Article

The rise and fall of malaria under land-use change in frontier regions

  • Nature Ecology & Evolution 1, Article number: 0108 (2017)
  • doi:10.1038/s41559-017-0108
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Abstract

Land-use change is the main force behind ecological and social change in many countries around the globe; it is primarily driven by resource needs and external economic incentives. Concomitantly, transformations of the land are the main drivers for the emergence and re-emergence of malaria. An understanding of malaria population dynamics in transforming landscapes is lacking, despite its relevance for developmental and public health policies. We develop a mathematical model that couples malaria epidemiology with the socio-economic and demographic processes that occur in a landscape undergoing land-use change. This allows us to identify different types of malaria dynamics that can arise in early stages of this transformation. In particular, we show that an increase in transmission followed by either a decline, or a further enhancement, of risk is a common outcome. This increase results from the asymmetry between the relatively fast ecological changes in transformed landscapes, and the slower pace of investment in malaria protection. These results underscore the importance of reducing ecological risk, while providing services and economic opportunities to early migrants for longer periods. Consideration of these socio-ecological processes and, more importantly, the temporal scale on which they act, is critical to avoid potential bifurcations that lead to long-lasting endemic malaria.

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References

  1. 1.

    et al. Unhealthy landscapes: policy recommendations on land use change and infectious disease emergence. Environ. Health Perspect. 112, 1092–1098 (2004).

  2. 2.

    , , & Anthropogenic land use change and infectious diseases: a review of the evidence. Ecohealth 11, 619–632 (2014).

  3. 3.

    Malaria and human polymorphisms. Annu. Rev. Genet. 5, 33–64 (1971).

  4. 4.

    & Phylogeny of the malarial genus Plasmodium, derived from rRNA gene sequences. Proc. Natl Acad. Sci. USA 91, 11373–11377 (1994).

  5. 5.

    , & Frontier Forests: Ecosystems and Economies on the Edge (World Resource Institute, 1997).

  6. 6.

    Agricultural intensity and its measurement in frontier regions. Agrofor. Syst. 49, 301–318 (2000).

  7. 7.

    Along Ethiopia’s western frontier: Gambella and Benishangul in transition. J. Mod. Afr. Stud. 37, 321–346 (1999).

  8. 8.

    & Land use transitions: socio-ecological feedback versus socio-economic change. Land Use Policy 27, 108–118 (2010).

  9. 9.

    , , & Effects of microclimatic changes caused by land use and land cover on duration of gonotrophic cycles of Anopheles gambiae (Diptera: Culicidae) in western Kenya highlands. J. Med. Entomol. 42, 974–980 (2005).

  10. 10.

    , , , & Effects of microclimatic changes caused by deforestation on the survivorship and reproductive fitness of Anopheles gambiae in western Kenya highlands. Am. J. Trop. Med. Hyg. 74, 772–778 (2006).

  11. 11.

    , & The ecology of Anopheles mosquitoes under climate change: case studies from the effects of deforestation in East African highlands. Ann. NY Acad. Sci. 1249, 204–210 (2012).

  12. 12.

    et al. Linking deforestation to malaria in the Amazon: characterization of the breeding habitat of the principal malaria vector, Anopheles darlingi. Am. J. Trop. Med. Hyg. 81, 5–12 (2009).

  13. 13.

    et al. The effect of deforestation on the human-biting rate of Anopheles darlingi, the primary vector of falciparum malaria in the Peruvian Amazon. Am. J. Trop. Med. Hyg. 74, 3–11 (2006).

  14. 14.

    , , , & Abundance, biting behaviour and parous rate of anopheline mosquito species in relation to malaria incidence in gold-mining areas of southern Venezuela. Med. Vet. Entomol. 21, 339–349 (2007).

  15. 15.

    , , , & Land use change alters malaria transmission parameters by modifying temperature in a highland area of Uganda. Trop. Med. Int. Health 5, 263–274 (2000).

  16. 16.

    , , & Deforestation and malaria in Mâncio Lima County, Brazil. Emerg. Infect. Dis. 16, 1108–1115 (2010).

  17. 17.

    , , , & Influence of deforestation, logging, and fire on malaria in the Brazilian Amazon. PLoS ONE 9, e85725 (2014).

  18. 18.

    , , & Malaria risk on the Amazon frontier. Proc. Natl Acad. Sci. USA 103, 2452–2457 (2006).

  19. 19.

    et al. Long-lasting transition toward sustainable elimination of desert malaria under irrigation development. Proc. Natl Acad. Sci. USA 110, 15157–15162 (2013).

  20. 20.

    & Agricultural colonization and malaria on the Amazon frontier. Ann. NY Acad. Sci. 954, 184–222 (2001).

  21. 21.

    , & Malaria eradication in the United States. Am. J. Public Health Nations Health 40, 1405–1411 (1950).

  22. 22.

