Mercedes and her collaborator Andres Baeza’s essay has just been published in e-Life. The commentary discusses how combining spatial and temporal data is helping researchers to understand how deforestation influences the risk of malaria.

Forests can act as reservoirs for insect species that spread deadly diseases such as malaria. Determining whether deforestation will result in an increase or decrease in expected malaria incidence is not straightforward, and earlier studies have yielded contradictory results. Disturbing forests can increase human exposure to malaria, but deforestation can also lead to economic development and better living conditions, which could reduce the number of cases.

Merecedes’ comementary explores some of the factors that govern the relationship between deforestation and malaria incidence in the context of a new study from François Rerolle (University of California San Francisco; UCSF) and colleagues of forest malaria in the Lao People’s Democratic Republic (Lao PDR) in the Greater Mekong Subregion. This study uses a spatiotemporal statistical model applied to longitudinal records of malaria cases in individual villages, combined with high-resolution images of forest cover obtained through remote sensing. The study found that, after deforestation, the incidence of malaria increases for a period of about two years, and then decreases.

The essay examines the implications of this study, including why previous studies that only used spatial data rather than spatiotemporal data may have been unable to observe this up-down pattern of malaria incidence following deforestation, how other mechanistic models may explain some of the patterns observed in this study, and why protecting forests is essential for safeguarding human health.

The commentary can be found on the eLife website along withe the study by Rerolle et al.