Evidence map›Paper›PMID 34465641›Full record

ArticleJournal of research in health sciences2021

Predictive Role of Population Density and Use of Public Transport for Major Outcomes of SARS-CoV-2 Infection in the Italian Population: An Ecological Study.

Alfonso Ilardi, Sergio Chieffi, Ciro Rosario Ilardi

Abstract read
In one paragraph

Article in Journal of research in health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Alfonso IlardiDepartment of Internal Medicine, A.O.R.N. "Antonio Cardarelli Hospital", Naples, Italy. alfonso.ilardi@aocardarelli.it.
Sergio ChieffiDepartment of Experimental Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Ciro Rosario IlardiDepartment of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed at assessing how population density (PD), aging index (AI), use of public transport (URPT), and PM10 concentration (PI) modulated the trajectory of the main COVID-19 pandemic outcomes in Italy, also in the recrudescence phase of the epidemic. STUDY

designEcological study.

methodsFor each region, we recovered data about cases, deaths, and case fatality rate (CFR) recorded since both the beginning of the epidemic and September 1, 2020. Data about total hospitalizations were included as well.

resultsPD correlated with, and was the best predictor of, total and partial cases, total and partial deaths, and total hospitalizations. Moreover, URPT correlated with, and was the best predictor of, total CFR. Besides, PI correlated significantly with total and partial cases, total and partial deaths, and total hospitalizations.

conclusionPD explains COVID-19 morbidity, mortality, and severity while URPT is the best predictor of disease lethality. These findings should be interpreted with caution due to the ecological fallacy.

Indexed as

HospitalizationPandemicsPopulation DensityTransportationAge FactorsAir PollutionCOVID-19EnvironmentHumansItalyParticle SizeRecurrenceRisk FactorsSARS-CoV-2Severity of Illness IndexAir PollutionCOVID-19Ecological StudyPopulation DensityPublic Transport

Identifiers

PMID34465641
PMCPMC8957675

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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.