PhD Candidate in Biostatistics, University of Abomey-Calavi, Labef.

Midokpè Merveille is a biostatistician specializing in infectious disease modeling, with expertise in structural equation modeling (SEM) and time series analysis to study disease dynamics and evaluate public health interventions. She has worked on predictive modeling for infectious disease surveillance, including assessing time series models for Lassa virus transmission in Nigeria, and designing simulation frameworks integrating environmental and socio-demographic factors for epidemic forecasting.

Her research focuses on non-vaccine interventions (NVIs) and malaria dynamics in West Africa, applying advanced statistical methodologies to inform disease control strategies. She has collaborated with institutions such as SoBAPS S.A., SBEE, and FAO, applying statistical modeling to assess intervention effectiveness. She has also co-authored research on Generalized Linear Models (GLMs) in agriculture.

Fluent in French and English, she is committed to leveraging biostatistics for infectious disease forecasting and public health decision-making.