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General ecological models for human subsistence, health and poverty

Nature Ecology & Evolutionvolume 1pages11531159 (2017) | Download Citation

Abstract

The world’s rural poor rely heavily on their immediate natural environment for subsistence and suffer high rates of morbidity and mortality from infectious diseases. We present a general framework for modelling subsistence and health of the rural poor by coupling simple dynamic models of population ecology with those for economic growth. The models show that feedbacks between the biological and economic systems can lead to a state of persistent poverty. Analyses of a wide range of specific systems under alternative assumptions show the existence of three possible regimes corresponding to a globally stable development equilibrium, a globally stable poverty equilibrium and bistability. Bistability consistently emerges as a property of generalized disease–economic systems for about a fifth of the feasible parameter space. The overall proportion of parameters leading to poverty is larger than that resulting in healthy/wealthy development. All the systems are found to be most sensitive to human disease parameters. The framework highlights feedbacks, processes and parameters that are important to measure in studies of rural poverty to identify effective pathways towards sustainable development.

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Acknowledgements

This work benefited from the working group ‘Land use change and infectious diseases’ conducted both at the National Socio-Environmental Synthesis Center (funded from NSF DBI-1052875) and the National Center for Ecological Analysis and Synthesis (funded by the University of California, Santa Barbara and the state of California). We are grateful to both centres for providing excellent interactive venues to discuss some of the analysis and results of the models, and to other members of the working group for their valuable feedback. A.P.D. and M.M.P. acknowledge SFI. M.H.B. and C.N.N. are supported by NIH grant 5K01TW008773-06 from Fogarty International Center and a Scholar Award in Complex Systems Science from the James S. McDonnell Foundation to M.H.B. G.A.D.L. was supported by the National Science Foundation (CNH grant no. 1414102), NIH grants (R01GM109499, R01TW010286), the Bill and Melinda Gates Foundation, Stanford GDP SEED (grant no. 1183573-100-GDPAO) and the SNAP-NCEAS-supported working group ‘Ecological levers for health: advancing a priority agenda for disease ecology and planetary health in the 21st century’. We thank S. and V. Della Pietras for helpful comments on the manuscript.

Author information

Affiliations

  1. Department of Mathematics, University of Florida, Gainesville, FL, 32611, USA

    • Calistus N. Ngonghala
  2. Department of Biology, Hopkins Marine Station, Woods Institute for the Environment, Center for Innovation in Global Health, Stanford University, Pacific Grove, CA, 93950, USA

    • Giulio A. De Leo
  3. Department of Ecology and Evolution, University of Chicago, Chicago, IL, 60637, USA

    • Mercedes M. Pascual
  4. Santa Fe Institute, Hyde Park Road, Santa Fe, NM, 87501, USA

    • Mercedes M. Pascual
    •  & Andrew P. Dobson
  5. Université de Cergy-Pontoise et THEMA, Cergy-Pontoise Cedex, 95011, France

    • Donald C. Keenan
  6. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, 08544, USA

    • Andrew P. Dobson
  7. Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, 02115, USA

    • Matthew H. Bonds
  8. PIVOT, Boston, MA, 02199, USA

    • Matthew H. Bonds
  9. Stanford School of Medicine, Palo Alto, CA 94305, USA

    • Matthew H. Bonds

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Contributions

C.N.N. and M.H.B. conceived the paper, C.N.N. conducted analysis. All authors performed research and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Calistus N. Ngonghala.

Electronic supplementary material

  1. Supplementary Information

    Details of the models used in the analysis

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DOI

https://doi.org/10.1038/s41559-017-0221-8

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