Evidence map›Paper›PMID 34999027›Full record

ArticleEnvironmental research2022

Meteorological factors' effects on COVID-19 show seasonality and spatiality in Brazil.

Caichun Yin, Wenwu Zhao, Paulo Pereira

Abstract read
In one paragraph

Article in Environmental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  10. Effects of fine particulate matter (PMCase studies in chemical and environmental engineering · 2023
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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

3 authors.

Caichun YinState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Wenwu ZhaoState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China. Electronic address: zhaoww@bnu.edu.cn.
Paulo PereiraEnvironmental Management Center, Mykolas Romeris University, Vilnius, 08303, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The meteorological conditions may affect COVID-19 transmission. However, the roles of seasonality and macro-climate are still contentious due to the limited time series for early-stage studies. We studied meteorological factors' effects on COVID-19 transmission in Brazil from February 25 to November 15, 2020. We aimed to explore whether this impact showed seasonal characteristics and spatial variations related to the macro-climate. We applied two-way fixed-effect models to identify the effects of meteorological factors on COVID-19 transmission and used spatial analysis to explore their spatial-temporal characteristics with a relatively long-time span. The results showed that cold, dry and windless conditions aggravated COVID-19 transmission. The daily average temperature, humidity, and wind speed negatively affected the daily new cases. Humidity and temperature played a dominant role in this process. For the time series, the influences of meteorological conditions on COVID-19 had a periodic fluctuation of 3-4 months (in line with the seasons in Brazil). The turning points of this fluctuation occurred at the turn of seasons. Spatially, the negative effects of temperature and humidity on COVID-19 transmission clustered in the northeastern and central parts of Brazil. This is consistent with the range of arid climate types. Overall, the seasonality and similar climate types should be considered to estimate the spatial-temporal COVID-19 patterns. Winter is a critical time to be alert for COVID-19, especially in the northern part of Brazil.

Indexed as

COVID-19BrazilHumansHumidityMeteorological ConceptsSARS-CoV-2SeasonsTemperatureClimateCOVID-19Meteorological factorsSeasonalitySpatiality

Identifiers

PMID34999027
PMCPMC8734082

What OpenQuestion holds

Textmetadata
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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.