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dc.contributor.authorNgonghala, Calistus N.en_US
dc.contributor.authorPluciński, Mateusz M.en_US
dc.contributor.authorMurray, Megan B.en_US
dc.contributor.authorFarmer, Paul E.en_US
dc.contributor.authorBarrett, Christopher B.en_US
dc.contributor.authorKeenan, Donald C.en_US
dc.contributor.authorBonds, Matthew H.en_US
dc.date.accessioned2014-05-06T16:17:01Z
dc.date.issued2014en_US
dc.identifier.citationNgonghala, 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.en
dc.identifier.issn1544-9173en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12152885
dc.description.abstractUnderstanding 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.en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.relation.isversionofdoi:10.1371/journal.pbio.1001827en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972083/pdf/en
dash.licenseLAAen_US
dc.subjectBiology and Life Sciencesen
dc.subjectPopulation Biologyen
dc.subjectTheoretical Biologyen
dc.subjectComputer and Information Sciencesen
dc.subjectSystems Scienceen
dc.subjectNonlinear Dynamicsen
dc.subjectEcology and Environmental Sciencesen
dc.subjectMedicine and Health Sciencesen
dc.subjectEpidemiologyen
dc.subjectInfectious Diseasesen
dc.subjectPhysical Sciencesen
dc.subjectMathematicsen
dc.subjectApplied Mathematicsen
dc.subjectSocial Sciencesen
dc.subjectEconomicsen
dc.titlePoverty, Disease, and the Ecology of Complex Systemsen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalPLoS Biologyen
dash.depositing.authorNgonghala, Calistus N.en_US
dc.date.available2014-05-06T16:17:01Z
dc.identifier.doi10.1371/journal.pbio.1001827*
dash.contributor.affiliatedNgonghala, Calistus N.
dash.contributor.affiliatedBonds, Matthew
dash.contributor.affiliatedMurray, Megan
dash.contributor.affiliatedFarmer, Paul


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