eMB: Collaborative Research: Transmission, Control and Risk Assessment of Chikungunya: Combining Machine Learning with Deterministic Models

This is a collaborative project among the University of Miami, Indiana University and Nova Southeastern University. Chikungunya (CHIK) is a viral disease transmitted to humans through the bites of mosquitoes infected with the chikungunya virus (CHIKV). CHIKV is endemic in Central and South American countries, posing significant public health burdens. As the “gateway to Latin America”, Miami-Dade County, Florida, has seen annual importations of CHIKV cases over the last decade. Miami-Dade County has an abundant population of Aedes mosquitoes, a suitable climate that promotes the growth of these mosquito vector species, and the potential for local CHIKV circulation. Integrating Aedes mosquito data collected in Miami-Dade County and local CHIK outbreak data from Brazil into a hybrid machine learning and mathematical modeling framework, the investigative team will reconstruct CHIKV dynamics in Brazil and evaluate control efforts in Florida. The project will further assess the risk for importation and local transmission of CHIKV in Florida considering global environmental changes. This study will provide valuable insights into the transmission dynamics of CHIKV and assist in developing more effective preventive and control measures. Findings can increase preparedness to anticipate and respond to other reemerging arboviruses such as dengue virus and yellow fever virus, as well as similar arboviruses yet to emerge. The project includes various activities for interdisciplinary training of undergraduate students, graduate students, and postdoctoral fellows. Networking activities are planned to encourage collaboration between researchers, especially young researchers from historically underrepresented groups in mathematics. The project aims to develop a novel method that integrates differential equations and machine learning techniques to incorporate complex features into traditional ecological and epidemic models. This method aims to: (i) identify climate and environmental factors affecting Aedes mosquito population growth; (ii) provide accurate projections on vector abundance to design mosquito control measures; (iii) reconstruct local transmission of CHIKV during recent outbreaks in Brazil; (iv) model the importation of CHIKV into Florida and the transmission of CHIKV from imported cases to local mosquitoes; (v) investigate how global environmental change may affect the population dynamics of Aedes mosquitoes and the local spread of CHIKV in South Florida. The obtained results will improve preparedness and response also for other emerging and reemerging arboviruses, such as the dengue virus, Zika virus, and yellow fever virus. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.