The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases
Open accessAbstract
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 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% 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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Cites
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Self-citationDonnelly, C. A., Ghani, A. C., Leung, G. M., Hedley, A. J., Fraser, C., Riley, S., Abu-Raddad, L. J., Ho, L.-M., Thach, T.-Q., Chau, P., et al. (2003) · The Lancet · doi:10.1016/s0140-6736(03)13410-1 · Cited by 940 · cited 2×
“Our cCFR estimates of 5.3% and 8.4% indicate that the severity of COVID-19 is not as high as that of other diseases caused by coronaviruses, including severe acute respiratory syndrome (SARS), which had an estimated CFR of 17% in Hong Kong [9,10,20], and Middle East respiratory syndrome, which had an estimated CFR of…”
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Cited by
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Verity, R., Okell, L. C., Dorigatti, I., Winskill, P., Whittaker, C., Imai, N., Cuomo-Dannenburg, G., Thompson, H., Walker, P. G. T., Fu, H., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30243-7 · Cited by 3,660
Serial interval of novel coronavirus (COVID-19) infections
Nishiura, H., Linton, N. M., & Akhmetzhanov, A. R. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.02.060 · Cited by 1,083
Self-citationIranian mental health during the COVID-19 epidemic
Zandifar, A., & Badrfam, R. (2020) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2020.101990 · Cited by 789
Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK
CMMID COVID-19 working group, Jarvis, C. I., Van Zandvoort, K., Gimma, A., Prem, K., Klepac, P., Rubin, G. J., & Edmunds, W. J. (2020) · BMC Medicine · doi:10.1186/s12916-020-01597-8 · Cited by 720
Evidence for transmission of COVID-19 prior to symptom onset
Tindale, L. C., Stockdale, J. E., Coombe, M., Garlock, E. S., Lau, W. Y. V., Saraswat, M., Zhang, L., Chen, D., Wallinga, J., & Colijn, C. (2020) · eLife · doi:10.7554/elife.57149 · Cited by 452
Metadata
- Authors
- Jung, S.-M., Akhmetzhanov, A. R., Hayashi, K., Linton, N. M., Yang, Y., Yuan, B., Kobayashi, T., Kinoshita, R., & Nishiura, H.
- Venue
- Journal of Clinical Medicine
- Publisher
- MDPI AG
- Published
- 2020-02-14
- Volume
- 9
- Issue
- 2
- Pages
- 523
- ISSN
- 2077-0383 (ISSN-L)
- OpenAlex
- W3005847234
- Cited by
- 374
- References
- 2
- FWCI
- 14.25
- Type
- journal article
- Language
- en
- Open access
- gold
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- Jung, S.-M., Akhmetzhanov, A. R., Hayashi, K., Linton, N. M., Yang, Y., Yuan, B., Kobayashi, T., Kinoshita, R., & Nishiura, H. (2020). Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases. Journal of Clinical Medicine. https://doi.org/10.3390/jcm9020523
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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