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Assessing the impact of interventions on the major Omicron BA.2 outbreak in spring 2022 in Shanghai.
Liu, Hengcong; Cai, Jun; Zhou, Jiaxin; Xu, Xiangyanyu; Ajelli, Marco; Yu, Hongjie.
Afiliación
  • Liu H; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Cai J; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Zhou J; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Xu X; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
  • Ajelli M; Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Yu H; Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China.
Infect Dis Model ; 9(2): 519-526, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38463154
ABSTRACT

Background:

Shanghai 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.

Methods:

We 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.

Results:

We 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.

Conclusion:

Our 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.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 4_TD Problema de salud: 4_covid_19 Idioma: En Revista: Infect Dis Model Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 4_TD Problema de salud: 4_covid_19 Idioma: En Revista: Infect Dis Model Año: 2024 Tipo del documento: Article País de afiliación: China
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