The influence of the environment and indoor residual spraying on malaria risk in a cohort of children in Uganda

Abstract

Studies have estimated the impact of the environment on malaria incidence although few have explored the differential impact due to malaria control interventions. Therefore, the objective of the study was to evaluate the effect of indoor residual spraying (IRS) on the relationship between malaria and environment (i.e. rainfall, temperatures, humidity, and vegetation) using data from a dynamic cohort of children from three sub-counties in Uganda. Environmental variables were extracted from remote sensing sources and averaged over different time periods. General linear mixed models were constructed for each sub-counties based on a log-binomial distribution. The influence of IRS was analysed by comparing marginal effects of environment in models adjusted and unadjusted for IRS. Great regional variability in the shape (linear and non-linear), direction, and magnitude of environmental associations with malaria risk were observed between sub-counties. IRS was significantly associated with malaria risk reduction (risk ratios vary from RR = 0.03, CI 95% [0.03–0.08] to RR = 0.35, CI95% [0.28–0.42]). Model adjustment for this intervention changed the magnitude and/or direction of environment-malaria associations, suggesting an interaction effect. This study evaluated the potential influence of IRS in the malaria-environment association and highlighted the necessity to control for interventions when they are performed to properly estimate the environmental influence on malaria. Local models are more informative to guide intervention program compared to national models.

GIS-based spatiotemporal mapping of malaria prevalence and exploration of environmental inequalities

“…Furthermore, the research findings indicated that environmental factors contribute to the increased malaria prevalence in the study area. A previous study by Sadoine et al ( 2022 ) and Arhin et al ( 2023 ) suggested that higher temperatures may lead to elevated malaria levels, potentially due to changes in mosquito populations. This underscores the importance of considering climate change in developing early warning systems and response strategies.…”

Process‐Based Atmosphere‐Hydrology‐Malaria Modeling: Performance for Spatio‐Temporal Malaria Transmission Dynamics in Sub‐Saharan Africa

“…However, the current model tuning does not consider the introduction of various vector control interventions (such as bednet use), leading to an earlier onset of malaria season as shown in Figure 11. The decline in both clinical episodes and deaths due to malaria is primarily associated with the expansion of vector‐control measures, such as insecticide‐treated bednets and indoor residual spraying (Elmardi et al., 2021; Musiime et al., 2019; Sadoine et al., 2024). While tuning model parameters, we observed a significant sensitivity of VECTRI schemes S1 and S2 to the parameter “wperm” (fraction of permanent water bodies, see Equation ), that is, setting “wperm” to 0.001 produces results that match the observed malaria cases from January to May.…”