4.7 Article

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

Journal

JOURNAL OF CLINICAL MEDICINE
Volume 9, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/jcm9020523

Keywords

mortality; censoring; travel; migration; importation; emerging infectious diseases

Funding

  1. Japan Agency for Medical Research and Development (AMED) [JP18fk0108050]
  2. Japan Society for the Promotion of Science (JSPS) KAKENHI [17H04701, 17H05808, 18H04895, 19H01074, 18J21587]
  3. Inamori Foundation
  4. Japan Science and Technology Agency (JST) CREST program [JPMJCR1413]
  5. Ministry of Education, Culture, Sports, Science and Technology, Japan
  6. China Scholarship Council
  7. Grants-in-Aid for Scientific Research [19H01074, 18J21587] Funding Source: KAKEN

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The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside 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 naive 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% confidence interval [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.

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