Malaria prevalence and forest cover change in Kenya: a geospatial analysis. (October 2022)

• Record Type: Journal Article
• Authors: Leffler, Thomas G; Hoffmann, Roman; Patz, Jonathan
• Is Part Of: Lancet. Volume 6(2022)Supplement 1
• Page Start: S10
• Publication Date: 2022-10
• Subjects: Global environmental change -- Periodicals; Climatic changes -- Government policy -- Periodicals; Ecology -- Periodicals; Human ecology -- Periodicals; Public health administration -- Periodicals; 304.2
• DOI: 10.1016/S2542-5196(22)00272-8
• Languages: English
• ISSNs: 2542-5196

Abstract

Abstract: Background: The relationship between forest cover loss and infectious disease risk needs further investigation, particularly in sub-Saharan Africa, and with regards to the effect to vulnerable populations—namely, children. The proposed research investigates the links between forest cover change and malaria. We aimed to identify spatiotemporal associations between deforestation and key children's health outcomes in sub-Saharan Africa nations affected by deforestation. Key aims were identifying: the amount of forest cover change most associated with malaria incidence changes; how these factors affect particularly vulnerable populations; what the most notable mechanisms were linking forest cover change to malaria incidence changes; how these findings informed the current theoretical understanding of the relationship between forest cover change and infectious disease risk; and identifying policy solutions that could avert any observed negative outcomes. Methods: We propose regression analyses to investigate forest cover data and malaria incidence and paediatric (aged 2–10 years) prevalence data from selected US Agency for International Development's Demographic and Health Survey (DHS) datasets to assess the association between malaria disease and forest cover change. The research will use DHS-derived cluster sites along the human–wildlife interface in Kenya as geographical variables. The anticipated outcomes would show the relationship between forest cover change and malaria incidence and paediatric prevalence, while allowing for further mechanistic investigation. To measure forest cover change, a Normalized Vegetation Index and Enhanced Vegetation Index will be used. Malaria incidence and paediatric prevalence by cluster site is quantified in the DHS dataset. We plan to run logistical, multiple, and longitudinal regression analyses plotting forest cover change versus malaria incidence and paediatric prevalence at the cluster level at 5-year time points from 2000 to 2020. Findings: This study is in the process of being completed, thus the findings are currently incomplete, bbut preliminary data will be available at the Planetary Health Alliance Annual Meeting in October 2022. We expect to show an association between substantial forest cover loss and higher malaria burden. The expected results would provide a basis and further opportunity for research to explore the causal relationship between these data. Interpretation: The relationship between forest cover loss and human health in areas along the human–wildlife interface is poorly understood. This research proposes an investigation into ecological determinants of of malarial disease. Although the connection between deforestation and infectious diseases is becoming more clear, additional data that expounds upon the ecological burden of disease for malaria in Kenya, and children as a vulnerable population, is needed in the literature. Understanding the relationship between forest cover and malarial disease might allow for the investigation of mechanistic properties that could further the evidence for a casual relationship between specific factors. Funding: National Academy of the Sciences, University of Wisconsin-Madison Global Health Institute Graduate Research Award.