Study population and setting
Using data on confirmed cases of COVID-19 from January and February 2020, the authors estimated i) how transmissible (defined by the reproductive number) the virus was over time in Beijing, Shanghai, Shenzhen, Wenzhou, and the 10 provinces with the largest number of confirmed cases; and ii) how severe (the proportion of confirmed cases who died due to COVID-19) the virus was in all 31 provinces in China. The authors used data from publicly available sources and detailed linelists to reconstruct the epidemic for these analyses. A simple SIR model (in which a population is stratified into three categories: Susceptible to the virus, Infected with the virus and infectious, or Recovered) was used to explore the potential effects of relaxing non-pharmaceutical and social interventions under different scenarios on the relative increase in case counts and the time required to push the disease prevalence back to pre-relaxation levels.
Summary of Main Findings
The authors found that COVID-19 transmissibility across mainland China declined since January 23, 2020, suggesting that the mass public health interventions including social distancing, travel restrictions, and other behavioural changes were effective. The reproductive number in the cities and provinces studied has remained below 1 until the end of the study period (February 29, 2020), and the number of new local cases continued to decline. Estimates of the proportion of confirmed cases who died due to COVID-19 varied across the ten provinces that reported the largest number of confirmed cases from 0.00% (uncertainty: 0.00–0.58%) in Jiangsu to 1.76% (uncertainty:1.11–2.65%) in Henan. Overall, the proportion of confirmed cases who died outside Hubei (0.98%, uncertainty:0.82–1.16%) was significantly lower than in Hubei province (5.91%, uncertainty: 5.73–6.09%). Transmission models exploring the consequences of relaxing non-pharmaceutical interventions showed that, in the absence of herd immunity, relaxation of measures must maintain the reproductive number below 1 to prevent a potential second wave of infections.
Authors used data from multiple provinces across mainland China to give an overall view of the epidemic outside of Hubei province. Empirical estimates of epidemiological delays were used to adjust estimates of severity and the reproductive number. Authors checked whether their findings were affected by unknown quantities such as the proportion of imported cases from Hubei to the 10 provinces studied.
As the symptom onset to report delays were not available for all provinces, authors assumed that this delay was the same as that estimated for Beijing. The severity estimates were adjusted based on a relatively small number of onset to death observations from Wuhan City. The lower severity estimates outside of Hubei province may have been affected by a combination of (i) increased testing and detection of milder infections and (ii) changes in the case definition over time.
This is one of the first comparisons of transmissibility over time and severity of COVID-19 in different provinces across China, and the impact of relaxation of interventions on future case numbers.