Domar 1970 ; Robinson and Acemoglu 2012 ). Similarly, the plagues affecting the Roman Empire and its successor states led to persistent socioeconomic degradation, aided by conservative political reforms introduced by the surviving elites (Duncan-Jones 1996 ; Sarris 2002 ; Little 2007 ; Harper 2016 ).

Yet pandemics are also great opportunities for the creation and diffusion of new knowledge. Bresalier ( 2012 ) documents how the Spanish influenza pandemic of 1918–9 was a turning point in the modernization of British medicine, leading to the establishment of key institutions and organizations that would shape the long-term development of medical research and healthcare, chief among them the Medical Research Council. The latter led to a wider active involvement of the state in sanitary matters. In general, the author shows that the pandemic’s effects were instrumental in developing the modern medical research system. Hopkins ( 1988 ) provides a description, similar in spirit, of how the successful smallpox eradication campaign conducted by the World Health Organization led to organizational learning, and the development and institutionalization of best practices, thereby greatly enhancing global medical response and prevention capabilities. Furthermore, large shocks, such as pandemics, can create windows of opportunity for change. This is echoed by Cohen ( 2019 )‘s review of the same episode, concluding that, while research and innovation activities played a key role in ensuring the campaign’s success, these efforts were at first greatly hindered by inappropriate practices and institutional routines. Only when the involved organizations implemented new and improved procedures did technological solutions become truly effective. While the scale differs, the argument echoes Pamuk ( 2007 )‘s. Wallace and Ràfols ( 2018 ) show that the avian flu highlighted how both excellence-based funding schemes and economic interests contribute to unduly restrict the field of active research as compared with the broad range of scientific opinions offered by experts, resulting in the development of a limited selection of techniques from the available knowledge base.

Analyzing the impact on the knowledge generation of vaccination subsidies, Finkelstein ( 2004 ) observes that, apart from the direct health impact from the eradication of illnesses, higher expected profitability might lead to socially wasteful competition for market share in the long term. Empirical evidence supports the hypothesis that the outcome depends on the state of the technological frontier and market conditions, as expressed by vaccination rates. In most cases, subsidies appear to lead to purely wasteful competition, but, in the case of the flu, there is evidence of increased product quality and demand, with the associated dynamic benefits outweighing static gains. Consistently, Kremer ( 2000 ) pointed out that market failures are endemic in the markets for both vaccine provision and vaccine research. While this opens up opportunities for policy intervention, it simultaneously underlines the challenges involved in the design of truly effective instruments. Similar challenges are described by Keohane ( 2016 ), in which innovative financial practices developed in the long term as a reaction to large shocks, including pandemics. He argues that “risk transfer for disease is a vital public good that the market has not otherwise provided” (ibid,130), and that new preventive and preparedness measures could be financed through the issue of catastrophe bonds. While these catastrophe bonds are expensive, the benefits of increased resilience in the face of health shocks might be a net gain, especially if the costs are somewhat lessened by pooled funds international initiatives. Although significant overlapping exists in terms of health-crisis preparedness and the organizational capacity of response, such an approach is probably more effective for estimating regional epidemic risks. Such instruments may be particularly useful in light of Confraria and Wang ( 2020 )‘s finding of persistent radical disparity between the disease burden carried by African countries and the amount of medical research dedicated to specifically African issues relative to global efforts.

The discussion so far has been focused on mechanisms that connect pandemics to the development of knowledge and practice, and from those to their economic and financial impact. Easterlin ( 1995 ) provides an original analysis based on a different viewpoint. Analyzing the steep decline in mortality that took place in northwestern Europe in the nineteenth century, he maintains that both the industrial and the health revolutions have a common root: the ascendancy of the scientific approach leading to technological change in both areas. The argument implies, on the one hand, that economic growth is not the main driver of life expectancy improvements, and, on the other, that improvements in health and life expectancy do not have a direct effect on economic outcomes, a position compatible with the relatively weak empirical evidence available (Acemoglu and Johnson 2007 ). The cause of structural change is argued to be found in the extraordinary stream of innovations implemented during the period, supported by a swarm of Schumpeterian “entrepreneurs”, only marginally motivated by profitability. Both those revolutions were triggered by the acceleration in the accumulation of usable empirical knowledge through the establishment and diffusion of the scientific method, the difference in timing to be imputed to the difficulty of developing and implementing the scientific solution. Deaton ( 2004 ) similarly argues that knowledge transfer, in the form of both effective practices and useful information, is key for explaining different national patterns of mortality decline and life expectancy increase, pointing out how globalization could benefit developing countries in this respect.

The argument is further expanded by Easterlin ( 1999 ), who showed that, while private firms have been crucial in fostering economic development, their role in improving health and especially infectious disease control practices has been marginal at best. Indeed, the preventive measures improve life expectancy more than the therapeutic ones, but firms rarely adopt them. However, the actions of households and governments are more important for disease prevention. The role of government is especially relevant because public action is necessary for both health education and prevention programs. Easterlin shows how irreplaceable effective knowledge and healthy practices are in the process of preventing and curing diseases, but how ineffective markets, contracts, and private property institutions have been in fostering their historical development, due to a number of related market failures. In fact, medical practitioners and public servants working towards the diffusion of salubrious norms have often found themselves hindered by economic actors defending their profitable, if deleterious, business. In his account of the US development, Gordon ( 2016 ) confirms both the decisive role of scientific advances and the importance of government intervention and regulation for the drastic improvement in health and life expectancy that took place in the nineteenth and twentieth centuries. However, Birchenall ( 2007 ) proposes an alternative explanation for the manifestly weak correlation between contemporaneous income growth and mortality, highlighting the significant long-term impact of income growth in terms of improved adult health and life expectancy, and subsequent mortality reduction. The argument is supported by a model illustrating how sustained economic growth, no matter the source, is sufficient to escape the Malthusian equilibrium, leading to drastically lower mortality in the process. Cervellati and Sunde ( 2015 ) provide further support by developing a model based on unified growth theory, also characterized by an inevitable take-off triggered by sufficient technological progress.

From the historical description emerges a complex interplay of negative and positive relations between health and business practices, driven by the contrast between short- and long-term interests, on the one hand, and private and public interests, on the other. This complexity is faced by Mokyr ( 2010 ) in his attempt to outline the principles of an evolutionary approach to the study of the development of useful medical knowledge. He begins by highlighting the two key idiosyncratic characteristics of such a knowledge field: the largely inelastic character of its demand, as all humans value their lives and health under all circumstances, and the relevance of negative exogenous shocks, such as the spread of pandemics. Medical knowledge maps to a set of instructions and recipes capable of guiding action, called techniques. According to context-specific selection criteria, only a subset of related techniques will actually be implemented for a given set of knowledge. While the actual usage of techniques is rival, knowledge can endlessly accumulate with only limited downsides. The evolutionary process of knowledge is mostly based on persuasion mechanisms; on the contrary, the related techniques are evaluated on their relative effectiveness. However, persistent empirical failure might not be sufficient as a selection mechanism, if no better technique is available on the basis of the socially accepted set of useful knowledge. This is particularly likely in the case of singleton techniques, based on the limited empirical knowledge that “this works”, and is therefore incapable of adaptation to sudden change. The shift towards scientific knowledge ensures that techniques are based on a more nuanced understanding of natural phenomena, enabling quicker and more efficient adaptation to exogenous shocks. Limits are provided by the path-dependency of knowledge development, which is only indirectly affected by the usefulness of related techniques. While this might result in the generation of “useless” knowledge, degrading response capacity in the present, sudden exogenous changes might lead to equally sudden revaluations. Summarizing, pandemics are a simultaneous shock to both practices and the underlying knowledge, as their often dramatic impact is sufficient to create opportunities for shifting entire development trajectories. The emergence of new knowledge and practices can be further amplified by diffuse and profound institutional change, which in turn may lead to significant upheavals, positive or negative. Owing to the complex nature of the outcomes, however, normative judgment lies beyond the capabilities of purely theoretical analysis.

The first key result of this review is that in the analysis of pandemics’ long-term economic consequences, historical and epidemiological characteristics are key (Donadelli et al. 2021 ; Meyers and Thomasson 2021 ). The extraordinary mortality associated with the Black Death is the most crucial factor in explaining its exceptional long-term consequences for European and global socioeconomic development (Pamuk 2007 ; Voigtländer and Voth 2013 ). Research on the consequences of HIV has rightly focused on its sexual transmission (Young 2005 ; Oster 2012 ; Fawaz et al. 2019 ; Gori et al. 2020 ) and the intergenerational consequences of increased mortality among working-age adults (Wobst and Arndt 2004 ; McDonald and Roberts 2006 ; McCannon and Rodriguez 2019 ). Therefore, the results offered by a general economic analysis of pandemics should be considered a wide collection of potential mechanisms, their empirical applicability and relative importance to be carefully weighed on a case-by-case basis. This does not imply that knowledge is not cumulative in this field, but rather that application of past knowledge should account for contextual factors in order to determine the likely long-term impact of a specific pandemic.

Our review of the literature goes one step further. By aggregating the pandemics by their effects on various economic factors, we observe some recurring trends, allowing some useful general conclusions to emerge. Table  1 provides a comprehensive overview of papers published in English focused on the relationship between pandemics and economic development. Following this paper’s structure, we organize the papers according to the mechanisms investigated into three broad categories: labor and human capital; physical capital and investments; and knowledge and innovation. We show that diseases can potentially affect all the productive factors of an economy in the long term. Most of the articles focus on the pandemic impacts on labor and human capital, all finding negative long-term impacts. However, some authors show that this effect could be partially mitigated in specific geographical areas, workers’ categories, and industrial sectors. The long-term effects on investment and physical capital are ambiguous: many papers show contrasting and complex mechanisms that do not allow us to know a priori the overall economic effects of pandemics on long-term investment trajectories. Notably, all papers which show long-term positive effects of pandemics on economic development focus on knowledge and innovation. However, negative cases also exist, leading many scholars to observe that the effect is potentially mixed, its direction dependent on necessary but not always implemented institutional changes.

The following general picture of the effects of pandemics on economic development emerges from our analysis. First, pandemics tend to reduce population and labor supply in both the short and the long term. This increases labor productivity, and therefore average wages. However, pandemics also hinder human capital accumulation, reducing productivity and per capita income growth. The negative effect is further compounded by the associated loss of knowledge, skills, experience, and innovative capabilities. Investments and savings are also negatively affected, leading to potential long-term hysteresis and the emergence of new, lower-income equilibria.

