Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

Publisher: BioMed Central Country of Publication: England NLM ID: 101462774 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-3305 (Electronic) Linking ISSN: 17563305 NLM ISO Abbreviation: Parasit Vectors Subsets: MEDLINE

Original Publication: London : BioMed Central

Agriculture* ; Climate Change* ; Population Growth*; Insect Vectors/*physiology ; Malaria/*epidemiology ; Malaria/*transmission; Animal Distribution ; Animals ; Humans ; South America/epidemiology

Background: Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts.
Methods: Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent.
Results: Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution.
Conclusion: As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

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U19 AI089702 United States AI NIAID NIH HHS; U19AI089702 United States AI NIAID NIH HHS

Date Created: 20150821 Date Completed: 20160418 Latest Revision: 20181113

20240513

PMC4546039

10.1186/s13071-015-1033-9

26289677