The research and modeling team focuses on studying the dynamics of vector-borne diseases in the country through a variety of statistical and modeling approaches. We build deterministic, stochastic, and network models to understand how some climatic variables and social factors impact the spread of these diseases. Machine learning tools are currently being explored, seeking to develop early warning tools to identify geographic locations at risk for dengue in Costa Rica.

Currently, the team collaborates with public health entities developing mathematical models used to predict and simulate possible scenarios of COVID-19 spread in the country.