The pandemic shock can also break old patterns, opening new innovative trajectories previously inaccessible. The aggregate impact of these long-term mechanisms on the economic system is dependent on the relative relevance of, mostly harmful, adaptive mechanisms vis-à-vis potentially fruitful innovative responses. When the latter dominate the picture, negative long-term effects are overwhelmed by the benefits captured by radically new socioeconomic models of production, trade, and consumption. Therefore, the key factor determining the long-term impact of pandemics is identified with the innovation processes to which they give rise, and particularly the necessary accompanying processes of institutional change. While these effects are more difficult to capture using traditional economic methods, they are highlighted by historical analysis and should not be ignored by researchers and policymakers alike (Callegari and Feder 2021b ; Jena et al. 2021 ; Mandel and Veetil 2020 ).

Another important conclusion that can be drawn from this review is that most short-term outcomes, such as the immediate reduction in labor supply (Bloom and Sachs 1998 ; Alfani 2013 ), can bring, in the long term, significantly different consequences in both scope and quality when compared with the transient short-term effects (Delfino and Simmons 2005 ; Acemoglu and Johnson 2007 ; Basco et al. 2021 ). Several specific long-term mechanisms also emerge (e.g., Herlihy 1997 ; Young 2005 ; Augier and Yaly 2013 ), whose impact can hardly be overstated (Lorentzen et al. 2008 ; Voigtländer and Voth 2013 ). Therefore, it is unsurprising that attempts to produce comprehensive quantitative measurements of the economic consequences of pandemics appear to be affected by a significant downward bias (Lee and McKibbin 2004 ; Mahal 2004 ; Keogh-Brown et al. 2010 ). The exceptional nature of the shock brought by the Black Death of 1347–52 has obscured the economic consequences of the other late-medieval plagues, of which we know little. Lack of strong empirical evidence should be understood in the context of the complexity of the phenomena involved, and therefore not be interpreted at first sight as sufficient for falsification purposes. At the same time, however, the mechanisms at work in the most deadly pandemics should not be assumed to apply in exactly the same way to weaker, shorter, or smaller case episodes: the complexity of the phenomena under analysis cannot be reduced to a single formal model. Research on the long-term impacts of pandemics should be understood as a collaborative effort, with single researchers and teams focusing on different, yet compatible, mechanisms. A comprehensive picture can only emerge from subsequent efforts to produce cohesive overviews of the entirety of the debate rather than from a single model, no matter how ambitious.

Some lessons for policymakers also follow. The first is that, in light of the idiosyncratic characteristics of pandemics, precise and detailed analyses of their long-term effects are only possible ex-post. Therefore, preparations for such events should focus on reactive capabilities to ensure that: research efforts can be quickly and adequately supported; their results are credibly communicated to the authorities and the general public; and scientifically-founded counter-measures are rapidly implemented. These characteristics apply to both health measures and economic policy. Furthermore, when these dramatic events occur, the effective public intervention should be timely (Bai et al. 2021 ; Martin et al. 2020 ; Rodríguez-Caballero and Vera-Valdés 2020 ; Stiglitz and Guzman 2021 ) and designed starting from the general characteristics that emerged in this review, and then directed over time by distinctive challenges brought by the specific health shock. The second lesson is that symmetric health shocks will lead to asymmetric economic long-term consequences, as country-specific institutional settings mediate most effects. The tendencies towards the uncritical adoption of global solutions should be tempered by concern for the specific features of local socioeconomic systems, leading to a preliminary process of policy customization. Resistance and push-back from below should not be interpreted automatically as regressive tendencies, but rather as symptoms of the need for policy adaptation to local concerns. Finally, the third lesson is that, while pandemics require careful and extensive public intervention, what matters most in the long term is to avoid crushing the innovative response capabilities of the private sector. A virtuous process of creative destruction may emerge only if public intervention does not attempt to restore the old socioeconomic regime, potentially now unsustainable, at all costs, trampling adaptive bottom-up initiatives in the process. Consequently, while initial efforts should be aimed towards counteracting immediate shocks, they should eventually be complemented by measures aiming to support the positive qualitative developments triggered by the pandemic and curb emerging negative trends. Thus, a potential positive role for policy action can be expected to persist well beyond the outbreak period, focusing on enabling and supporting positive private responses through processes of institutional change.

Conclusions

The COVID-19 pandemic has made evident the need to study the overall economic effects of global health shocks. This literature review collects the main contributions that describe the long-term impact of a pandemic, in order to better understand the lessons from the current economic literature on this topic, and then to better address and analyze the effects on economic development of COVID-19 and of future risks of pandemics. The contributions are organized by discussing, in turn, the mechanisms affecting: labor and human capital; investments and physical capital; and knowledge and innovation. We conclude that pandemics could affect aggregate demand, aggregate supply, and productivity (Jinjarak et al. 2021 ). More precisely, we show that a pandemic reduces labor supply and human capital accumulation in the long term; that the complex interaction of these contrasting and idiosyncratic mechanisms on investments and savings is theoretically indeterminate; and that pandemics, when accompanied by supporting institutional change, can greatly benefit innovation and knowledge development. However, a detailed analysis of the pandemic’s specific characteristics, the affected economic systems, and their response remains necessary to understand which mechanisms can be expected to prevail and which policies should be implemented. The key factors determining their long-term impact are the associated processes of institutional change. We finally identify some general lessons for both researchers and policymakers. The research focuses on the theoretical plausibility and empirical significance of specific mechanisms that should be complemented by meta-analytic efforts aimed at reconstructing the resulting complexity. Policymakers should prioritize developing organizational learning and innovative capabilities, focusing on the ability to quickly adapt to emergencies, rather than developing rigid protocols calibrated over previous pandemics.

We expect the emergence of three new strands of literature in the near future. The first field of research will be on the long-term economic impact of the COVID-19 pandemic (Jordà et al. 2021 ; Poblete-Cazenave 2021 ; Tokic 2020 ). Such research will contribute to testing previously identified mechanisms reviewed here, while potentially also leading to the identification and theorization of new ones (Cacault et al. 2021 ; Silverio-Murillo et al. 2021 ; Costa Junior et al. 2021 ; Favilukis et al. 2021 ; Pagano et al. 2021 ). We also expect significant interest in comparing the impact of COVID-19 with previous pandemics, in order to highlight the relative importance of their respective defining features. The second field of research will be on the public and private responses to the effects of pandemics. The heterogeneity of both the method and timing of the institutional responses for the same health shock can be used to effectively test their efficiency and reduce the impact of future pandemic and epidemic waves (Adolph et al. 2021 ; Caserotti et al. 2021 ; Chakrabarty and Roy 2021 ; Croce et al. 2021 ; Martin et al. 2020 ). The ongoing debate on structural changes as a response to COVID-19 can be seen as a first step in increasing academic attention to the problem of the prediction of possible future pandemics and the precautionary measures to be taken in dealing with these events (Büscher et al. 2021 ; Dosi et al. 2020 ; Leach et al. 2021 ). Finally, we expect a more extensive interaction between, and cross-fertilization of, the medical and economic literatures (Avery et al. 2020 ; Murray 2020 ; Verikios 2020 ). This combination will be needed to better understand how a specific feature of the virus impacts economic development. A taxonomy of pandemics is necessary to group them correctly and then clarify how the different mechanisms move in and impact economic development. In general, we expect the academic debate on the long-term economic impact of pandemics to be renewed and reinforced in the coming years. This survey has the ultimate goal of preparing the basis for this inevitable and intellectually challenging new generation of scientific contributions on the long-term economic effects of pandemics.

Data Availability

Not applicable.

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Callegari, B., Feder, C. A Literature Review of Pandemics and Development: the Long-Term Perspective. EconDisCliCha 6 , 183–212 (2022). https://doi.org/10.1007/s41885-022-00106-w

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Literature review on income inequality and economic growth

This paper provides a comprehensive literature review of the relationship between income inequality and economic growth. In the theoretical literature, we identified various models in which income inequality is linked to economic growth. They include (i) The level of economic development, (ii) The level of technological development, (iii) Social-political unrest, (iv) The savings rate, (v) The imperfection of credit markets, (vi) The political economy, (vii) Institutions and (viii) The fertility rate. Based on the transmission mechanisms of these models, we found that the relationship between income inequality and growth can be negative, positive or inconclusive. The first three models demonstrate that the relationship is inconclusive, the fourth shows that it is positive, while the remainder indicate that the relationship should be negative. In the face of theoretical ambiguity, we also noted that the empirical findings on the relationship between income inequality and growth are highly debatable. These findings can be broadly classified into four categories, namely negative, positive, inconclusive and no relationship. Based on these findings, we provide a critical survey on methodology issues employed in the prior studies and propose a better methodology to researchers for future studies.

• • Theoretical and empirical literature is reviewed and synthesis is done to understand the income inequality-growth nexus

Graphical Abstract

Specification table

Across countries, the unequal distribution of income and resources among the population is the defining challenge of our time. In both developed and developing economies, the income inequality gap (as measured by the decile ratios and the Gini coefficient based on the Lorenz curve) between rich and poor is at high levels, and continues to rise [24] . When income inequality becomes extremely high, it fuels social dissatisfaction and raises the threat of social and political unrest [13] . In similar vein, Alesina and Perotti [8] :1 argue that high income inequality, “ by increasing the probability of coups, revolutions, mass violence or, more generally, by increasing policy uncertainty and threatening property rights, has a negative effect on investment and, as a consequence, reduces growth ”.

Given the already high level of income inequality and rising trends in many countries, along with the potentially negative consequences for economies, we found that a significant body of literature examines the causes of income inequality and its consequences for economic development. Among them were theoretical analyses of the inequality–growth nexus, which identified various transmission mechanisms linking income inequality to economic growth. These include (i) The level of economic development, (ii) The level of technological development, (iii) Social-political unrest, (iv) The savings rate, (v) The imperfection of credit markets, (vi) The political economy, (vii) Institutions and (viii) The fertility rate. Based on these models, we found that the relationship between income inequality and growth can be negative, positive or inconclusive. Theories on the level of economic development (see [7 , 31 , 38 , 54] ) and technological development (see [6 , 29 , 33] ) demonstrate that the relationship between inequality and growth changes from positive to negative as the level of development increases. Inconclusive results are also echoed by the social-political unrest model, which argues that the socio-political unrest stemming from high income inequality can either inhibit or benefit growth (see [13 , 14 , 56 , 62] ). In addition, theories on the political economy (see [9 , 11 , 13 , 46 , 48 , 50] ), the imperfection of credit markets (see [5 , 12 , 30 , 51] ; Panniza, [46] ), institutions (see [22 , 34 , 61] ) and the fertility rate (see [26] ) demonstrate that income inequality is negatively related to growth. The only theory which supports the positive relationship between income inequality and growth is the theory on the savings rate (see [3 , 17 , 42 , 53] ).

