State-by-State prediction of likely COVID-19 scenarios in the United States and assessment of the role of testing and control measures

Zhai, Z.-M.; Long, Y.-S.; Kang, J.; Li, Y.-L.; Zeng, L.; Han, L.-L.; Lin, Z.-H.; Zeng, Y.-Q.; Wu, D.-Y.; Tang, M.; Xu, D.; Liu, Z.; Lai, Y.-C.

Due to the heterogeneity among the States in the US, predicting COVID-19 trends and quantitatively assessing the effects of government testing capability and control measures need to be done via a State-by-State approach. We develop a comprehensive model for COVID-19 incorporating time delays and population movements. With key parameter values determined by empirical data, the model enables the most likely epidemic scenarios to be predicted for each State, which are indicative of whether testing services and control measures are vigorous enough to contain the disease. We find that government control measures play a more important role than testing in suppressing the epidemic. The vast disparities in the epidemic trends among the States imply the need for long-term placement of control measures to fully contain COVID-19.