Evidence map›Paper›PMID 35946036›Full record

ArticleGeoHealth2022

The Relative Contribution of Climatic, Demographic Factors, Disease Control Measures and Spatiotemporal Heterogeneity to Variation of Global COVID-19 Transmission.

Yihan Cao, Jason D Whittington, Kyrre Kausrud, Ruiyun Li, Nils Chr Stenseth

Abstract read
In one paragraph

Article in GeoHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yihan CaoCentre for Ecological and Evolutionary Synthesis (CEES) Department of Biosciences University of Oslo Oslo Norway.ORCID https://orcid.org/0000-0002-3353-9825
Jason D WhittingtonCentre for Ecological and Evolutionary Synthesis (CEES) Department of Biosciences University of Oslo Oslo Norway.
Kyrre KausrudNorwegian Veterinary Institute Oslo Norway.
Ruiyun LiCentre for Ecological and Evolutionary Synthesis (CEES) Department of Biosciences University of Oslo Oslo Norway.
Nils Chr StensethCentre for Ecological and Evolutionary Synthesis (CEES) Department of Biosciences University of Oslo Oslo Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite a substantial number of COVID-19 related research papers published, it remains unclear as to which factors are associated with the observed variation in global transmission and what are their relative levels of importance. This study applies a rigorous statistical framework to provide robust estimations of the factor effects for a global and integrated perspective on this issue. We developed a mixed effect model exploring the relative importance of potential factors driving COVID-19 transmission while incorporating spatial and temporal heterogeneity of spread. We use an integrated data set for 87 countries across six continents for model specification and fitting. The best model accounts for 70.4% of the variance in the data analyzed: 10 fixed effect factors explain 20.5% of the variance, random temporal and spatial effects account for 50% of the variance. The fixed effect factors are classified into climatic, demographic and disease control groups. The explained variance in global transmission by the three groups are 0.6%, 1.1%, and 4.4% respectively. The high proportion of variance accounted for by random effects indicated striking differences in temporal transmission trajectories and effects of population mobility among the countries. In particular, the country-specific mobility-transmission relationship turns out to be the most important factor in explaining the observed global variation of transmission in the early phase of COVID-19 pandemic.

Indexed as

COVID‐19global transmissionmixed effect modelpopulation mobilitySARS‐CoV‐2spatiotemporal heterogeneity

Identifiers

PMID35946036
PMCPMC9349723

What OpenQuestion holds

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Registered trials

None linked

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.