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. 2010 Apr 22;277(1685):1185-92.
doi: 10.1098/rspb.2009.1778. Epub 2009 Dec 9.

Poverty trap formed by the ecology of infectious diseases

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Poverty trap formed by the ecology of infectious diseases

Matthew H Bonds et al. Proc Biol Sci. .

Abstract

While most of the world has enjoyed exponential economic growth, more than one-sixth of the world is today roughly as poor as their ancestors were many generations ago. Widely accepted general explanations for the persistence of such poverty have been elusive and are needed by the international development community. Building on a well-established model of human infectious diseases, we show how formally integrating simple economic and disease ecology models can naturally give rise to poverty traps, where initial economic and epidemiological conditions determine the long-term trajectory of the health and economic development of a society. This poverty trap may therefore be broken by improving health conditions of the population. More generally, we demonstrate that simple human ecological models can help explain broad patterns of modern economic organization.

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Figures

Figure 1.
Figure 1.
Feedback between economics and the ecology of infectious diseases forms a poverty trap. The prevalence of infectious diseases, I*(M) (black line), falls as per capita income rises, while per capita income, M*(I) (grey line), falls as disease prevalence, I, rises. The disease and income functions are in equilibrium where these two curves intersect at (I*(M*), M*(I*)). Two of these equilibria (I*(M*1), M*(I*1) and I*(M*3), M*(I*3)) are stable, and one (I*(M*2), M*(I*2)) is unstable. The poverty trap is the basin of attraction around (I*(M*3), M*(I*3)). α = 0.06; β̄ = 40; μ̄ = 0.01; ν = 0.02; = 90; δ = 5; ϱ = 0.003; τ = 0.15; ϕ = 15; κ = 30.
Figure 2.
Figure 2.
(a) If labour productivity, δ, is sufficiently high, then all initial conditions lead to high income and low disease burden. (b) If δ is sufficiently low, then all initial conditions lead to low income and high disease burden. α = 0.06; β̄ = 40; μ̄ = 0.01; ν = 0.02; = 90; δ = 5; ϱ = 0.003; τ = 0.15; ϕ = 15; κ = 30. Black line, I*(M); grey line, M*(I); dotted grey line, M*(I).
Figure 3.
Figure 3.
Sensitivity analysis. The threshold level of disease prevalence beyond which an economy could grow out of poverty, I*2, is presented over a range of values for the transmission parameter, β̄, and the income parameter, δ. Notice that for every value of β̄ presented, there is a range of values of δ for which the entire economy is in a poverty trap (I*2 = 0; as in figure 2b), for which the poverty trap does not exist (I*2 = 1; as in figure 2a) and for which the initial conditions determine the long-term outcome of the economy (0 < I*2 < 1; as in figure 1). The points A, B, and C represent the system at three different values for δ, which are illustrated in figures 2b, 1 and 2a, respectively. α = 0.06; μ̄ = 0.01; ν = 0.02; = 90; ϱ = 0.003; τ = 0.15; ϕ = 15; κ = 30.
Figure 4.
Figure 4.
Disease burden and income. (a) The correlation between per capita GDP (USD, 2000) in 2002 and the infectious disease burden (DALYs) in 2002 over 170 countries in the world is negative and highly nonlinear. (b) The natural log of the per capita DALYs and GDP are presented for least developed countries (LDCs, open circles) and developed countries (DCs, open diamonds) with the filled circles representing the average values for the LDCs and DCs. The slopes of the estimated effect of income on disease burden, IDC(M) and ILDC(M), and of disease burden on income, MDC(I) and MLDC(I), are represented by the solid lines. If the estimates of the stable equilibria are part of a continuous system, then there is an unstable equilibrium in-between, represented by the dotted lines. Data sources: Lopez et al. (2006); World Bank Development Data Group (2007).

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