Increased Detection coupled with Social Distancing and Health Capacity Planning Reduce the Burden of COVID-19 Cases and Fatalities: A Proof of Concept Study using a Stochastic Computational Simulation Model

Pramit Ghosh; Salah Basheer; Sandip Paul; Partha Chakrabarti; Jit Sarkar

According to the Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID- 19) , COVID-19 manifests in several forms with 80% of the cases presenting with mild to moderate disease. 13 .8% progress to severe disease and 6.1% become critically ill with respiratory failure, septic shock or multi-organ failure [1] . However, detection and response capacity of COVID-19 cases globally vary across all countries [4] . In a country like India with a varied administrative set-up and state policies, healthcare amenities vary even further [5] . Amidst measures like "Lock-down", Social distancing and Sanitization being used to reduce the peak number of COVID-19 cases [6] in India, we extended the SIR model to a SEIQHRF (Susceptible-Exposed-Infectious-Quarantined-Hospitalised-Recovered-Fatal) model [7] to take in account the healthcare capacity of that state. As a proof of concept study, we ran the SEIQHRF model on Kasargod [8] , the most affected district in Kerala, the state with best healthcare capacity in India [9] .