Given such theoretical ambiguity, it is little wonder that the empirical findings on the relationship between income inequality and growth are strongly debated. Early empirical studies by Alesina and Rodrik [9] , Persson and Tabellini [50] and Perotti [49] reported that inequality exerted a negative impact on growth. That negative relationship has been confirmed by numerous subsequent studies (see, for example, Panniza, [18 , 19 , 46 , 55 , 64] ). Evidence of a negative relationship has, however, been challenged by studies which reported positive results on the inequality–growth nexus (see, for example, [28 , 39 , 57 , 58] ). In addition, several studies have yielded inconclusive findings, with most reporting that the relationship is positive in high-income and negative in low-income countries (see, for example, [13 , 20 , 25 , 27] ). A few studies found no relationship between inequality and growth (see [15 , 44] ).

Given the above background, the aim here is to provide a comprehensive literature review of the relationship between income inequality and economic growth, both in theory and empirically. While Section 2 critically analyses the theoretical framework of the income inequality–growth nexus, Section 3 reviews empirical studies on this relationship. Section 4 provides a critical survey on methodology issues employed in the prior studies and proposes a better methodology that can help reconcile the literature. Section 5 concludes the study.

Income inequality and economic growth: Theoretical framework

A theoretical analysis of the inequality–growth nexus has identified various transmission mechanisms in which income inequality is linked to economic growth. These mechanisms are discussed in detail in this section.

The level of economic development

Early researchers explored the link between income inequality and growth through the lens of the developmental stage of the economy. Kuznets [38] documented that the relationship between the two variables relies on the level of economic development of a country, meaning there is a differential relationship between income inequality and growth, with a positive relationship during the early stage of economic development and a negative relationship during the mature stage. This may be attributed to shifts of labor, from one sector to other, developed sectors. For example, when labor moves from the agricultural sector to other sectors of the economy, the per capita income of those individuals increases, as their skills are in demand in those sectors. Individuals who remain in the agricultural sector keep earning a low income, thus income inequality increases during this stage. As the economy develops, with labour continuing to move from agriculture to other sectors, individuals who remain in the agricultural sector will earn higher incomes due to the low supply of labour in that sector. Income inequality thus declines during this stage. Kuznets [38] describes the relationship as an inverted U-hypothesis, which advocates that inequality tends to increase during early stages of economic development and decrease during later stages. This argument is supported by Ahluwalia [7] , Robinson [54] and Gupta and Singh [31] .

The level of technological development

In addition to sectoral change, Galor and Tsiddon [29] , Helpman [33] and Aghion et al. [6] explored the link by connecting income inequality to the developmental stage of technology. During the early stages of technological development, innovative ideas in the economic sector result in increases in income inequality. This is due to the fact that new technology requires highly skilled labor and training, which raises wages in these sectors compared to those sectors which use old technology. As a result, employees in the new sector earn high per-capita incomes, while those working in the sector with old machines continue earning lower incomes. Therefore, income inequality increases during the early stages of technological improvements. However, as the economy moves to the more mature stage of technological development, income inequality decreases, the reason being that as more labour shifts to the sector using new technology, the incomes of those who remained in the sector with old technology also increase due to the low supply in labor in that sector. Therefore, the wage differential gap between them declines, leading to a decrease in income inequality.

The role of technology was probed further by researchers who focused on the Fourth Industrial Revolution (4IR). By implementing modern technologies, 4IR will lead to the continuing automation of traditional manufacturing and industrial processes. As Krueger [37] documented, improvements in technology widen the income inequality gap in the labor market between skilled and lowly skilled labour, because the income of highly skilled labor increases (as those individuals are in demand), while lowly skilled laborers continue earning low incomes. In similar vein, 4IR is skills-biased, which leads to a widening of the income inequality gap [1] . Based on this argument, technological improvements can be harmful to growth, due to concerns about growing inequality and unemployment.

Social-political unrest

Some studies argue that the rise of socio-political unrest, stemming from high income inequality, may dampen growth (see [13 , 14 , 62] ). In countries with extreme wealth and income inequality, there are high levels of social unrest that cause people to engage in strikes, criminality and other unproductive activities. This often results in wastage of government resources and disruptions that threaten the political stability of the country. It causes uncertainty in government and slows down productivity in the economy, while discouraging investment.

By contrast, high income inequality due to the rise of socio-political unrest can promote growth. To reduce the number of strikes, criminal activity, uncertainty and political unrest, politicians and leaders favor redistribution – from the rich to the poor – in the form of a transfer of payments. In turn, this creates a safety net for the population and government to restore society's trust in government. As a result, levels of uncertainty decline and investment increases, prompting an increase in the growth rate in the long run [13 , 14 , 62] . Similarly, Saint-Paul and Verdier [56] demonstrate that, in the presence of high income inequality, the median voter favors a transfer of payments by means of public expenditure, such as financing education. This, in turn, increases human capital for the poor to access education, thereby promoting growth.

The political economy

Political economy models demonstrate that high income inequality may hinder growth (see [9 , 13 , 48] ). The law and government play crucial roles in the economy, with government in charge of the redistribution of income and resources among the population. These models reveal that when the mean income is greater than that of the median voter, people support the redistribution of income and resources (from the rich to the poor). Redistribution takes place through a transfer of payments and public expenditure, such as the establishment of health facilities and the building of schools, among others. This kind of redistribution reduces growth in the long run, however, by discouraging innovation and investment, and causing low productivity [9 , 13 , 48] . In addition, when there is high income inequality, the population demands equal distribution. That sometimes results in riots and other unproductive activities which retard economic growth. Furthermore, factors such as lobbying and rent-seeking, which often occur during the political process, also discourage growth. This happens when those in the upper decile of income distribution prevent the redistribution of income and resources to the poor, resulting in a wastage of government funds and corruption, both of which hamper economic growth in the long run [11 , 46 , 48 , 50] .

The imperfection of credit markets

The imperfect credit markets model demonstrates that income inequality is negatively associated with growth through credit markets (see [4 , 12 , 30 , 51] ; Panniza, [46] ). In an imperfect credit market, a high degree of income inequality limits the poor from accessing credit. Asymmetric information – where the lender and borrower have limited information about each other – inhibits the ability to make well-informed decisions. This limits the ability to borrow and returns on investment. In addition, imperfect laws make it difficult for creditors to collect defaulted loans, because the law might protect the assets of the borrower from being repossessed as collateral. Such laws constrain the collection of debt, leading to the hard terms and conditions faced by potential creditors. This prohibits access to credit for some individuals, in particular the poor. Given that investment depends on how much income and how many assets an individual has, the poor (who only have income for basic necessities) are unable to afford investment opportunities with high returns (for instance, to invest in human capital or property, among others). For this reason, extremely high income inequality reduces investment opportunities, leading to declining growth in the long run.

Existing studies report that income inequality exerts a positive impact on economic growth through savings rates (see [3 , 13 , 17] ). According to these studies, savings are a function of income. As income earned increases, so the savings rate rises, and vice versa. In the presence of high income inequality, rich people earn high incomes which help them to save more, because their marginal propensity to save is relatively high. This increases the aggregate savings, leading to a rise in capital accumulation, thereby enhancing economic growth in the long run (see [3] , [17] , [42] , [53] , [66] ). Following on this argument, Shin [59] demonstrates that the redistribution of income and resources from rich to poor is harmful to growth. Such action reduces the income, wealth and other resources of the rich, leading to a decline in the marginal propensity to save. As a result, aggregate savings and investments decline.

Institutions

Several studies illustrate that income inequality inhibits growth through institutions (see [22 , 34 , 61] ). Institutions play a vital role in the wellbeing of a country, because they are the key drivers of economic growth and development in the long run [2 , 60 , 65] . The quality of institutions is important for distribution and growth outcomes. High income inequality creates fertile ground for bad institutions, and exacerbates inequality and inefficiency, which leads to low growth rates in the long run. In the case of high income inequality, political decisions tend to be biased towards enriching the already rich minority, at the expense of the poor. This results in poor policies, leading to a high level of inefficiency, wastage of state resources, social dissatisfaction and political instability. It further perpetuates inequality and inhibits growth in the long run [34 , 61] . Based on this argument, bad institutions tend to associate with extreme records of inequality, inefficiency and sluggish growth. By contrast, good institutions tend to associate with low inequality, productivity and economic growth.

The fertility rate

Income inequality has been found to negatively affect growth through differences in fertility (see [26] ). This study documented that a widening income inequality gap raises differences in fertility between the rich and the poor in a population. The low-income group usually have many children, and tend to invest less in their children's education due to a lack of financial resources. By contrast, those in the high-income group usually have fewer children and invest more in their education. Therefore, in the case of extreme income inequality, the high fertility differential has a negative impact on human capital, leading to a decline in economic growth.

Income inequality and economic growth: Empirical evidence

Given such theoretical ambiguity, the empirical findings on the relationship between income inequality and growth are also highly debatable. These findings can broadly be classified into four categories, namely negative, positive, inconclusive and no relationship.

Studies with negative results on the relationship between income inequality and economic growth

The earliest empirical studies examining the inequality–growth nexus were conducted in the 1990s, and employed the ordinary least squares (OLS) and two-stage least squares (2SLS) estimation techniques (see [9 , 49 , 50] ). Alesina and Rodrik [9] examined the relationship between distributive politics and economic growth in 46 countries, for the period 1960–1985. They found that higher income inequality was accompanied by low growth. Similarly, Persson and Tabellini [50] examined the impact of inequality on growth in 56 countries, for the period 1960–1985, and found that inequality exerted a negative impact on growth. Using similar estimating techniques, Perotti [49] analysed the relationship between income distribution, democratic institutions and growth in 67 countries, and found that countries with a low level of inequality tended to have high investments in human capital, which then led to economic growth.

Studies in the 2000s developed different estimation techniques to solve the problem at hand. For example, Panizza [46] employed the standard fixed effect (FE) and generalised method of moments (GMM) to reassess the relationship between income inequality and economic growth in the United States for the period 1940–1980. The results of that study documented that income inequality negatively affected economic growth. Another single-country study was conducted on China, where Wan et al. [64] investigated the short- and long-run relationship between inequality and economic growth during the period 1987–2001. By using three-stage least squares, they found that the relationship was nonlinear and negative for China. Recently, Iyke and Ho [35] studied income inequality and growth in Italy, from 1967–2012, using the autoregressive distributed lag (ARDL) estimation technique. Their study found that income inequality affected growth both in the short and long run. That is, income inequality slowed down growth in the country.

