Challenges in control of Covid-19: short doubling time and long delay to effect of interventions

Lorenzo Pellis; Francesca Scarabel; Helena B Stage; Christopher E Overton; Lauren H K Chappell; Katrina A Lythgoe; Elizabeth Fearon; Emma Bennett; Jacob Curran-Sebastian; Rajenki Das; Martyn Fyles; Hugo Lewkowicz; Xiaoxi Pang; Bindu Vekaria; Luke Webb; Thomas A House; Ian Hall

where f is the density of the onset to hospitalisation delay and g is the density of the onset time. Using this truncation corrected method and a gamma distribution to fit the delay distribution, we get a mean delay of 5.14 with standard deviation 4.20. Unfortunately, we cannot share the FF100 data. To compare different regions, we also use data from Hong Kong and Singapore to estimate the local onset to hospitalisation delays. This data is taken from an open access line-list [33 ] , and the filtered data sets used are provided in the supplementary material. Using the method above, for Hong Kong the mean delay is 4.41 days, with standard deviation 4.63, and for Singapore the mean delay is 2.62 with standard deviation 2.38. For the incubation period, we use data from Wuhan during the early stages of the outbreak. This data was extracted from an open access line-list [33 ] , containing dates when individuals were in Wuhan and when they developed symptoms (among other information). Since this data is from the early stages of the epidemic, the majority of cases were in Wuhan. Therefore, it is likely that these individuals were infected in Wuhan, so the time spent in Wuhan provides a potential exposure window during which infection occurred. For individuals with symptom onset date before leaving Wuhan or the same day they left Wuhan, the upper bound on the exposure window was adjusted to half a day before symptom onset. Using the data as of 21/02/2020, we have 162 cases from which to infer the incubation period. This infection date is interval censored, so we obtain the likelihood function