Events Calendar

Malaria remains a major public health challenge in Benin, particularly among children under five, despite government efforts and the implementation of vector control interventions. This study, based on a modelling approach, assesses the potential impact and effectiveness of introducing the RTS,S/AS01 vaccine in reducing malaria morbidity in the Couffo department. The multi-disease epidemiological model (EMOD) was calibrated using entomological, epidemiological and climatic data collected between 2010 and 2023. The vaccine was incorporated in line with the Expanded Programme on Immunisation (EPI) strategy, enabling the monitoring of cohorts of children under five within 1,000 simulated populations. Nine scenarios combining different levels of coverage and vaccination schedules, as well as a baseline scenario without vaccination, were analysed using various statistical analyses with the R software (version 4.5.1).

This presentation will be in French. Deep within the dense forests of eastern Cameroon, the landscape is changing—and with it, the nature of the malaria epidemic. This study explores the logical signature of environmental disturbances caused by logging and mining. By analyzing 20 years of climate and satellite data (NASA), we seek to understand how abandoned mine pits and gaps in the canopy create highways for the Anopheles mosquito. Using an innovative tool, the Tetradic Conceptual Atlas, we go beyond traditional statistics to visually model the vector’s temporal response to environmental shocks. Our goal is to provide the 14 health districts in the East with a tool for a detailed understanding of their specific vulnerabilities, enabling vector control measures better adapted to local conditions.

This presentation focuses on how Ghana used data as the foundation for Subnational Tailoring(SNT) of malaria interventions during the 2025/2026 planning cycle. It demonstrates how multiple data sources—including DHIMS2 routine surveillance data, household surveys, intervention coverage reports, climate and environmental datasets, entomological evidence, and population statistics—were systematically integrated to stratify malaria risk across 261 districts and guide intervention targeting. The presentation highlights the importance of rigorous data quality management through completeness checks, consistency validation, outlier detection, and imputation methods to ensure reliable analyses. Using adjusted malaria incidence models, geospatial prevalence mapping, seasonality analysis, and care-seeking adjustments, Ghana developed evidence-based prioritization frameworks for interventions such as ITNs, IRS, SMC, malaria vaccines, IPTSc, MDA, and PDMC. Overall, the presentation illustrates that effective SNT depends on high-quality, multi-source data systems and advanced analytical approaches that enable precise, locally tailored, and resource-efficient malaria control decision. Real-time interpretation to FRENCH will be available and Portuguese speakers can activate the CAPTIONS feature on Zoom.