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Assessment of the fatality rate and transmissibility taking account of undetected cases during an unprecedented COVID-19 surge in Taiwan.
Yuan, Hsiang-Yu; Hossain, M Pear; Wen, Tzai-Hung; Wang, Ming-Jiuh.
  • Yuan HY; Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, SAR, China. sean.yuan@cityu.edu.hk.
  • Hossain MP; Centre for Applied One Health Research and Policy Advice, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, SAR, China. sean.yuan@cityu.edu.hk.
  • Wen TH; Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, SAR, China.
  • Wang MJ; Department of Geography, National Taiwan University, Taipei City, Taiwan.
BMC Infect Dis ; 22(1): 271, 2022 Mar 20.
Article in English | MEDLINE | ID: covidwho-1745483
ABSTRACT

BACKGROUND:

During the COVID-19 outbreak in Taiwan between May 11 and June 20, 2021, the observed fatality rate (FR) was 5.3%, higher than the global average at 2.1%. The high number of reported deaths suggests that many patients were not treated promptly or effectively. However, many unexplained deaths were subsequently identified as cases, indicating a few undetected cases, resulting in a higher estimate of FR. Whether the true FR is exceedingly high and what factors determine the detection of cases remain unknown. Estimating the true number of total infected cases (i.e. including undetected cases) can allow an accurate estimation of FR and effective reproduction number ([Formula see text]).

METHODS:

We aimed at quantifying the time-varying FR and [Formula see text] using the estimated true numbers of cases; and, exploring the relationship between the true case number and test and trace data. After adjusting for reporting delays, we developed a model to estimate the number of undetected cases using reported deaths that were and were not previously detected. The daily FR and [Formula see text] were calculated using the true number of cases. Afterwards, a logistic regression model was used to assess the impact of daily testing and tracing data on the detection ratio of deaths.

RESULTS:

The estimated true daily case number at the peak of the outbreak on May 22 was 897, which was 24.3% higher than the reported number, but the difference became less than 4% on June 9 and afterwards. After taking account of undetected cases, our estimated mean FR (4.7%) was still high but the daily rate showed a large decrease from 6.5% on May 19 to 2.8% on June 6. [Formula see text] reached a maximum value of 6.4 on May 11, compared to 6.0 estimated using the reported case number. The decreasing proportion of undetected cases was found to be associated with the increases in the ratio of the number of tests conducted to reported cases, and the proportion of cases that are contact traced before symptom onset.

CONCLUSIONS:

Increasing testing capacity and contact tracing coverage without delays not only improve parameter estimation by reducing hidden cases but may also reduce fatality rates.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: S12879-022-07190-Z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: S12879-022-07190-Z