Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Oct 1, 2020
Date Accepted: Jan 21, 2021
Date Submitted to PubMed: Mar 5, 2021
Descriptive Epidemiological Assessment of the Relationship between the Global Burden of Influenza from 2017-2019 and COVID-19
ABSTRACT
Background:
SARS-CoV-2 and influenza are lipid-enveloped viruses with differential morbidity and mortality but shared modes of transmission. With a descriptive epidemiological framing, we assessed whether historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.
Objective:
With a descriptive epidemiological framing, we assessed whether historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.
Methods:
Weekly surveillance data reported in FluNet from January 2017–December 2019 for influenza and World Health Organization for COVID-19 (to May 31, 2020) across the seven World Bank regions were used to assess the total and annual number of influenza and COVID-19 cases per country, within and across all regions, to generate comparative descending ranks from highest to lowest burden of disease.
Results:
Across regions, rankings of influenza and COVID-19 were relatively consistent. Europe and Central Asia and North America ranked first and second for COVID-19 and second and first for influenza, respectively. East Asia and the Pacific traditionally ranked higher for influenza with recent increases in COVID-19 consistent with influenza season. Across regions, Sub-Saharan Africa ranked amongst the least affected by both influenza and COVID-19.
Conclusions:
Consistency in the regional distribution of the burden of COVID-19 and influenza suggest shared individual, structural, and environmental determinants of transmission. Using a descriptive epidemiological framework to assess shared regional trends for rapidly emerging respiratory pathogens with better studied respiratory infections may provide further insights into the differential impacts of non-pharmacologic interventions and intersections with environmental conditions. Ultimately, forecasting trends and informing interventions for novel respiratory pathogens like COVID-19 should leverage epidemiologic patterns in the relative burden of past respiratory pathogens as prior information.
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