The epidemic curve was constructed by date of illness onset, and key dates relating to epidemic identification and control measures were overlaid to aid interpretation. Case characteristics were described, including demographic characteristics, exposures, and health care worker status. The incubation period distribution (i.e., the time delay from infection to illness onset) was estimated by fitting a log-normal distribution to data on exposure histories and onset dates in a subset of cases with detailed information available. Onset-to-first-medical-visit and onset-to-admission distributions were estimated by fitting a Weibull distribution on the dates of illness onset, first medical visit, and hospital admission in a subset of cases with detailed information available. We fitted a gamma distribution to data from cluster investigations to estimate the serial interval distribution, defined as the delay between illness onset dates in successive cases in chains of transmission.
We estimated the epidemic growth rate by analyzing data on the cases with illness onset between December 10 and January 4, because we expected the proportion of infections identified would increase soon after the formal announcement of the outbreak in Wuhan on December 31. We fitted a transmission model (formulated with the use of renewal equations) with zoonotic infections to onset dates that were not linked to the Huanan Seafood Wholesale Market, and we used this model to derive the epidemic growth rate, the epidemic doubling time, and the basic reproductive number (R0), which is defined as the expected number of additional cases that one case will generate, on average, over the course of its infectious period in an otherwise uninfected population. We used an informative prior distribution for the serial interval based on the serial interval of SARS with a mean of 8.4 and a standard deviation of 3.8.11 (link)Analyses of the incubation period, serial interval, growth rate, and R0 were performed with the use of MATLAB software (MathWorks). Other analyses were performed with the use of SAS software (SAS Institute) and R software (R Foundation for Statistical Computing).
We estimated the epidemic growth rate by analyzing data on the cases with illness onset between December 10 and January 4, because we expected the proportion of infections identified would increase soon after the formal announcement of the outbreak in Wuhan on December 31. We fitted a transmission model (formulated with the use of renewal equations) with zoonotic infections to onset dates that were not linked to the Huanan Seafood Wholesale Market, and we used this model to derive the epidemic growth rate, the epidemic doubling time, and the basic reproductive number (R0), which is defined as the expected number of additional cases that one case will generate, on average, over the course of its infectious period in an otherwise uninfected population. We used an informative prior distribution for the serial interval based on the serial interval of SARS with a mean of 8.4 and a standard deviation of 3.8.11 (link)Analyses of the incubation period, serial interval, growth rate, and R0 were performed with the use of MATLAB software (MathWorks). Other analyses were performed with the use of SAS software (SAS Institute) and R software (R Foundation for Statistical Computing).