In multiple-country studies, Knowles [36] re-examined the relationship between inequality and growth in 40 countries using comparable data and OLS from 1960–1990. That investigation found a negative relationship between inequality and economic growth for the full sample. When the countries were divided according to the income level, he found a significant negative relationship in the low-income countries but an insignificant relationship in high- and middle-income countries. Malinen [41] investigated a sample comprising 60 countries (developed and developing economies) using the Gini index as a measure of income inequality. Panel cointegration methods were used, employing panel dynamic OLS and panel dynamic seemingly unrelated regression (SUR) to analyze the steady state correlation between income inequality and economic development. During the period under study, the findings revealed a negative steady-state correlation between income distribution and economic development. In addition, in developed countries, income inequality was associated with low economic growth in the long run. Another study focused on developed countries: Cingano [23] , for instance, examined the impact of income inequality and economic growth in OECD (Organisation for Economic Co-operation and Development) countries between 1980 and 2012. Employed GMM, the researcher found that in those countries income inequality negatively affected economic growth. Furthermore, the study confirmed human capital as the transmission channel through which income inequality affects growth. Research by Braun et al. [18] , tested the main prediction of their model with respect to the impact of income inequality on growth at different levels of financial development. By using pooled OLS, dynamic panel and instrumental variables (IV) estimations on 150 countries during the period between 1978 and 2012, they found that greater income inequality is associated with lower economic growth. In addition, they also found that such an effect is significantly attenuated when the level of financial development increases in economies. Another study by Royuela et al. [55] tested the income inequality-growth nexus for over 200 comparable regions in 15 OECD countries during 2003–2013. By using the similar estimation techniques of Bruan et al. [18] , they showed a general negative association between inequality and growth in OECD regions. Recently, Breunig and Majeed [19] re-investigated the impact of inequality and economic growth in 152 countries. The study used GMM for the period 1956 to 2011 and found that inequality had a negative effect on growth. They further found that when both poverty and inequality were considered, the negative impact of inequality on growth was concentrated on countries with high rates of poverty.

Studies with positive results on the relationship between income inequality and economic growth

A study which found a positive relationship is that of Partridge [47] , who investigated whether inequality benefited or hindered growth in the United States between 1960 and 1990. That study, which employed OLS, yielded the following results: first, during the period of the study, a positive relationship was found between inequality and economic growth. That is, American states with high inequality grew faster. Second, the study reported that the wellbeing of the median voter had a positive impact on growth. This implies that the unequal distribution of income and resources among the population encouraged economic activity and, in turn, grew the economy. In another single-country study, Rangel et al. [52] focused on growth and income inequality by investigating the linear correlation and inverted-U shape hypothesis in Brazil, from 1991–2000. They found that, in the long run, income inequality and growth tended to move together. The results also confirmed the existence of the inverted-U hypothesis between income inequality and economic growth.

Bhorat and Van der Westhuizen [16] investigated the relationship between economic growth, poverty and inequality in South Africa, for the period 1995–2005. The study employed a distribution-neutral measure, poverty inequality elasticity estimates, and the marginal proportional rate of substitution. During the period under study, the researchers found a shift in the distribution of income and resources during periods of growth, and hence income inequality tended to increase with increases in economic growth. Later, Shahbaz [58] and Majeed [40] both employed the ARDL technique to study the income inequality–growth nexus in Pakistan, with the first investigation spanning the years 1971–2005, and the second, 1975–2013. Both studies identified a positive correlation between income inequality and economic growth in Pakistan during the period under investigation. Majeed [40] further argued that because the poor population did not participate in the growth process, growth became unsustainable.

Studies on multiple countries also reported positive results. For example, Li and Zou [39] re-examined the relation between inequality and growth from 1947–1994 for a group of developed and developing countries. Using FE and RE methods and expanded data, they found that high income inequality resulted in an increase in economic growth. Later, Forbes [28] also re-assessed the inequality–growth relationship in 45 countries, from 1966–1995. With the use of FE and RE, Chamberlain's ᴫ matrix procedure and Arrelano and Bond's GMM, the findings showed that as income increased in the short to medium term, economic growth tended to increase. A recent study by Scholl and Klasen [57] revisited the inequality-growth relationship, paying special attention to the role of transition (post-Soviet) countries. The study was based on the specification used by Forbes [28] on a sample of 122 countries over the period of 1961–2012. By using FE, GMM and IV estimation techniques, they found a positive association between inequality and growth in the overall sample which was driven by transition countries.

Studies with inconclusive results on the relationship between income inequality and economic growth

A number of studies yielded inconclusive findings on the inequality–growth nexus. In particular, most reported that the relationship was positive in high-income countries and negative in the low-income countries. For example, Deininger and Squire [25] employed cross-country samples from 1960–1992 to analyse the influence of inequality (income and distribution of assets) on economic growth, and also studied the effect it exerts on reducing poverty. Using OLS and panel data, that study found that income inequality had a negative effect on future growth. In addition, Deininger and Squire [25] reported that high income inequality reduced the income of the poor and boosted the income of the rich. Barro [13] used 2SLS to study the inequality–growth relationship in a panel of countries for the period 1965–1995. The results showed that, in rich countries, inequality positively affected economic growth, while in poor countries it negatively affected growth during the period under study. This means that, for rich countries, as inequality increased, the economy (as measured by Gross Domestic Product [GDP] per capita) tended to increase as well, while in poor countries, the economy tended to decline as inequality increased.

Studies using GMM methods reached similar results. For example, Voitchovsky [63] analysed the link between income distribution and economic growth in 21 developing countries, from 1975–2000. The findings showed that income inequality had a positive effect on growth at the upper decile of income distribution, while inequality negatively affected growth at the lower decile. Similarly, Castelló-Climent [21] confirmed that the relationship between income and growth was positive in high-income countries and negative in low- and middle-income countries. That study examined the correlation between income and human capital and economic growth across countries during the period 1992–2000. The results further indicated that both income and human capital inequality constrained economic growth for low- and middle-income countries. However, in high-income countries, income and human capital inequality encouraged economic growth during the period under study. In yet another investigation, Fawaz et al. [27] studied the income inequality–growth nexus, focusing on its link to credit constraints in high- and low-income developing countries from 1960–2010. The study found similar results, namely that in low-income developing countries, income inequality is negatively related to economic growth. For high-income developing countries, income inequality was positively related to economic growth.

Halter et al. [32] reported that this relationship changed over time, having studied the relationship across countries from 1965–2005, using GMM. The findings showed that, in the short run, high inequality encouraged economic growth, but over the long run, high inequality slowed down the economy and impeded growth. Likewise, Ostry et al. [45] investigated the link between redistribution, inequality and growth in various countries, and found that net inequality was positively correlated to economic performance during the early stage of economic development, but turned negative during the mature stage. Research by Brueckner and Lederman [20] studied the relationship between inequality and GDP per capita growth. Using panel data from 1970 to 2010, the findings documented that in low income countries transitional growth was positively affected by higher income inequality while such effect turned negative in high income countries.

Studies with evidence of no relationship between income inequality and economic growth

Some studies reported no relationship between income inequality and economic growth. For example, research by Niyimbanira [44] focused on how economic growth affected income inequality from 1996–2014. That study employed the FE method and the pooled regression model, using data from 18 municipalities across the provinces of South Africa. The findings confirmed that economic growth reduced poverty, but had no effect on income inequality, which implies that there was no relationship between income inequality and economic growth. Benos and Karagiannis [15] examined the relationship between top income inequality and growth under the influence of physical and human capital accumulation in the U.S. By using 2SLS and GMM on the annual panel of U.S. state-level data during 1929 to 2013, they concluded that changes in inequality do not have an impact on growth. Table 1 shows the summary of empirical studies discussed in this section.

Summary of empirical studies on the association between income inequality and economic growth

Note: - denotes negative; + denotes positive; 0 denotes no relationship

Methodology

As we have discussed in the previous section, the empirical findings on income inequality and growth are highly inconclusive. In this section, by providing a critical survey on methodology issues employed in the prior studies, we offer possible explanations on the disparity found in the empirical findings, particularly on multiple-countries studies. The early multiple-countries studies [9 , 49 , 50] in general reached a consensus on the negative impact of inequality on growth. Although they used different measures of inequality and samples, they all employed the Ordinary Least Squares (OLS) and Two-Stage Least Squares (2SLS) estimation techniques on cross-section data to estimate the coefficient on the inequality variable.

By the late 1990s, however, the general consensus on the negative relationship between income inequality and growth was challenged by concerns over data quality and the methodological procedures used (see Neves and |Silva, [43] ). With regard to the data quality, some studies argued that the dataset used in the previous studies, which lacked comparability due to the use of different income definitions (gross income versus expenditures) can lead to different results (see [10 , 36] ). According to Knowles [36] , European countries, the U.S. and most of the Latin American countries use gross income data whereas most of the African and Asian countries use expenditure data. Since expenditure is more equally distributed than gross income, such difference in income distribution may lead to a difference in the final results.

Concerning the methodological procedures, there has been a shift on the usage of panel data instead of cross-sectional data in the later studies. Forbes [28] argues that the use of panel data is desirable as it can specifically estimate how a change in a country's level of inequality within a given country will affect growth in that country. In addition, panel data can remove bias from the correlation between time-variant, observable country characteristics and the explanatory variables by controlling for differences in these characteristics. Due to these considerations, many studies started to use panel data (see [13 , 28 , 39] ; among others). However, the use of panel data in the studies may lead to more diverse results. One of the possible explanations is the diversity of estimators employed in the panel studies. While most of the cross-section studies use OLS, panel studies use a wide variety of estimators such as fixed effects, random effects, GMM, etc. Given that these estimators have different underlying assumptions, they are likely to produce different results among the panel studies [43] . Another possible explanation is that, unlike the cross-section data, panel data controls for time-variant, observable country characteristics. Given that the impact of inequality on growth tends to differ across countries and regions, the inter-continental variation contribute a substantial part of the effect. Therefore, the usage of panel data analysis may lead to different results when different samples are used in the studies. With the wider usage of various panel data estimation techniques in the later studies, it is not surprising that we found more diverse results in the inequality-growth literature.

Based on the above considerations, researchers should be more cautious when identifying a general global pattern regarding the inequality-growth relationship. Instead, we propose that more emphasis should be placed on identifying the inequality-growth relationship on a national or regional level. Such an approach will provide a better understanding of the inequality-growth process on the study area by overcoming data comparability constraints and possible methodological challenges.

