Dataset Information

Epidemics, pandemics and income inequality.

ABSTRACT: The novel coronavirus is part of a series of infectious disease outbreaks that include: Ebola, Avian influenza, Middle East respiratory syndrome coronavirus, and Influenza A. This paper addresses the question of how do these epidemics and pandemics affect income inequality in countries around the world during the first two decades of this century. To achieve its objective, the paper develops a model that indicates a positive association between these health crises and income inequality. To empirically test our theoretical predictions, the paper explores the effect on the Gini coefficient of a dummy variable that indicates the occurrence of an epidemic or a pandemic in a country in a given year and the number of deaths per 100,000. To properly address potential endogeneity, we implement a Three-Stage-Least Squares technique. The estimation shows that the number of deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when we incorporate COVID-19 data. This suggests that not only the occurrence, but also the health consequences of COVID-19 have a significant and economically important effect on income inequality.

Background

The purpose of the study is to examine the effect of epidemics and pandemics on income inequality. This has important implications as the outcome of this study can guide policymakers into implementing policies that can mitigate the economic consequences of these health crises.

Methods

The study is a cross country analysis using fixed effects estimation. To address potential endogeneity and determine causality, the paper uses the Three-Stage-Least-Squares estimation.

Results

The paper finds that the number of epidemic deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when we incorporate COVID-19 data.

Conclusions

The paper finds that it is not only the occurrence of an epidemic, captured by the epidemics dummy variable, but also the health consequences, captured by the number of deaths per 100,000 population, that have a significant effect on income inequality. This is especially the case when we incorporate COVID-19 in our analysis.

Trial registration

Not Applicable.

SUBMITTER: Esseau-Thomas C

PROVIDER: S-EPMC8765494 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRapid data sharing can maximize the utility of data. In epidemics and pandemics like Zika, Ebola, and COVID-19, the case for such practices seems especially urgent and warranted. Yet rapidly sharing data widely has previously generated significant concerns related to equity. The continued lack of understanding and guidance on equitable data sharing raises the following questions: Should data sharing in epidemics and pandemics primarily advance utility, or should it advance equity as well? If so, what norms comprise equitable data sharing in epidemics and pandemics? Do these norms address the equity-related concerns raised by researchers, data providers, and other stakeholders? What tensions must be balanced between equity and other values?MethodsTo explore these questions, we undertook a systematic scoping review of the literature on data sharing in epidemics and pandemics and thematically analyzed identified literature for its discussion of ethical values, norms, concerns, and tensions, with a particular (but not exclusive) emphasis on equity. We wanted to both understand how equity in data sharing is being conceptualized and draw out other important values and norms for data sharing in epidemics and pandemics.ResultsWe found that values of utility, equity, solidarity, and reciprocity were described, and we report their associated norms, including researcher recognition; rapid, real-time sharing; capacity development; and fair benefits to data generators, data providers, and source countries. The value of utility and its associated norms were discussed substantially more than others. Tensions between utility norms (e.g., rapid, real-time sharing) and equity norms (e.g., researcher recognition, equitable access) were raised.ConclusionsThis study found support for equity being advanced by data sharing in epidemics and pandemics. However, norms for equitable data sharing in epidemics and pandemics require further development, particularly in relation to power sharing and participatory approaches prioritizing inclusion. Addressing structural inequities in the wider global health landscape is also needed to achieve equitable data sharing in epidemics and pandemics.