Back to Search
Start Over
Global patterns and drivers of influenza decline during the COVID-19 pandemic.
- Source :
-
International Journal of Infectious Diseases . Mar2023, Vol. 128, p132-139. 8p. - Publication Year :
- 2023
-
Abstract
- • We analyzed the global reduction of influenza during the COVID-19 pandemic. • With regression trees, we classified trimesters-countries with similar influenza drop. • The decline in influenza was global but heterogeneous across space and time. • Countries with low flu drop had low pandemic preparedness and mild COVID-19 response. • A group of four "zero-COVID" countries experienced the greatest influenza decline. The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers. The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors. During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The "zero-COVID" countries experienced the greatest decline. Our findings set the stage for interpreting the resurgence of influenza worldwide. [ABSTRACT FROM AUTHOR]
- Subjects :
- *COVID-19 pandemic
*INFLUENZA
*REGRESSION trees
*RANDOM forest algorithms
*DATABASES
Subjects
Details
- Language :
- English
- ISSN :
- 12019712
- Volume :
- 128
- Database :
- Academic Search Index
- Journal :
- International Journal of Infectious Diseases
- Publication Type :
- Academic Journal
- Accession number :
- 162009324
- Full Text :
- https://doi.org/10.1016/j.ijid.2022.12.042