Your browser doesn't support javascript.
Using an influenza surveillance system to estimate the number of SARS-CoV-2 infections in Beijing, China, weeks 2 to 6 2023.
Zhang, Li; Zhang, Yi; Duan, Wei; Wu, Shuangsheng; Sun, Ying; Ma, Chunna; Wang, Quanyi; Zhang, Daitao; Yang, Peng.
  • Zhang L; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Zhang Y; General Administration of Customs (Beijing) International Travel Health Care Center, Dongcheng District, Beijing, China.
  • Duan W; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Wu S; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Sun Y; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Ma C; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Wang Q; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Zhang D; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
  • Yang P; Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China.
Euro Surveill ; 28(11)2023 03.
Article in English | MEDLINE | ID: covidwho-2288582
ABSTRACT
With COVID-19 public health control measures downgraded in China in January 2023, reported COVID-19 case numbers may underestimate the true numbers after the SARS-CoV-2 Omicron wave. Using a multiplier model based on our influenza surveillance system, we estimated that the overall incidence of SARS-CoV-2 infections was 392/100,000 population in Beijing during the 5 weeks following policy adjustment. No notable change occurred after the Spring Festival in early February. The multiplier model provides an opportunity for assessing the actual COVID-19 situation.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza, Human / COVID-19 Type of study: Diagnostic study / Observational study Topics: Variants Limits: Humans Country/Region as subject: Asia Language: English Journal subject: Communicable Diseases Year: 2023 Document Type: Article Affiliation country: 1560-7917.ES.2023.28.11.2300128

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza, Human / COVID-19 Type of study: Diagnostic study / Observational study Topics: Variants Limits: Humans Country/Region as subject: Asia Language: English Journal subject: Communicable Diseases Year: 2023 Document Type: Article Affiliation country: 1560-7917.ES.2023.28.11.2300128