Global patterns and drivers of influenza decline during the COVID-19 pandemic

Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved..

OBJECTIVES: 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.

METHODS: 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.

RESULTS: 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.

CONCLUSION: Our findings set the stage for interpreting the resurgence of influenza worldwide.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:128

Enthalten in:

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases - 128(2023) vom: 06. März, Seite 132-139

Sprache:

Englisch

Beteiligte Personen:

Bonacina, Francesco [VerfasserIn]
Boëlle, Pierre-Yves [VerfasserIn]
Colizza, Vittoria [VerfasserIn]
Lopez, Olivier [VerfasserIn]
Thomas, Maud [VerfasserIn]
Poletto, Chiara [VerfasserIn]

Links:

Volltext

Themen:

COVID-19 pandemic
Global analysis
Influenza
Journal Article
Regression trees

Anmerkungen:

Date Completed 27.02.2023

Date Revised 20.03.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.ijid.2022.12.042

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM35119889X