Publication: Poverty, Disease, and the Ecology of Complex Systems
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Date
2014
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Public Library of Science
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Citation
Ngonghala, Calistus N., Mateusz M. Pluciński, Megan B. Murray, Paul E. Farmer, Christopher B. Barrett, Donald C. Keenan, and Matthew H. Bonds. 2014. “Poverty, Disease, and the Ecology of Complex Systems.” PLoS Biology 12 (4): e1001827. doi:10.1371/journal.pbio.1001827. http://dx.doi.org/10.1371/journal.pbio.1001827.
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Abstract
Understanding why some human populations remain persistently poor remains a significant challenge for both the social and natural sciences. The extremely poor are generally reliant on their immediate natural resource base for subsistence and suffer high rates of mortality due to parasitic and infectious diseases. Economists have developed a range of models to explain persistent poverty, often characterized as poverty traps, but these rarely account for complex biophysical processes. In this Essay, we argue that by coupling insights from ecology and economics, we can begin to model and understand the complex dynamics that underlie the generation and maintenance of poverty traps, which can then be used to inform analyses and possible intervention policies. To illustrate the utility of this approach, we present a simple coupled model of infectious diseases and economic growth, where poverty traps emerge from nonlinear relationships determined by the number of pathogens in the system. These nonlinearities are comparable to those often incorporated into poverty trap models in the economics literature, but, importantly, here the mechanism is anchored in core ecological principles. Coupled models of this sort could be usefully developed in many economically important biophysical systems—such as agriculture, fisheries, nutrition, and land use change—to serve as foundations for deeper explorations of how fundamental ecological processes influence structural poverty and economic development.
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Keywords
Biology and Life Sciences, Population Biology, Theoretical Biology, Computer and Information Sciences, Systems Science, Nonlinear Dynamics, Ecology and Environmental Sciences, Medicine and Health Sciences, Epidemiology, Infectious Diseases, Physical Sciences, Mathematics, Applied Mathematics, Social Sciences, Economics
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