Abstract
AbstractInfectious diseases have been a major determinant of human mortality in history and the key regulator of population size, including the first epoch of the Industrial Revolution (until the 1950s) in Western countries and still now in developing countries, especially in Sub‐Saharan Africa. In recent times, a new vein of economic research dealing with the interplay between communicable diseases and economic development has grown. However, pioneering previous research has analysed this issue in a framework where prevention decisions were the outcome of private individual rational choices. This assumption neither seems to hold for least‐developed countries, primarily due to a lack of resources, nor for developed countries, where prevention policies are mostly planned by the public authority through its (public) health system, as also well documented by the current COVID‐19 crisis. Our aim in this article is twofold. First, we pinpoint the properties of Chakraborty et al.'s (2010, 2016) basic epidemiological equation to fully enlighten its usability in economic‐epidemiology modelling. Second, we apply this framework to analyse prevention activities against a range of infectious diseases by endogenous public (rather than private) health expenditures. Our results identify the relationships governing the interplay between—on the one hand—typical epidemiological phenomena, namely invasion (i.e., the tendency of infection to establish in a population) versus endemicity (i.e., the tendency of infection to persist in the long term) and—on the other hand—economic variables, such as capital accumulation, GDP, and taxation. This is done by identifying threshold quantities, depending on both epidemiological and economic parameters, and by bifurcation analysis showing the effects that public intervention can have on previously uncontrolled infectious diseases. Both direct and indirect, that is, partial and general equilibrium, effects of control interventions are identified.
Highlights
Infectious diseases have been a major determinant of human mortality in history and the key regulator of population size
The ongoing COVID‐19 pandemic is dramatically changing the perspectives on the economic effects of infectious diseases in the industrialised world and is opening up a growing literature, which was previously confined in a niche largely focused on specific topics, such as the effects of deadly infections as HIV/AIDS and malaria in Sub‐Saharan Africa (SSA), and their effects on economic development, or the effects of vaccine refusal in relation to vaccine preventable infections
Though their representation is a stylised one, using a simplistic time frame of infection dynamics, which is taken identical to the overlapping generations (OLG) time, it represents a very useful tool for qualitative interpretations of the interplay between economic development and infectious diseases
Summary
Infectious diseases have been a major determinant of human mortality in history and the key regulator of population size. In relation to the key topic of the impact of communicable infections on development, a seminal effort has been done by Chakraborty et al (2010, 2016), who were first in setting an explicit, parsimonious representation of the dynamics of infection prevalence (i.e., the proportion of infective individuals at any time in the population) within a finite lived overlapping generations (OLG) growth model. They built on a standard Diamond‐like OLG set‐up, where rational (two‐period lived) individuals choose their private health prevention investments. Though their representation is a stylised one, using a simplistic time frame of infection dynamics, which is taken identical to the OLG time (and appropriate only for infections spreading over long scales of time, as is the case of the HIV/AIDS epidemic or has been the case of TB spread in history), it represents a very useful tool for qualitative interpretations of the interplay between economic development and infectious diseases
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