This paper presented a comprehensive literature review of the relationship between income inequality and economic growth. In the theoretical literature, various transmission mechanisms were identified in which income inequality is linked to economic growth, namely the level of economic development, the level of technological development, social-political unrest, the political economy, the imperfection of credit markets, the savings rate, institutions, and the fertility rate. Based on these models, we found that the relationship between income inequality and growth can be negative, positive or inconclusive. For example, based on the level of economic and technological development, the relationship between inequality and growth is positive and becomes negative as the level of development progresses. Inconclusive results were reported by the social-political unrest model, showing that the rise in socio-political unrest stemming from high-income inequality could either dampen or promote growth. In addition, theories on the political economy, the imperfection of credit markets, institutions and the fertility rate, reported that income inequality was negatively related to growth. The only theory which supported the positive relationship between income inequality and growth was the theory of savings rates.

On the empirical front, we found that numerous studies joined the debate by testing the relationship between income inequality and economic growth. Some found a positive relationship, while others identified a negative impact. Some studies yielded inconclusive findings. In particular, most found that the relationship was positive in high-income countries and negative in low-income countries. Several studies documented no relationship between income inequality and economic growth. In the methodology section, we provided a critical survey on methodology issues employed in the prior studies. We argued that the varying results obtained by these studies can be attributed to empirical aspects such as the data comparability and methodological procedures used. We, therefore, suggest that future studies should place more emphasis on identifying the inequality-growth relationship on a national or regional level to better understand the inequality-growth process on the study area. In addition, we conjecture that as the study countries and time span differed in the empirical studies, the impacts of the various theoretical channels we identified previously could also play a uniquely important role in affecting the relationship of the inequality–growth nexus in those studies. It would be prudent for future studies to apply the theoretical models to provide an in-depth analysis of the existing empirical findings. Such findings, with reference to the social, political and economic structure, would provide more relevant policy recommendations to the countries under study.

Declaration of Competing Interest

The authors of this paper certify that there is no financial or personal interest that influenced the presentation of the paper.

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GOOD GOVERNANCE AND ITS IMPACT ON ECONOMIC DEVELOPMENT: A SYSTEMATIC LITERATURE REVIEW

Good governance is a polymorphous concept that stems from economic and political science. It is used both in the context of the management of public action and in a strategic perspective of economic development. In this article, we are first interested in deconstructing the various contributions to define and reaffirm the role of "good governance" in development strategies. What is "good governance"? How does it have an impact on a country's economy? This paper addresses the issue of causality between good governance and economic development, by examining the inter-connections between economic development and governance indicators to increase transparency and efficiency. The purpose of this article is to organize a systematic literature review in a scientific manner from data collection, through data selection, reading and finally data analysis. The impact of good Governance in economic development differs in political system structure, governance current characteristics and contextual factors. Although outcome factors are influenced by contextual determinants, the governance characteristics are of great importance.

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Review article, implementation of water energy food-health nexus in a climate constrained world: a review for south africa.

• 1 Council for Scientific and Industrial Research (CSIR), Climate Services Research Group, Pretoria, South Africa
• 2 Sustainable and Smart Cities and Regions Research Unit, Department of Urban and Regional Planning, Faculty of Engineering and Built Environment, South Africa School for Climate Studies, University of Johannesburg, Johannesburg, South Africa
• 3 Department of Agricultural Economics, University of Stellenbosch, Stellenbosch, South Africa
• 4 Department of Geography and Environmental Sciences, University of Venda, Thohoyandou, South Africa
• 5 Department of Botany and Zoology, School of Climate Studies, University of Stellenbosch, Stellenbosch, South Africa

In recent years, the Water-Energy-Food (WEF) nexus has gained significant attention in global research. Spatial inequality in water-energy-food security (WEF) and its impact on public health and how this is affected by climate change remains a grand adaptation challenge. South Africa is extremely vulnerable and exposed to the impacts of climate change due to its socio-economic and environmental context. While alternative nexus types have garnered interest, this paper pioneers an extension of the conventional WEF framework to encompass health, giving rise to the Water-Energy-Food-Health (WEF-H) nexus. Despite a plethora of WEF nexus studies focused on South Africa, a substantial knowledge gap persists due to the lack of a comprehensive overview of the enablers and barriers to realizing the WEF-H nexus. South Africa boasts diverse policies related to water, energy, food, and health; however, their alignment remains an ongoing challenge. This study seeks to bridge this critical gap by conducting an exhaustive review of existing literature. Its primary aim is to delve into the intricate mechanisms that either facilitate or impede the actualization of the WEF-H nexus in South Africa. By synthesizing insights from a wide array of literature sources, this research strives to illuminate the challenges and opportunities stemming from the integration of health considerations into the established WEF nexus framework. This exploration holds immense significance, not only for unraveling the multifaceted interactions between these pivotal sectors but also for guiding policy development and decision-making processes in South Africa towards a more holistic and sustainable approach to resource management.

1 Introduction

Despite three decades of democracy, South Africa still struggles with the legacy of apartheid, including extreme inequality across racial and regional lines ( Klug, 2021 ), widening gulfs between the rich and poor ( Naidoo, 2005 ; Sibanda and Batisai, 2021 ) compounded with increased frequency of climate-induced hazards. The 1994 transition to majority rule in South Africa aimed to reduce socio-economic inequality, expand basic services, and embrace human rights principles as the foundation of constitutional solutions ( Klug, 2021 ). Access to water, food, health, and energy services are basic human rights, but the struggle for these rights continues to echo the popular struggles of the apartheid era. The South African government is committed to eliminating poverty and reducing inequality by 2030, as set out in its key national policy documents, e.g., National Development Plan 2030 ( NPC, 2011 ) and National Climate Change Response Policy (NCCRP) ( DEA, 2011 ) as well as the international agenda for Sustainable Development Goals (SDGs) to which the government has subscribed. Despite the government’s valiant efforts, many South Africans continue to face socio-economic challenges and the ramifications of climate change ( Naidoo, 2005 ; Sibanda and Batisai, 2021 ). This reality is particularly pronounced among the country’s black African population.

Like many developing countries, South Africa faces the challenge of balancing economic growth with environmental sustainability, what Simpson coined “reconciling growth with planetary boundaries” ( Simpson and Jewitt, 2019 ). This means developing the economy in a way that is equitable, inclusive, and does not irreversibly damage renewable resources or fail to realize the full potential of non-renewable resources. However, South Africa’s political economy has tended to prioritise an economic approach that transfers problems to a wide range of sectors. For example, mining rights often trump conservation of strategic water resource areas, agriculture lands and even human health considerations. As a result, tensions are growing between the increasing demand for, and use of natural resources (e.g., water, land, and energy) to support development and the availability and quality of those resources.

Coupled with its developmental challenges, the country is also water-stressed, with climate change ( Nhamo et al., 2020 ) further compounding existing socio-economic challenges. Escalating food prices ( Simpson and Jewitt, 2019 ) are leaving a large portion of the population highly food insecure, unable to meet their basic nutritional needs. Even more urgent and complex is the issue of the ailing energy system. Eskom, the national power utility has failed to meet the energy demand resulting in frequent power outages ( Baker and Phillips, 2019 ; International Energy Agency, 2022 ) and increased rationing of the available energy ( Lawrence, 2020 ).

South Africa has many policies related to water, food, and energy, which aim to make these sectors more sustainable. However, many stakeholders are increasingly recognizing the importance of managing the complex interactions between water, energy and food (WEF). The WEF nexus, an approach that considers these three sectors together, has been suggested as a governance solution to complex resource management challenges ( Srigiri and Dombrowsky, 2022 ). This paper examines the implementation of the WEF-H nexus in a country case study, with a focus on the key bottlenecks and enablers. The paper acknowledges that more than a decade after the introduction of the WEF Nexus as a governance ( Keskinen et al., 2016 ), analytical ( Nhamo et al., 2020 ) and ideological tool, the transition from “nexus thinking” to “nexus doing” remains essential to foster appropriate policy development, effective decision-making and practical implementation, in the context of water, energy, food, and health interlinkages.

The paper explores developments in the WEF-H nexus through an extensive literature review, unpacking its complexity and challenges within the South African context, and examining the key ingredients for successful implementation.

2 Understanding the nexus concept

The term “nexus” is central to the WEF-H Nexus, and it refers to a polycentric approach to problem solving ( Srigiri and Dombrowsky, 2022 ). As such, the nexus concept is a useful framework ( Keskinen et al., 2016 ) for action that brings together multiple actors and institutions at different levels of governance to address complex challenges. It is both an analytical tool and a discourse centred on the theory of polycentricity ( Thiel, 2016 ) and polycentric governance ( Ostrom, 2010 ) which means that power and decision-making are distributed across multiple centres.

In simpler terms, a nexus approach is a systems-based way of thinking about complex problems by considering how different sectors are connected and how decisions made in one sector can impact on others. This may be especially useful for identifying the inter-relatedness and interdependencies between sectors when making decisions about projects, strategies, policies and investment options in complex socio-environmental systems ( DeLaurentis and Callaway, 2004 ). It aims to integrate research, management and governance across sectors and scales. The nexus approach assumes that there are biophysical and environmental limits to the degree to which resources can be exploited or pollutants can be absorbed, and that exceeding these limits will have potentially catastrophic impacts, either now or in the future.

Moreover, it is understood that there are complex feedbacks within and between sectors ( Mutanga et al., 2016 ), often resulting in non-linear responses, and tipping points beyond which systems cannot easily recover ( Cabrera et al., 2008 ). The nexus approach allows for a more holistic understanding of (un-)intended consequences of policies, technologies and practices whilst highlighting areas of opportunity for further exploration ( Trist, 1981 ; Mutanga et al., 2016 ). It aims to enhance resource-use efficiency (resource-use getting more from less) and political cohesion by reducing resource trade-offs and increasing synergies. The nexus concept needs to be interdisciplinary and transdisciplinary, accepting a plurality of views ( Geels, 2004 ). It is also participatory, requiring stakeholders to engage with researchers in jointly deriving potential solutions. Given the above dimensions, resource-use remains clear that no single definition can be used to define nexus and its applications, it remains an evolving concept. What is clear though is that it forms the basis within which the WEF nexus is defined and understood.

3 The water-energy-food-health (WEF-H) nexus approach

The Water-Energy-Food-Health (WEF-H) Nexus is a complex concept with no single agreed-upon definition or framework. It is often used to describe the interconnectedness of these four sectors, and how challenges in one sector can have cascading impacts on the others ( Rasul and Sharma, 2016 ). The number of sectors included in the Nexus can vary, depending on the discipline or perspective and can sometimes add additional lenses such as livelihoods, ecosystems, and climate change ( Keskinen et al., 2016 ). For example, those in the water sector may refer to the Nexus as WEF, while those in the energy sector may refer to it as EWF. The agriculture sector may define it as FEW, and the health sector may add the ‘H’ ( Nhamo et al., 2020 ). This lack of common understanding can make it difficult to collaborate and develop effective policies and solutions.

