Forest loss and other environmental changes correlate with increased malaria incidence.

Background Land use changes disrupt ecosystems, altering the transmission of vector-borne diseases. These changes have been associated with increasing incidence of zoonotic malaria caused by Plasmodium knowlesi; however, the population-level distributions of infection and exposure remain unknown. We aimed to measure prevalence of serological exposure to P knowlesi and assess associated risk factors. Methods We did an environmentally stratified, population-based, cross-sectional survey across households in the Kudat, Kota Marudu, Pitas, and Ranau districts in northern Sabah, Malaysia, encompassing a range of ecologies. Using blood samples, the transmission intensity of P knowlesi and other malaria species was measured by specific antibody prevalence and infection detected using molecular methods. Proportions and configurations of land types were extracted from maps derived from satellite images; a data-mining approach was used to select variables. A Bayesian hierarchical model for P knowlesi seropositivity was developed, incorporating questionnaire data about individual and household-level risk factors with selected landscape factors.

BackgroundPrimarily impacting poor, rural populations, the zoonotic malaria Plasmodium knowlesi is now the main cause of human malaria within Malaysian Borneo. While data is increasingly available on symptomatic cases, little is known about community-level patterns of exposure and infection. Understanding the true burden of disease and associated risk factors within endemic communities is critical for informing evidence-based control measures.Methodology/Principal findingsWe conducted comprehensive surveys in three areas where P. knowlesi transmission is reported: Limbuak, Pulau Banggi and Matunggung, Kudat, Sabah, Malaysia and Bacungan, Palawan, the Philippines. Infection prevalence was low with parasites detected by PCR in only 0.2% (4/2503) of the population. P. knowlesi PkSERA3 ag1 antibody responses were detected in 7.1% (95% CI: 6.2–8.2%) of the population, compared with 16.1% (14.6–17.7%) and 12.6% (11.2–14.1%) for P. falciparum and P. vivax. Sero-prevalence was low in individuals <10 years old for P. falciparum and P. vivax consistent with decreased transmission of non-zoonotic malaria species. Results indicated marked heterogeneity in transmission intensity between sites and P. knowlesi exposure was associated with agricultural work (OR 1.63; 95% CI 1.07–2.48) and higher levels of forest cover (OR 2.40; 95% CI 1.29–4.46) and clearing (OR 2.14; 95% CI 1.35–3.40) around houses. Spatial patterns of P. knowlesi exposure differed from exposure to non-zoonotic malaria and P. knowlesi exposed individuals were younger on average than individuals exposed to non-zoonotic malaria.Conclusions/SignificanceThis is the first study to describe serological exposure to P. knowlesi and associated risk factors within endemic communities. Results indicate community–level patterns of infection and exposure differ markedly from demographics of reported cases, with higher levels of exposure among women and children. Further work is needed to understand these variations in risk across a wider population and spatial scale.

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement and space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

Land-use changes can impact infectious disease transmission by increasing spatial overlap between people and wildlife disease reservoirs. In Malaysian Borneo, increases in human infections by the zoonotic malaria Plasmodium knowlesi are hypothesised to be due to increasing contact between people and macaques due to deforestation. To explore how macaque responses to environmental change impact disease risks, we analysed movement of a GPS-collared long-tailed macaque in a knowlesi-endemic area in Sabah, Malaysia, during a deforestation event. Land-cover maps were derived from satellite-based and aerial remote sensing data and models of macaque occurrence were developed to evaluate how macaque habitat use was influenced by land-use change. During deforestation, changes were observed in macaque troop home range size, movement speeds and use of different habitat types. Results of models were consistent with the hypothesis that macaque ranging behaviour is disturbed by deforestation events but begins to equilibrate after seeking and occupying a new habitat, potentially impacting human disease risks. Further research is required to explore how these changes in macaque movement affect knowlesi epidemiology on a wider spatial scale. Electronic supplementary materialThe online version of this article (10.1007/s10393-019-01403-9) contains supplementary material, which is available to authorized users.