Estimating the Growth Rate and Doubling Time for Short-Term Prediction and Monitoring Trend During the COVID-19 Pandemic with a SAS Macro

Coronavirus disease (COVID-19) has spread around the world causing tremendous stress to the US health care system. Knowing the trend of the COVID-19 pandemic is critical for the federal and local governments and health care system to prepare plans. Our aim was to develop an approach and create a SAS macro to estimate the growth rate and doubling time in days if growth rate is positive or half time in days if growth rate is negative. We fit a series of growth curves using a rolling approach. This approach was applied to the hospitalization data of Colorado State during March 13 ^th and April 13 ^th . The growth rate was 0.18 (95% CI=(0.11, 0.24)) and the doubling time was 5 days (95% CI= (4, 7)) for the period of March 13 ^th -March 19 ^th ; the growth rate reached to the minimum −0.19 (95% CI= (−0.29, −0.10)) and the half time was 4 days (95% CI= (2, 6)) for the period of April 2 ^nd – April 8 ^th . This approach can be used for regional short-term prediction and monitoring the regional trend of the COVID-19 pandemic.