Despite the lack of consensus on a definition, the WEF-H Nexus is a useful concept for understanding the complex challenges facing our world. It can be used as an analytical tool, a conceptual framework, or a discourse ( Keskinen et al., 2016 ). Instead of passively acknowledging the existence of the WEF-H nexus, this paper argues that it is a critical driver of resilience in both our economy and society. Recognizing its interconnectedness demands proactive measures – not just awareness, but concrete policies and actions. By effectively managing this complex system, we can harness its synergies and mitigate challenges, ensuring the WEF-H nexus becomes a potent force for resilience in the face of interconnected water, energy, food, and health concerns.

Nexus studies equip us with the knowledge and tools to tackle complex challenges head-on. By delving into resource efficiency, institutional dynamics, and policy integration, they provide a roadmap for action through methods like integrated models and stakeholder engagement. The WEF-H nexus is not just a concept; it's a powerful framework for shaping a sustainable future.

For example, it enables consideration of ways to:

i. Address energy security without impacting further on food or water resources.

ii. Improve water security without increasing the energy burden of water management.

iii. Create a more circular system by integrating food production with water and energy utilization. Wastewater can be treated and reused for irrigation, renewable energy can power agricultural processes, and food waste can be converted into biofuels or compost.

iv. Encourage sustainable food production practices that prioritize nutrient-rich crops and diversified diets which can contribute to improved public health and reduced malnutrition.

v. Create new green jobs in renewable energy, resource recovery, and precision agriculture, thereby meeting job creation ambitions in a sluggish agricultural economy without overextending water and energy resources.

The four most important interfaces in the water-energy-food-health (WEF-H) nexus are:

• Water which plays a vital role in both food and energy production, and for sustaining the ecosystems that support agriculture and other economic activities that are critical for food security.

• Energy, which is required for food production (especially irrigation) and for water supply, including the extraction, purification, and distribution of water.

• The role of food production as a consumer of land, energy, and water as well as their interlinkage with health.

• Health which is an intrinsic component of the WEF-H nexus, as the wellbeing of individuals is intricately linked to the quality and availability of water, the energy required for sustenance, and the nutritional aspects of food production. Recognition of the interconnections between addressing the challenges and opportunities within this interconnected system.

Agriculture, which is responsible for growing food, is a major user of water (more than 70% of all water use globally) and energy ( Rasul and Sharma, 2016 ). Agriculture and food production also affect the water sector through land degradation, changes in runoff, and disruption of groundwater discharge (Shinde, 2017). Recognizing the intricate connections within the Water-Energy-Food-Health (WEF-H) nexus is paramount. Health, as a crucial facet of this nexus, is intricately linked to the availability and quality of water, the energy required for sustenance, and the nutritional aspects of food production. A holistic understanding of these interdependencies is essential for comprehensive and sustainable management within the WEF-H nexus.

4 Taxonomy of nexus approaches

According to Bian & Liu, (2021) , there are four globally recognized nexus types:

• Water-energy: This nexus focuses on the interconnectedness of water and energy systems. For example, energy production often requires large amounts of water for cooling, while water distribution and treatment require energy ( Wilson et al., 2021 ).

• Water-food: This nexus focuses on the connections between water resources and agriculture. Agriculture, particularly irrigation, is a major consumer of water resources. Consequently, fluctuations in water availability directly impact food production.

• Water-energy-food: This nexus adopts a holistic approach, bringing together the three core elements of water, energy, and food. It underscores the need for integrated planning and management, recognizing the interconnectedness and interdependence of these essential domains.

• Water-energy and climate: In this context, the nexus signifies the interplay between water, energy, and climate factors. It acknowledges the substantial influence of climate change on water resources, energy production, and food security. For instance, altered precipitation patterns can disrupt water availability, and extreme weather events have the potential to damage energy infrastructure and disrupt food supply chains. The discussion aims to clarify that the nexus represents the combination of these sectors, emphasizing the importance of a comprehensive understanding and strategic planning within the broader WEF-H context.

In recent years, additional nexus types have emerged:

• The Water-energy-food-ecosystems (WEFE) nexus: This nexus recognizes the pivotal role of ecosystems in shaping and sustaining the interconnections among water, energy, and food systems. Ecosystems provide indispensable services, including clean water, pollination, climate regulation, and biodiversity, which underpin the functionality of water, energy, and food systems ( De Roo et al., 2021 ). The WEFE nexus highlights the profound interdependence between ecosystems and the essential sectors of water, energy, and food. It emphasises the need for holistic, integrated resource management approaches that recognize the intrinsic value of ecosystems in sustaining human wellbeing and promoting environmental resilience.

• Nuwayhid and Mohtar, 2022 contends that Water-Energy-Food-Health (WEF-H) nexus is a comprehensive framework that explores the intricate relationships between water resources, energy production, food systems, and public health. Unlike the WEFE which advances ecosystems as a critical physical component this nexus advances the health wellbeing. Equally it recognizes that changes in one domain can have significant impacts on the others though with an inherent interlinkage between physical components and human wellbeing. For instance, water is crucial for human survival and agricultural production, while energy is essential for water treatment and food processing. Similarly, food quality and availability directly affect public health. This approach underscores the need for integrated, sustainable strategies in resource management and policymaking, emphasizing that decisions in one sector can have far-reaching consequences for the others. By embracing the WEF-H nexus, stakeholders can better address complex challenges related to resource scarcity, environmental sustainability, and community wellbeing through collaborative and innovative solutions refer to ( Figure 1 ).

• Another nexus type, the water-energy-food-biodiversity-health (WEFBH) nexus, encompasses the complex interdependencies between water utilization, energy generation, food supply chains, and environmental and public health ( Hirwa et al., 2021 ).

Figure 1 . WEF-H nexus adaptation framework.

The interrelationships between the nexuses are illustrated in Figure 1 . Essentially the framework for WEF-H Nexus not only captures the traditional WEF but encapsulates the health dimension as an equal sectoral lens to the nexus thus providing a holistic dimension. Policy framing is broadened to include issues around “healthy water,” “sustainable energy for health,” and “nutritious food for wellbeing.” Health metrics can be tracked alongside traditional WEF indicators to monitor the Nexus’s impact on health and identify areas needing improvement. Moreover, the nexus adaptation framework recognizes that the nexus is influenced by several exogenous factors including the impact of climate change, the policy sphere, institutional mechanisms as well as the financial mechanisms all of which have an inherent effect on each of the sectors identified in this nexus.

Building on the foundation of previous nexus typologies that excluded health, the Water-Energy-Food-Health (WEF-H) nexus is a powerful tool at the socio-political level. It can alleviate tensions caused by poor coordination among non-state actors and inadequate service provision by the state. The WEF-H nexus also presents a unique opportunity to shift the focus from governance challenges to community empowerment, fostering self-reliance and sustainability. This empowerment includes showcasing alternative livelihood possibilities.

Furthermore, the WEF-H nexus has the potential to bridge the gap created by inequitable partnerships, whether rooted in gender, wealth disparities, racial divides, educational levels, or social statuses which have become pervasive in South African society. The nexus approach can contribute to what we term “societal hope,” instilling a profound belief within communities that they can chart a course away from hopelessness, even in the face of governance inefficiencies and limited access to opportunities. The principles thereof illustrated in Figure 1 include environmental stewardship which advocates for investment in sustaining ecosystems services, social equity, resource use efficiency as well as the integrative perspective. These principles provide a foundation for merging effective pathways for successful implementation of NEXUS.

The adaptability of the Water-Energy-Food-Health (WEF-H) nexus, in contrast to other aspects of the economy, lies in its capacity to cater to communities with varying levels of knowledge and information. Unlike traditional economic frameworks, the WEF-H nexus is inherently versatile, offering a more inclusive approach that accommodates diverse communities. This adaptability stems from its comprehensive consideration of interconnected elements, allowing for nuanced solutions that address the complex and dynamic challenges present in the realms of water, energy, food, and health. By embracing a holistic perspective and fostering collaboration among stakeholders, including academics, civil society organizations, the private sector, government bodies, and international partners, the WEF-H nexus creates a platform that encourages innovation and technological advancements across multiple sectors and scales.

The WEF-H nexus holds the most promise for regions facing significant development gaps or struggling with complex socio-economic issues. It offers a powerful, unified approach to tackling these challenges and unlocking new opportunities. We characterize the opportunity presented by the WEF-H nexus as “extraordinary” due to its unique capacity to simultaneously address multiple facets of development challenges. The extraordinary nature lies in the nexus’s holistic approach, integrating water, energy, food, and health considerations. This all-encompassing strategy allows for comprehensive and interconnected solutions, offering a more effective and sustainable response to the complex socio-economic challenges and developmental hurdles that regions may face. The extraordinary nature of this opportunity is underscored by the potential for transformative and inclusive development outcomes, some of which are illustrated on Figure 1 as sustainable adaptation outcomes.

5 Key characteristics of the water-energy-food-health (WEF-H) nexus approach

The WEF-H nexus approach is inherently accessible and requires no demystification. It is conceptually straightforward and designed to be inclusive, catering to individuals of all backgrounds and levels of expertise. Recognizing that, for the general public, concepts such as the WEF nexus and the WEF-H nexus may benefit from some explanation, we emphasize the fundamental nature of this approach. It relates to some of the most essential human needs: water, energy, food, and health. In this paper, we have identified ten salient characteristics that are recognized by many scholars and in the literature on the WEF-H nexus, aiming to enhance clarity and promote a more inclusive understanding:

a. Multi-sectoral focus : The WEF-H approach unites a diverse range of stakeholders around a common set of goals, providing a platform for intentional and focused interaction. This cross-sectional coordination promotes convergence of perspectives and facilitates collaborative solutions.

b. Interconnectedness : WEF-H nexus broadens the understanding of interlinkages ( Simpson and Jewitt, 2019 ) recognizing the interdependencies ( Leck et al., 2015 ) between sectors i.e., water, food, and energy.

c. Social embeddedness. Beyond the physical/environmental connections of the nexus approach is the ability to recognize the social interactions among actors which may be referred to as social embeddedness interactions ( Srigiri and Dombrowsky, 2022 ). WEF thus considers the political and cognitive factors that are central to policy change within sectors ( Weitz et al., 2017 ).

d. Complexity : The multifaceted nature and interactions between and within different subsystems ( Mutanga et al., 2016 ) create complex dimensions that must be addressed. As a result, there is no one-size-fits-all model to deal with WEF-related issues ( Simpson and Jewitt, 2019 ). Instead, time-bound and place-bound solutions are encouraged.

e. Governance modes : Scholars studying the WEF nexus agree that integrative coordination across sectors, actors and levels of governance is essential, given the interconnected nature of the nexus ( Welsch et al., 2015 ). It is important to note that the WEF-H nexus approach does not seek to replace focus and attention on actions (planning, investments, implementation, etc.) related to related to water, energy, food and health. Rather, it aims to break down the siloed approach to managing these resources and promote coherent and balanced planning and implementation.

f. Holistic Approach : WEF-H nexus is a holistic approach that is consistent with well-established analytical frameworks such as Institutional analysis and development (IAD) framework ( Ostrom, 2010 ) value chain analysis ( Villamayor-Tomas et al., 2015 ), network of adjacent action situations (NAAS) ( Srigiri and Dombrowsky, 2022 ), multi-criteria decision-making models (MCDM) ( Kumar et al., 2017 ), Integrative Model ( Nhamo et al., 2020 ), as well as systems dynamics models ( Wen et al., 2022 ). All these tools share a common structure for solving complex decision and planning problems, but their application and impact vary across sectors.

g. Implementation : WEF-H nexus implementation is not an event, rather, it is a process that requires access to information about on-going plans and activities to ensure building-on and complementing those activities.

