Optimal lockdown strategies for SARS-CoV2 mitigation--- an Indian perspective

We sought to identify optimal temporal windows for lockdown-based mitigation strategies on infectious disease spreads. An age-structured multi-compartmental Susceptible- Infected-Recovered (SIR) model was used to estimate infection spreads under parametric variation of lockdown intensity and duration from the data of SARS-CoV2 cases in India between January to July, 2020. The resulting parameter values were used to simulate lockdown outcomes for a wide range of start times and durations. Lockdowns were simulated as intervention strategies that modified weights assigned to social contact matrices for work, school and other places. Lockdown efficacy was assessed by the maximum number of infections recorded during a simulation run. Our analysis shows that lockdown outcomes depend sensitively on the timing of imposition and that it is possible to minimize lockdown durations while limiting case loads to numbers below the hospitalization thresholds. Such timing based effects arise naturally from the non-linear nature of SIR dynamics. NotationN Total Population S Number of susceptible individuals I Number of infected individuals R Number of recovered/removed individuals {beta} Per-individual disease transmission rate {gamma}Recovery rate {tau}Lockdown start-time {Delta}Duration of lockdown p Post-lockdown coefficient h Total number of hospital beds {xi}Maximum fraction of infected individuals {xi}0 Hospitalization threshold