    Determinants of Malaria Transmission in the United States Between 1900 and 1946 PhD thesis, Univ. London (2005).

  23. 23.

    & The decline of malaria in Finland—the impact of the vector and social variables. Malar. J. 8, 94 (2009).

  24. 24.

    , & Reducing malaria by mosquito-proofing houses. Trends Parasitol. 18, 510–514 (2002).

  25. 25.

    , , , & The Kheda malaria project: the case for environmental control. Health Policy Plann. 6, 262–270 (1991).

  26. 26.

    , , & Impact of education on knowledge, agricultural practices, and community actions for mosquito control and mosquito-borne disease prevention in rice ecosystems in Sri Lanka. Am. J. Trop. Med. Hyg. 74, 1034–1042 (2006).

  27. 27.

    Compass and Gyroscope: Integrating Science and Politics for the Environment (Island, 1993).

  28. 28.

    , , & The economic payoffs of integrated malaria control in the Zambian copperbelt between 1930 and 1950. Trop. Med. Int. Health 7, 657–677 (2002).

  29. 29.

    , , & Poverty trap formed by the ecology of infectious diseases. Proc. R. Soc. B 277, 1185–1192 (2010).

  30. 30.

    & Panarchy: Understanding Transformations in Human and Natural Systems (Island, 2002).

  31. 31.

    et al. Climate change and the global malaria recession. Nature 465, 342–345 (2010).

  32. 32.

    A review of the emergence of Plasmodium falciparum-dominated malaria in irrigated areas of the Thar Desert, India. Acta Trop. 89, 227–239 (2004).

  33. 33.

    et al. Linking deforestation to malaria in the Amazon: characterization of the breeding habitat of the principal malaria vector, Anopheles darlingi. Am. J. Trop. Med. Hyg. 81, 5–12 (2009).

  34. 34.

    et al. Agro-ecosystems impact malaria prevalence: large-scale irrigation drives vector population in western Ethiopia. Malar. J. 12, 350 (2013).

  35. 35.

    et al. Quantifying the impact of human mobility on malaria. Science 338, 267–270 (2012).

  36. 36.

    et al. Household risk factors for malaria among children in the Ethiopian highlands. Trans. R. Soc. Trop. Med. Hyg. 94, 17–21 (2000).

  37. 37.

    What’s happening to malaria in the U.S.A.? Am. J. Public Health Nations Health 38, 931–942 (1948).

  38. 38.

    Government spending in a simple model of endogenous growth. J. Polit. Econ. 98, 103–125 (1990).

  39. 39.

    Total factor productivity growth in Indian agriculture. J. Global Econ. 6, 286–298 (2010).

  40. 40.

    & Labour decomposition analysis under different soil and land irrigability environments in the Kakrapar left bank canal irrigation project in Gujarat state. Ann. Arid Zone 37, 187–194 (1998).

  41. 41.

    & The economic burden of malaria. Am. J. Trop. Med. Hyg. 64, 85–96 (2001).

  42. 42.

    Statistical Year Book, India 2016 (Ministry of Statistics and Programme Implementation, 2016).

  43. 43.

    , , & The role of sensitivity analysis in ecological modelling. Ecol. Modell. 203, 167–182 (2007).

  44. 44.

    , & Sensitivity Analysis (Wiley, 2000).

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Acknowledgements

This research was supported by the National Socio-Environmental Synthesis Center (SESYNC) (grant no. DBI-1052875) through the postdoctoral fellowship programme to A.B. and the venture working group Land Use & Infectious Diseases jointly with the National Center for Ecological Synthesis (NCEAS) to A.P.D. We especially thank M. Bonds, C. Ngonghala, G. De Leo, N. Gottdenker and the rest of the working group for their insightful comments during our meetings in Annapolis.

Author information

Author notes

    • Andres Baeza
    •  & Mauricio Santos-Vega

    These authors contributed equally to this work.

Affiliations

  1. National Socio-Environmental Synthesis Center, University of Maryland, Annapolis, Maryland 21401, USA

    • Andres Baeza
  2. School of Sustainability, Arizona State University, Tempe, Arizona 85281, USA

    • Andres Baeza
  3. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA

    • Mauricio Santos-Vega
    •  & Mercedes Pascual
  4. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08544, USA

    • Andrew P. Dobson
  5. Santa Fe Institute, Hyde Park Road, Santa Fe, New Mexico 87501, USA

    • Andrew P. Dobson
    •  & Mercedes Pascual

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Contributions

A.B., M.S.-V., A.P.D. and M.P. formulated the model. A.B. and M.S.-V. conducted the numerical and statistical analyses, and all the authors contributed to the final writing of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andres Baeza.

Supplementary information

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  1. 1.

    Supplementary Information

    The mathematical model used in the analysis; Supplementary Tables 1–10; Supplementary Figures 1,2; Supplementary References.