6 Barriers/bottlenecks for implementing nexus

The WEF-H is anchored in prioritizing the management of the four interconnected resources (water, energy, food, and health) in a sustainable way. However, implementing this nexus comes with different barriers and bottlenecks that hinder progress (detailed below and in Table 1 ).

Table 1 . Identified bottlenecks drawn from literature and recommendations for implementing WEF-H Nexus.

South Africa currently lacks a singular policy document that explicitly addresses the Water-Energy-Food-Health (WEF-H) nexus. This does not necessarily imply a lack of commitment but reflects the intricate task of navigating trade-offs and resource constraints. This, position reflects the broader global context where numerous nations are yet to formulate comprehensive policies on the WEF-H nexus. In many instances, the implementation of WEF-H activities remains imbalanced, with sectors such as water, energy, food, and health often managed in a sectoral or “silo” approach ( Nhamo et al., 2018 ). Despite the acknowledgment of the WEF-H nexus approach, these sectors frequently treat resources independently, guided by institutional structures ( Adom et al., 2022 ). The reluctance to enforce integrative policies is a complex challenge influenced by trade-offs embedded across sectors, particularly in resource-limited countries. South Africa, being a water-scarce nation, has ambitious plans to transition from coal-based to renewable energy, including hydropower ( Pegels, 2010 ; Ololade et al., 2017 ). This puts pressure on the water sector which has to prioritise maintaining the supply of its limited water resource to water provision, energy generation and agricultural production (the latter has a very high-water consumption factor of 62% due to irrigation ( Adom et al., 2022 ).

The reluctance to enforce integrative policies, driven by trade-offs across sectors in resource-limited countries like South Africa, poses significant challenges. As a water-scarce nation with ambitious plans for transitioning to renewable energy, the pressure on the water sector is pronounced ( Rasul and Sharma, 2016 ).

Global climate change, and climate variability exacerbates the challenges of WEF-nexus in South Africa. Increasing aridity has a direct knock-on effect on food security ( Schreiner and Baleta, 2015 ; Mabhaudhi et al., 2016 ), leading to hunger and a decline in the supply of nutritious food ( Wlokas, 2008 ). Extreme weather events such as floods and heat waves also cause health issues such as food and waterborne diseases and heat stroke ( Mabhaudhi et al., 2019 ) and exacerbates land degradation, especially of agricultural lands ( Wlokas, 2008 ).

Water and land are key natural resources that are already under pressure from competing interests. Climate change exacerbates these challenges, as it increases the demand for resources. In regions where land and water are limited, an upsurge in multi-service projects aiming to tackle food insecurity and promote clean energy could exacerbate competition for these vital resources.

The lack of dedicated funding to provide integrated solutions is another reason why the sectoral approach persists, as the implementation of the nexus requires significant investment. The current funding landscape in South Africa prioritizes individual WEF sectors, with cross-sectoral funding streams being scarce ( Mabhaudhi et al., 2018 ). This siloed approach creates several challenges among which includes:

• Competing priorities: Crises like the COVID-19 pandemic necessitate diverting limited resources to immediate needs like health and hunger alleviation ( Wlokas, 2008 ; Mabhaudhi et al., 2019 ). This can exacerbate other critical issues like energy insecurity and poverty, further hindering progress on the WEF-H nexus.

• Limited impact: Sector-specific funding often fails to account for the interconnected nature of the WEF-H nexus, hindering the development of holistic solutions that address multiple challenges simultaneously.

The implementation of the WEF-H nexus requires innovative technologies and robust data, yet South Africa faces significant limitations:

• Data scarcity and comparability: Data availability is limited, and existing data often suffers from inconsistencies in spatial scales and temporal trends, hindering effective analysis and planning.

• Technological lag: Access to and expertise in innovative technologies like smart agriculture and early warning systems is limited, impeding the development of solutions to address challenges like climate change and disease outbreaks.

• Amid unpredictable extreme weather events and the prevalence of diseases, there is also a lack of innovative technologies tailored to alleviate the resultant impacts imposed by these events. Even though they come at a hefty cost, technologies such as smart agriculture (to alleviate a 15% decline in agricultural yields by 2050 if global warming increased by 2°C ( Mabhaudhi et al., 2019 )), early warming or detection systems and cutting edge health facilities are a necessity for an integrated response. Another bottleneck in this is that these innovative and sophisticated technologies require, trained personnel to operate them, which is still a scarce skill in the country.

Lack of functional, effective, efficient, and equitable partnerships or collaborations to drive implementation is another barrier. The implementation of the WEF-H nexus requires partnerships as individual experts rarely have expertise across all its dimensions. All this comes with effective communication across all relevant stakeholders including communities, technicians and government officials to promote dialogue among partners towards balancing the decision-making process. At the moment there is ambiguity regarding the roles of communities and relevant stakeholders in the implementation of the nexus framework (D. Naidoo et al., 2021 ). Some of the stakeholders are also in need of capacity development and awareness which hinders collaboration and results in a lack of stakeholder involvement in the nexus framework ( Adom et al., 2022 ). For instance, about 73% of the participants in an interview study agreed that there are major gaps within stakeholder engagement in the nexus ( Adom et al., 2022 ).

The WEF-H nexus faces the challenge of navigating complex political and socio-cultural landscapes, where historical biases towards isolated sectors hinder balanced implementation. Achieving consensus across spheres and sectors requires addressing these challenges and fostering equitable development.

By design, the implementation of the WEF-H programme ideally requires a long period of time. It is possible that while implementing the WEF-H programme, the breadth and coverage of activities of WEF-H approach lend themselves to unintended delays that derail achievement of outcomes and impact. Pressured by the short terms in government, politicians and decision-makers may face pressure to show immediate results to meet political or economic agendas. This can lead to biased prioritization of short-term goals at the expense of the more comprehensive long-term goals of the nexus. Developing and revising policies to effectively enforce the WEF-H nexus demands meticulous consideration of numerous factors, inherently leading to a time-intensive process.

Getting the private sector to actively contribute to the implementation of the WEF-H nexus is another bottleneck. The focus of the private sector is profit. ‘What is in it for us’ has been the dominant and acceptable main focus of the private sector. The private sector is risk averse. Waiting for, encouraging, or coercing the government to absorb the inherent transactional risks has been one of the approaches that the private has used to minimize their exposure and ensure their profitability and sustainability. Despite these basic attributes of the private sector, it is evident that most sections of the private sector are looking for opportunities where they can make a positive societal impact. The WEF-H nexus provides such an opportunity. This leaves us with the question: Why has the private sector not seized the opportunities to implement the WEF-H nexus, especially in communities wherein they operate? Is it likely that there are actions inherent in the implementation of the WEF-H nexus that are laden with risks that the private sector is not willing to absorb?

7 Enablers for implementing the WEF-H nexus

Several ingredients for transitioning from “nexus thinking” to “nexus doing” are required for a successful implementation of the WEF-H nexus. This approach holds immense potential to provide lucrative opportunities for South Africa. This paper adapts the scaling framework and classify the nexus under a three-pronged scaling principles system consisting of (i) scaling up, (ii) scaling deep, and (iii) scaling out as illustrated in Figure 2 . Scaling up focusses on enabling factors that are policy and institutionally oriented, while scaling deep focus on culture and beliefs and scaling out centers on factors impacting greater numbers, the replication and dissemination of information on the WEF-H nexus. This results in an increased number of people or communities impacted. Lastly, scaling deep looks at enabling factors impacting on the cultural roots including aspects such as changing relationships, culture, and beliefs.

Figure 2 . Nexus enabling principles.

For this procedural and transformative transition to happen, several enabling factors have been identified in the literature which foster the adoption and implementation of the WEF-H nexus. The first factor identified is the investment in Capacity Development. To unlock the full potential of the WEF-H nexus, robust capacity development initiatives are required across stakeholders, encompassing government agencies, researchers, and local communities ( Chibarabada et al., 2022 ). These initiatives should encompass comprehensive training programs and knowledge-sharing platforms aimed at enhancing the understanding of nexus interlinkages. By equipping stakeholders with the necessary skills and insights, we empower them to make informed decisions that align with the holistic goals of the WEF-H nexus, thus catalyzing its effectiveness ( Ramos et al., 2022 ). Local communities can also benefit from educational programs on sustainable water and energy practices, alongside leadership development workshops to empower them to participate in decision-making processes.

Secondly, mobilization of finance is also an imperative factor when it comes to the WEF-H nexus implementation. Securing finances is pivotal to translating the WEF-H nexus from theory into impactful practice, regardless of the chosen institutional approach ( Hejnowicz et al., 2022 ). Southern Africa has witnessed a surge in research projects and publications concerning the nexus since 2013 ( Naidoo et al., 2021 ). For instance, the Southern African Development Community-European Union (SADC-EU) nexus dialogue-funded project has been instrumental in driving the WEF nexus from abstract research to tangible action across southern Africa. This initiative has led to the organization of numerous workshops, symposia, and science-policy dialogues within the region. Such financial commitments not only facilitate research and data generation but also provide the necessary resources for practical interventions and policy implementations that promote the sustainable integration of water, energy, food, and health systems.

Decision Support Systems and Frameworks are also a necessary ingredient. The development of robust decision support systems and frameworks is paramount in navigating the complex terrain of the WEF-H nexus ( Nhamo et al., 2020 ). These technological tools serve as indispensable guides for systematic analysis of intricate nexus linkages, enabling policymakers to scrutinize diverse scenarios and their potential ramifications on water, energy, food, and health systems. Decision support systems are the linchpin of informed and effective decision-making within the multifaceted landscape of the WEF-H nexus, fostering data-driven, evidence-based solutions that optimize resource allocation, minimize vulnerabilities, and bolster resilience across these interconnected sectors.

