Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks

• DOI: 10.3389/fpubh.2024.1323618
• Publication Date: 2024-01-19T04:45:15Z
• Authors: Mikaela Schlesinger; Franklyn Edwin Pr...; Milena Edith Borb...; Maquins Odhiambo ...; Corinne Simone Merle; Axel Kroeger; Laith Hussain-Alk...
• Keywords: Early warning system

Introduction Dengue is currently the fastest-spreading mosquito-borne viral illness in world, with over half of world's population living areas at risk dengue. As dengue continues to spread and become more a health burden, it essential have tools that can predict when where outbreaks might occur better prepare vector control operations communities' responses. One such predictive tool, Early Warning Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data alert systems weeks before they occur. EWARS-csd robust Distribution Lag Non-linear Model combination INLA Bayesian regression framework outbreaks, utilizing historical data. This study seeks validate tool's performance two states Colombia, evaluating how well tool performed 11 municipalities varying endemicity levels. Methods The validation used retrospective alarm indicators (mean temperature rain sum) an outbreak indicator (weekly hospitalizations) from spanning Colombia 2015 2020. Calibrations different variables were find optimal sensitivity positive value each municipality. Results demonstrated produced overall reliable early alarms. median most calibration municipality was very high: (97%), specificity (94%), (75%), negative (99%; 95% CI). Discussion worked across all sizes levels but had slightly poorer results highly endemic predicting non-outbreak weeks. Migration and/or socioeconomic status are factors impact should be further evaluated. Overall well, providing evidence continue implemented other countries prediction.