ArticleJMIR public health and surveillance2021
The Relationship Between the Global Burden of Influenza From 2017 to 2019 and COVID-19: Descriptive Epidemiological Assessment.
Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Leveraging epidemiological principles to evaluate Sweden's COVID-19 response.Annals of epidemiology · 2021Article
- The possible impact of increased physical intimate partner violence during the COVID-19 pandemic on ocular health.SAGE open medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 5 countries.
Funding
Abstract
backgroundSARS-CoV-2 and influenza are lipid-enveloped viruses with differential morbidity and mortality but shared modes of transmission.
objectiveWith a descriptive epidemiological framing, we assessed whether recent historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.
methodsWeekly surveillance data reported by the World Health Organization from January 2017 to December 2019 for influenza and from January 1, 2020 through October 31, 2020, for COVID-19 were used to assess seasonal and temporal trends for influenza and COVID-19 cases across the seven World Bank regions.
resultsIn regions with more pronounced influenza seasonality, COVID-19 epidemics have largely followed trends similar to those seen for influenza from 2017 to 2019. COVID-19 epidemics in countries across Europe, Central Asia, and North America have been marked by a first peak during the spring, followed by significant reductions in COVID-19 cases in the summer months and a second wave in the fall. In Latin America and the Caribbean, COVID-19 epidemics in several countries peaked in the summer, corresponding to months with the highest influenza activity in the region. Countries from regions with less pronounced influenza activity, including South Asia and sub-Saharan Africa, showed more heterogeneity in COVID-19 epidemics seen to date. However, similarities in COVID-19 and influenza trends were evident within select countries irrespective of region.
conclusionsEcological consistency in COVID-19 trends seen to date with influenza trends suggests the potential for 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 nonpharmacologic 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.