Skip to main content

Reconstruction of the full transmission dynamics of COVID-19 in Wuhan

Our take —

Authors used a specialized Susceptible-Exposed-Infected-Removed (SEIR) model to estimate the true extent of the COVID-19 epidemic in Wuhan, China over the course of five time periods between January 1, 2020 through March 8, 2020. Results estimated the effective reproductive number decreased from 3.84 during the first period to 0.28 during the final period. Authors also determined an overall ascertainment rate of 0.13, indicating a high proportion of asymptomatic or mild-symptomatic cases. This study used laboratory-confirmed cases from Wuhan and results were robust to extensive sensitivity analyses.

Study design

Modeling/Simulation

Study population and setting

Authors developed a Susceptible (S), Exposed (E), Presymptomatic infectious (P), unAscertained infectious (A), Isolated (H), and Removed (R) (SAPHIRE) model, an extension of the traditional Susceptible-Exposed-Infected-Recovered model, to estimate the true extent of the COVID-19 epidemic in Wuhan, China. Using 32,583 laboratory-confirmed cases from Wuhan, authors ran the model across five time periods in 2020 (January 1 to 9; January 10 to 22; January 23 to February 1; February 2 to 16; and February 17 to March 8), defined by different events (e.g., Chinese New Year) and the implementation of intervention strategies (e.g., the cordons sanitaire). Authors estimated Re (the effective reproductive number, the reproductive number after the implementation of interventions and community transmission has occurred) for each time period and total cumulative cases across all time periods using these data. Authors also projected what the total cumulative cases would have been assuming the incidence trend from each time period continued uninterrupted until March 8, 2020 (i.e., assuming none or with no additional interventions than what occurred in each respective time period). Authors used confirmed cases exported from Wuhan to Singapore to estimate the ascertainment rate (the percentage of total cases that are reported and confirmed).

Summary of Main Findings

The Re in each time period was 3.54 (95% CrI: 3.40-3.67), 3.32 (3.19-3.44), 1.18 (1.11-1.25), 0.51 (0.47-0.54), and 0.28 (0.23-0.33), respectively from first to fifth/last. Authors credit the significant decrease in Re to the wide-spread and multi-level public health interventions implemented in Wuhan. Overall, authors estimated that a total of 249,187 (95% CrI: 198,412-307,062) cases (including unascertained cases) occurred when they fit the data across all five time periods; this was notably lower than when authors fit the data according to time period trends, which was estimated to be up to 6,302,694 (6,275,508-6,327,520) when the trend from the second time period was assumed. The model projected the number of daily infections (including unascertained cases) peaked on February 2, 2020 at 55,879 (43,582-69,571). Regardless of time period, case ascertainment rates were low: 0.15 (95% CrI: 0.13-0.17), 0.15 (0.13-0.17), 0.14 (0.11-0.17), 0.10 (0.08-0.12), 0.16 (0.13-0.21), respectively, from first to fifth/last, and 0.13 (0.11-0.16) overall. Due to the high proportion of presymptomatic and unascertained cases, authors estimated the probability of case resurgence could be as high as 97% and would occur approximately one month after the removal of control measures, assuming they were lifted 14 days after the first day of zero ascertained cases.

Study Strengths

Authors used laboratory-confirmed cases, ensuring that false clinical diagnoses did not bias results. Authors validated assumed parameters and estimation methods before running the full simulations; authors determined the model was able to make accurate estimations. The decreases observed in Re between time periods and the low proportion of unascertained cases were robust to sensitivity analyses.

Limitations

Delays in laboratory reporting may have resulted in an underestimation of the ascertainment rate, which would also overestimate the proportion of asymptomatic cases and the effect these cases would have on potential resurgence. Authors also excluded clinically confirmed cases without laboratory confirmation, which may have had similar effects on results. Authors assumed homogeneous transmission between heterogeneous populations; rates of transmission have been shown to vary between groups of differing ages, sexes, race/ethnicities, and geographic locations. Control measures were evaluated as a whole, so the effects of individual interventions on Re are not available.

Value added

This study sought to describe the full spectrum of the dynamics of the COVID-19 epidemic in Wuhan using laboratory-confirmed cases from the city. Results indicated control measures significantly reduced transmission and that there was a high proportion of unascertained cases. Understanding these dynamics is critical for surveillance and control measures, and could be used to inform strategies in countries still experiencing active transmission.

This review was posted on: 12 August 2020