Work

Clusters of poverty and disease emerge from feedbacks on an epidemiological network

Year: 2012

Type: article

Abstract: The distribution of health conditions is characterized by extreme inequality. These disparities have been alternately attributed to disease ecology and the economics of poverty. Here, we provide a novel framework that integrates epidemiological and economic growth theory on an individual-based hierarchically structured network. Our model indicates that, under certain parameter regimes, feedbacks between disease ecology and economics create clusters of low income and high disease that can stably persist in populations that become otherwise predominantly rich and free of disease. Surprisingly, unlike traditional poverty trap models, these localized disease-driven poverty traps can arise despite homogeneity of parameters and evenly distributed initial economic conditions.

Source: Journal of The Royal Society Interface

DOI: 10.1098/rsif.2012.0656

Authors: Mateusz M. Pluciński, Calistus N. Ngonghala, Wayne M. Getz, Matthew H. Bonds

Institutions: University of California, Berkeley, National Institute for Mathematical and Biological Synthesis, University of Tennessee at Knoxville, University of KwaZulu-Natal, Harvard University

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Applied Mathematics

Field: Mathematics

Domain: Physical Sciences

SDGs: No poverty, Reduced inequalities, Good health and well-being

Open Access status: green

Funders: National Institute of General Medical Sciences, Fogarty International Center