Security or severity? A research of COVID-19 pandemic control policy based on nonlinear programming approach

The COVID-19 pandemic has caused huge impacts to human health and world's econ-omy. Finding out the balance between social productions and pandemic control becomes crucial. In this paper, we first extend the SIR model by introducing two new status. We calibrate the model by 2022 Shanghai COVID-19 outbreak. The results shows compared to zero-constraint policy, under our control policy, 50 % more life can be saved at the cost of 2.13 % loss of consumptions. Our results also emphasize the importance of the dynamic nature and the timing of control policy, either a static pandemic control or a lagged pandemic control damages badly to people's livelihood and social productions. Counter factual experiments show that compared to the baseline, when a persistent high-strength control is applied, aggregate productions decreases by 57 %; when pandemic control ends too early, the death would rise by 15 %, when pandemic control starts too late, the death rises by 23 % and aggregate productions decreases by 13 %.