2020/08/09 by Fulgence Mansal, Mansal, Fulgence, Mouhamadou A. M. T. Baldé +4
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · #2019-20 coronavirus outbreak #92D30 #Artificial intelligence #COVID-19 epidemiological studies #Computer science #Control (management) #Coronavirus disease 2019 (COVID-19) #Disease #Distancing #Environmental health #Epidemic model #Epidemiology #FOS: Biological sciences #Infectious disease (medical specialty) #Intervention (counseling) #Mathematical and Theoretical Epidemiology and Ecology Models #Mathematical modelling of infectious disease #Mathematical optimization #Mathematics #Medicine #Optimal control #Outbreak #Pandemic #Populations and Evolution (q-bio.PE) #Risk analysis (engineering) #SARS-CoV-2 and COVID-19 Research #Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) #Social distance #Virology #msc:92D30 #q-bio.PE
paper · pdf · doi:10.48550/arxiv.2008.05897
published in arXiv (Cornell University) (Cornell University) · 21 pages, 32 figures
arxiv created 2020/08/09 · openalex publication_date 2020/08/09 · arxiv updated 2020/08/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In this study, we present a new epidemiological model, with contamination from confirmed and unreported. We also compute equilibria and study their stability without intervention strategies. Optimal control theory has proven to be a successful tool in understanding ways to curtail the spread of infectious diseases by devising the optimal disease intervention strategies. We investigate the impact of distancing, case finding, and case holding controls while at the same time, we minimize the number of infected and dead individuals. The method consists of minimizing the cost functional related to infectious, death, and controls through some strategies to reduce the spread of the COVID19 epidemic.