Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing

Abstract

Deforestation and land use change are among the most pressing anthropogenic environmental impacts. In Brazil, a resurgence of malaria in recent decades paralleled rapid deforestation and settlement in the Amazon basin, yet evidence of a deforestation-driven increase in malaria remains equivocal. We hypothesize an underlying cause of this ambiguity is that deforestation and malaria influence each other in bidirectional causal relationships-deforestation increases malaria through ecological mechanisms and malaria reduces deforestation through socioeconomic mechanisms-and that the strength of these relationships depends on the stage of land use transformation. We test these hypotheses with a large geospatial dataset encompassing 795 municipalities across 13 y (2003 to 2015) and show deforestation has a strong positive effect on malaria incidence. Our results suggest a 10% increase in deforestation leads to a 3.3% increase in malaria incidence (∼9,980 additional cases associated with 1,567 additional km² lost in 2008, the study midpoint, Amazon-wide). The effect is larger in the interior and absent in outer Amazonian states where little forest remains. However, this strong effect is only detectable after controlling for a feedback of malaria burden on forest loss, whereby increased malaria burden significantly reduces forest clearing, possibly mediated by human behavior or economic development. We estimate a 1% increase in malaria incidence results in a 1.4% decrease in forest area cleared (∼219 fewer km² cleared associated with 3,024 additional cases in 2008). This bidirectional socioecological feedback between deforestation and malaria, which attenuates as land use intensifies, illustrates the intimate ties between environmental change and human health.

Keywords: Brazil; Plasmodium falciparum; Plasmodium vivax; environmental change; instrumental variables.

Fig. 1.

Malaria and forest cover are highest in the interior of the Brazilian Amazon, while active deforestation and aerosol pollution peak at the interface between the forest interior and outer Amazonian states. (A) The states encompassing the legal Amazon region with “microregion” boundaries, where the interior region is in dark blue and the outer Amazonian region is in light blue. (B) Plasmodium vivax malaria incidence (cases per 1,000 population). (C) P. falciparum malaria incidence (cases per 1,000 population). (D) Deforestation (square kilometers of forest lost). (E) Forest cover (percentage). (F) Mean September aerosol pollution. Data in B–F are mapped by municipality for the year 2008, the midpoint of the study. Municipality boundaries are from 2010.

Fig. 2.

Forest loss increases malaria, while malaria decreases forest loss. Coefficient estimates and partial residual plots illustrating the effect of deforestation (total municipality forest loss) on total malaria incidence (A and B), and of total malaria incidence on deforestation (C and D). Coefficient estimates are plotted for the ordinary least squares (OLS), least-squares dummy variable (LSDV), and instrumental variable (IV) models (A and C). Model diagnostics indicate that the IV model is most appropriate for both analyses. The IV estimator produces consistent estimates but is less efficient than the OLS and LSDV estimators, which leads to larger SEs in IV estimation than in OLS or LSDV (1 SD is plotted in blue around the point estimate in black). Partial residual plots illustrate the estimated effects of deforestation on total malaria (B) and total malaria on deforestation (D) from the IV models, while controlling for other included independent variables.