Innovative Policy Frameworks have also been identified as one of the enabling factors ( Naidoo et al., 2021 ). The dynamic nature of the WEF-H nexus necessitates adaptive and forward-thinking policy frameworks capable of accommodating its complexity. These policies should transcend sectoral boundaries, encouraging seamless integration and collaboration while emphasizing sustainability and resilience. The shared resources within the SADC region highlight the importance of harmonizing existing policies and linking them, as illustrated by the Revised Regional Indicative Strategic Development Plan. Such initiatives promote holistic resource management, acknowledge the interdependence of different sectors, and pave the way for comprehensive, cross-cutting policies that effectively address the WEF-H nexus’s challenges.

Regional Cooperation is also an important enabling factor that has been identified within the literature ( Decoppet et al., 2023 ) . Recognizing that environmental and resource challenges often transcend national borders, robust regional cooperation is essential. Collaborative efforts between South Africa and neighboring countries can effectively address shared WEF-H nexus issues, enhancing stability and mutual benefits while ensuring harmonized resource management. Given the overarching nature of environmental and resource challenges, regional cooperation may serve as a fundamental pillar in addressing the complexities of the WEF-H nexus. The SADC regional integration framework (Saurombe, 2010) could transcend beyond trade to include developmental trajectories that have a bearing on WEF-H nexus. South Africa’s geographical proximity to neighboring countries accentuates the necessity for collaborative endeavors. By forging strategic partnerships and alliances with neighboring nations, South Africa and other member states can collectively tackle shared WEF-H nexus challenges that transcend political borders. Such collaborative efforts foster stability, mutual benefit, and regional cohesion. Whether it is addressing transboundary water management, cross-border energy initiatives, harmonizing agricultural practices, or jointly responding to health crises, regional cooperation can yield synergistic solutions that are more effective and sustainable than isolated efforts within national boundaries. Additionally, regional cooperation can lead to enhanced resilience in the face of resource-related uncertainties and bolster collective capacity for responding to emerging WEF-H nexus issues.

Political will is another important enabling factor that fosters the adoption and implementation of the WEF-H nexus. A bedrock of strong political will is fundamental to prioritize the WEF-H nexus and commit to sustainable resource management and public health. Such commitment provides the foundation for integrated policies and action plans that genuinely address the nexus’s intricate challenges. A robust and unwavering political will stands as the cornerstone of meaningful progress within the WEF-H nexus. National leaders hold the key to prioritizing this integrated approach, committing to sustainable resource management, and safeguarding public health. Their dedication paves the way for the development and implementation of comprehensive policies and action plans that genuinely confront the intricate challenges posed by the nexus. It sends a resounding message that these issues are of paramount importance, transcending political cycles and short-term interests, and underscoring a commitment to the long-term wellbeing of both the environment and the populace.

Another necessary ingredient noted in the literature is the clear demarcation of WEF-H operational boundaries: Defining distinct operational boundaries for WEF-H initiatives is crucial as it ensures that roles, responsibilities, and accountabilities are well-understood, preventing overlaps or gaps in resource management, and fostering efficient and effective governance. This not only prevents wasteful overlaps and dangerous gaps in resource management but also fosters efficient and effective governance. By delineating the boundaries of action and influence, stakeholders can coordinate their efforts more effectively, resulting in streamlined operations and more impactful outcomes.

360-Degree stakeholder engagement that leaves no one behind is also another important enabling factor. This underscores the principle of inclusivity’s paramount importance is recognized. Engaging all stakeholders, including marginalized communities, is essential for equitable resource allocation and access ( Bruns et al., 2022 ; Hejnowicz et al., 2022 ). Such comprehensive engagement ensures that diverse perspectives and needs are considered. Engaging all stakeholders, without exception, is not only a moral imperative but also a strategic necessity. This comprehensive involvement ensures that the benefits and burdens of resource management are equitably distributed. Marginalized communities, often disproportionately affected by environmental and health challenges, must have their voices heard and their needs addressed. Inclusivity makes the WEF-H nexus genuinely holistic, drawing on a wealth of perspectives and insights to inform more equitable and effective policies and actions. To operationalize this approach, we propose several pathways for engaging all relevant stakeholders in the WEF-H nexus. Firstly, the establishment of inclusive platforms, such as community forums and online portals, can facilitate ongoing communication and collaboration. Secondly, targeted outreach and awareness campaigns can ensure that marginalized communities are actively involved. Thirdly, leveraging technology, such as mobile applications and social media, can enhance accessibility and engagement. Additionally, incorporating participatory approaches, like co-design sessions and citizen science initiatives, fosters a sense of ownership among stakeholders.

Unlocking the full potential of the WEF-H Nexus, demands breaking down siloed governance. Effective collaboration among government departments, private sector entities, civil society organizations, and academia creates a fertile ground for innovation which enables the sharing of knowledge, identify synergies, and address challenges holistically ( Lazaro et al., 2022 ). Imagine a fertile ecosystem where engineers, farmers, policymakers, and community leaders, all contribute to cross-pollination of ideas. This is the power of a multidisciplinary approach to the WEF-H nexus, where collaboration sparks innovation and ensures no facet is overlooked. From policy blueprints to grassroots implementation, every strand contributes to a more comprehensive and impactful solution, ultimately leading to more sustainable and equitable outcomes for food, water, energy, and health.

Establishment of open access databases and encouraging data sharing can also positively impact on the adoption and the implementation of the WEF-H nexus. Data transparency and sharing are cornerstones of the WEF-H nexus approach. Open access databases facilitate the exchange of information, supporting evidence-based decision-making and research that can drive sustainable resource management and public health improvements ( Mabhaudhi et al., 2021 ). Open access databases facilitate the seamless exchange of information among stakeholders, underpinning evidence-based decision-making, and research. With access to comprehensive and up-to-date data, policymakers and researchers can identify trends, track progress, and make informed choices that drive sustainable resource management and improvements in public health.

Innovative Technology is another enabling factor positively impacting on the adoption and implementation of the WEF-H nexus. Examples of these cutting-edge technologies include, but are not limited to, precision agriculture techniques that optimize water use, the integration of renewable energy sources to power nexus-related activities, and advanced health monitoring systems. Embracing cutting-edge technology within the WEF-H nexus enhances monitoring, data collection, and resource management. This includes the adoption of technologies that promote efficient water use, harness renewable energy sources, advance sustainable agriculture practices, and facilitate health monitoring, thereby driving innovation and progress across the nexus. Embracing cutting-edge technology is a catalyst for progress across the WEF-H nexus. By harnessing innovative solutions, stakeholders can drive meaningful change. Technology enhances monitoring, data collection, and resource management, leading to more efficient and sustainable practices that benefit both the environment and public health. It also fosters a culture of innovation, inspiring continuous progress within the nexus.

8 Conclusion

The exploration of water-energy-food-health (WEF-H) remains key in broadening our understanding of the nexus complexity. This article contributes to the body of knowledge which reveals a paradigm-shifting approach to addressing the intricate interdependencies among these critical sectors. Integration of the health dimension goes beyond conventional WEF frameworks, as it introduces a comprehensive understanding of human wellbeing and resilience. The study contribute to the ongoing discourse surrounding the WEF nexus demonstrating the advantages of linking the health sector. By synthesizing insights from various disciplines, our work advances the understanding of how health interplays with water, energy, and food dynamics. This contribution positions the WEF-H nexus as an innovative solution to complex global challenges. To realize its full potential, there is a need for dedicated champions who can not only navigate the enablers and barriers outlined in this study but also translate concepts into actionable plans and sustainable programs. The success of the WEF-H nexus requires collaborative efforts from governments, stakeholders, and communities, providing a unique and impactful framework for addressing the multifaceted challenges at the intersection of water, energy, food, and health. South Africa, like many nations, aspires to build capable governance, but the complexity of the WEF-H nexus approach may strain government resources. The nexus approach acknowledges the existence of various policies, plans, systems, and programs, but also recognizes that their impact can be amplified when integrated into a cohesive implementation framework from the outset. This should not discourage governments to invest resources in the nexus approach but highlights the inherent challenges in aligning governance structures with its holistic nature.

While the Water-Energy-Food-Health (WEF-H) nexus presents a promising solution to urgent global challenges, its successful implementation necessitates meticulous planning, dedicated champions, and strategic governance. Recognizing the need for a nuanced approach, our paper emphasizes the imperative of capacity development, cross-sectoral collaboration, and the formulation of integrated governance frameworks. These elements are not merely suggested but they could be integral components that address the complexities involved. By strategically integrating these aspects into the implementation process, we ensure that the WEF-H nexus may be closer to reaching its full potential without imposing undue burdens on existing systems. Throughout the paper, we have enhanced the discussion, providing earlier argumentation to articulate the critical role of capacity development and integrated governance, thereby reinforcing the foundation for our proposed strategies.

In conclusion the WEF-H nexus presents an extraordinary opportunity to break the mold of traditional development paradigms. Its unprecedented focus on interconnectedness allows us to address multifaceted challenges from water scarcity, energy and food security to health disparities in a truly comprehensive manner. This holistic approach promises not just incremental progress, but a paradigm shift towards sustainable and equitable development.

Author contributions

SSM: Conceptualization, Writing–original draft, Writing–review and editing, Funding acquisition, Investigation, Project administration. BKM: Writing–review and editing, Funding acquisition, Project administration, Supervision. SM: Writing–review and editing. MSM: Writing–review and editing. FVS: Writing–review and editing. TL: Writing–review and editing. SN: Writing–review and editing. TT: Writing–review and editing. JJ: Writing–review and editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The author(s) acknowledge that the financial support for the research, authorship and publication of this article was received from the Department of Science and Innovation (DSI) through a CSIR Parliamentary Grant (P1EGC02).

Conflict of interest

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Keywords: WEF-H nexus, South Africa, enablers, barriers, policy alignment, sustainability

Citation: Mutanga SS, Mantlana BK, Mudavanhu S, Muthige MS, Skhosana FV, Lumsden T, Naidoo S, Thambiran T and John J (2024) Implementation of water energy food-health nexus in a climate constrained world: a review for South Africa. Front. Environ. Sci. 12:1307972. doi: 10.3389/fenvs.2024.1307972

Received: 06 October 2023; Accepted: 14 March 2024; Published: 25 March 2024.

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Copyright © 2024 Mutanga, Mantlana, Mudavanhu, Muthige, Skhosana, Lumsden, Naidoo, Thambiran and John. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Shingirirai S. Mutanga, [email protected]