Case growth analysis to inform local response to COVID-19 epidemic in a diverse U.S community - Marcia C. de Oliveira Otto; Frances A. Brito; Ji Yun Tark; Eric Bakota; Jose-Miguel Yamal; Dritana Marko; Shreela V. Sharma; Michael R. Brown; Savitri N. Appana; Alison M. Rector; Stephen H. Linder; Jennifer Kiger; et al. (Scientific Reports, 2022)
Abstract Early detection of new outbreak waves is critical for effective and sustained response to the COVID-19 pandemic. We conducted a growth rate analysis using local community and inpatient records from seven hospital systems to characterize distinct phases in SARS-CoV-2 outbreak waves in the Greater Houston area. We determined the transition times from rapid spread of infection in the community to surge in the number of inpatients in local hospitals. We identified 193,237 residents who tested positive for SARS-CoV-2 via molecular testing from April 8, 2020 to June 30, 2021, and 30,031 residents admitted within local healthcare institutions with a positive SARS-CoV-2 test, including emergency cases. We detected two distinct COVID-19 waves: May 12, 2020–September 6, 2020 and September 27, 2020–May 15, 2021; each encompassed four growth phases: lagging, exponential/rapid growth, deceleration, and stationary/linear. Our findings showed that, during early stages of the pandemic, the surge in the number of daily cases in the community preceded that of inpatients admitted to local hospitals by 12–36 days. Rapid decline in hospitalized cases was an early indicator of transition to deceleration in the community. Our real-time analysis informed local pandemic response in one of the largest U.S. metropolitan areas, providing an operationalized framework to support robust real-world surveillance for outbreak preparedness.