Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

Abstract

The exported cases of 2019 novel coronavirus infection that were confirmed outside of China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number-the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January, 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

“…This study presents the estimates of epidemiological characteristics of COVID-19 infections that are key parameter for studies on incidence, case fatality, and epidemic final size, among other possibilities [7,11]. From the 95th percentile estimate of the incubation period we found that the length of quarantine should be at least 14 days, and we stress that the 17-24-day time delay from illness onset to death must be addressed when estimating COVID-19 case fatality risk.…”

“…Here, r is the exponential growth rate (estimated at 0.14 [11]), T is the latest time of observation (31 January 2020), and F(.) is the cumulative density function of f (.…”

Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19)

“…What the estimate of 9.2% also indicates is that the cCFR value is likely 11 times greater than the risk of death among all infected individuals, which is referred to as the infection fatality risk (IFR) [9]. For instance, if the value of cCFR is 5-8% as estimated earlier in [5], the IFR can be in a range of 0.5-0.7% out of all infected individuals. This value is also in line with another estimate of the IFR at 0.8% (95% CI: 0.4, 3.0) [6].…”

“…where c t is the daily number of cases (i.e., incidence) and f s is the probability density function of the time from illness onset to death-the relative frequency of the time from illness onset to death among fatal cases. See Jung et al [5] as an example of application of (2) for the ongoing COVID-19 epidemic. Table 1 compares the cCFR (adjusted estimate) and the value resulting from simple division (not adjusting for the time from illness onset to death).…”

“…Considering that the estimated mean time from illness onset to death can be as long as 20 days [5], there may be no deaths yet observed in Chinese cities with recent epidemic spread, which leads to underestimation of the risk of death. It must be remembered that the abovementioned issue can be neglected when the epidemic comes close to its end; even the division (1) converges to the unbiased value of the cCFR.…”