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Estimation of disease burden and clinical severity of COVID-19 caused by Omicron BA.2 in Shanghai, February-June 2022.

ABSTRACT:

SUBMITTER: Chen X

PROVIDER: S-EPMC9327634 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Estimation of disease burden and clinical severity of COVID-19 caused by Omicron BA.2 in Shanghai, February-June 2022.

Chen Xinhua X Yan Xuemei X Sun Kaiyuan K Zheng Nan N Sun Ruijia R Zhou Jiaxin J Deng Xiaowei X Zhuang Tingyu T Cai Jun J Zhang Juanjuan J Ajelli Marco M Yu Hongjie H

medRxiv : the preprint server for health sciences 20220712

<h4>Background</h4>An outbreak of COVID-19 caused by the SARS-CoV-2 Omicron BA.2 sublineage occurred in Shanghai, China from February to June 2022. The government organized multiple rounds of molecular test screenings for the entire population, providing a unique opportunity to capture the majority of subclinical infections and better characterize disease burden and the full spectrum of Omicron BA.2 clinical severity.<h4>Methods</h4>Using daily reports from the websites of the Shanghai Municipal ...[more]

PMID: 35898339

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Project description:BackgroundShanghai experienced a significant surge in Omicron BA.2 infections from March to June 2022. In addition to the standard interventions in place at that time, additional interventions were implemented in response to the outbreak. However, the impact of these interventions on BA.2 transmission remains unclear.MethodsWe systematically collected data on the daily number of newly reported infections during this wave and utilized a Bayesian approach to estimate the daily effective reproduction number. Data on public health responses were retrieved from the Oxford COVID-19 Government Response Tracker and served as a proxy for the interventions implemented during this outbreak. Using a log-linear regression model, we assessed the impact of these interventions on the reproduction number. Furthermore, we developed a mathematical model of BA.2 transmission. By combining the estimated effect of the interventions from the regression model and the transmission model, we estimated the number of infections and deaths averted by the implemented interventions.ResultsWe found a negative association (-0.0069, 95% CI: 0.0096 to -0.0045) between the level of interventions and the number of infections. If interventions did not ramp up during the outbreak, we estimated that the number of infections and deaths would have increased by 22.6% (95% CI: 22.4-22.8%), leading to a total of 768,576 (95% CI: 768,021-769,107) infections and 722 (95% CI: 722-723) deaths. If no interventions were deployed during the outbreak, we estimated that the number of infections and deaths would have increased by 46.0% (95% CI: 45.8-46.2%), leading to a total of 915,099 (95% CI: 914,639-915,518) infections and 860 (95% CI: 860-861) deaths.ConclusionOur findings suggest that the interventions adopted during the Omicron BA.2 outbreak in spring 2022 in Shanghai were effective in reducing SARS-CoV-2 transmission and disease burden. Our findings emphasize the importance of non-pharmacological interventions in controlling quick surges of cases during epidemic outbreaks.

Dataset Information

Estimation of disease burden and clinical severity of COVID-19 caused by Omicron BA.2 in Shanghai, February-June 2022.

Publications

Estimation of disease burden and clinical severity of COVID-19 caused by Omicron BA.2 in Shanghai, February-June 2022.

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