Evidence map›Paper›PMID 32498152›Full record

ArticleThe Science of the total environment2020

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID.

Mario Coccia

Abstract read
In one paragraph

Article in The Science of the total environment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 292 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
292citing papers in PubMed, 6 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

292 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  3. The role of children in household transmission of COVID-19: a systematic review and meta-analysis.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Pooled it
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  5. Surface contamination with SARS-CoV-2: A systematic review.The Science of the total environment · 2021
    Pooled it
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232 more citing papers are in PubMed but not listed here.

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

1 author.

Mario CocciaCNR - National Research Council of Italy, Research Institute on Sustainable Economic Growth, Collegio Carlo Alberto, Via Real Collegio, 30-10024 Moncalieri, Torino, Italy; Yale School of Medicine, 310 Cedar Street, Lauder Hall, New Haven, CT 06510, USA. Electronic address: mario.coccia@cnr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM

Indexed as

Air PollutionBetacoronavirusCoronavirus InfectionsPandemicsPneumonia, ViralAir PollutantsCitiesCOVID-19HumansItalyParticulate MatterSARS-CoV-2Air PollutantsParticulate MatterAirborne diseaseAirborne TransmissionAir PollutionCoronavirus InfectionCOVID-19Disease TransmissionEpidemic OutbreakInfection PreventionLung DiseaseOpportunistic pathogenPandemicParticulate MatterQuarantineSARS CoronavirusSARS-CoV-2Severe Acute Respiratory Syndrome Coronavirus 2Transmission DynamicsViral infectivityVirus PneumoniaVirus Transmission

Identifiers

PMID32498152
PMCPMC7169901

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.