Evidence map›Paper›PMID 39767445›Full record

ArticleInternational journal of environmental research and public health2024

An Ecological Study Relating the SARS-CoV-2 Epidemiology with Health-Related, Socio-Demographic, and Geographical Characteristics in South Tyrol (Italy).

Antonio Lorenzon, Lucia Palandri, Francesco Uguzzoni, Catalina Doina Cristofor, Filippo Lozza, Cristiana Rizzi, Riccardo Poluzzi, Pierpaolo Bertoli, Florian Zerzer, Elena Righi

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

10 authors.

Antonio LorenzonEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.ORCID 0009-0006-2001-6140
Lucia PalandriDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy.
Francesco UguzzoniDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy.
Catalina Doina CristoforEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.
Filippo LozzaEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.
Cristiana RizziDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy.
Riccardo PoluzziEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.
Pierpaolo BertoliEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.
Florian ZerzerEpidemiological Surveillance Unit, South Tyrolean Healthcare Agency, 39100 Bolzano, Italy.
Elena RighiDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy.ORCID 0000-0002-3469-7446

Funding

Department of Innovation, Research, University and Museums of the Au-tonomous Province of Bozen/Bolzano for covering the Open Access publication costs. none
6 · The paper itself

Abstract

The literature associating the spread of SARS-CoV-2 with the healthcare-related, geographical, and demographic characteristics of the territory is inconclusive and contrasting. We studied these relationships during winter 2021/2022 in South Tyrol, a multicultural Italian alpine province, performing an ecological study based on the 20 districts of the area. Data about incidence, hospitalization, and death between November 2021 and February 2022 were collected and associated to territorial variables via bivariate analyses and multivariate regressions. Both exposure variables and outcomes varied widely among districts. Incidence was found to be mainly predicted by vaccination coverage (negative correlation). Mortality and ICU admission rates partially followed this distribution, while the case fatality rate was inversely correlated to average salary, and hospital admission rates increased where hospitals capacity was higher, and from the southern to the northern border of the province. These findings, besides confirming the efficacy of vaccination in preventing both new and severe SARS-CoV-2 cases, highlight that several geographical and socio-demographic variables can be related to disease epidemiology. Remote areas with wage gaps and lower access to care suffered most from the pandemic. Our findings, therefore, underly the existence of health inequity issues that need to be targeted by implementing specifically tailored public health interventions.

Indexed as

COVID-19SARS-CoV-2FemaleHospitalizationHumansIncidenceItalyMaleSociodemographic FactorsSocioeconomic Factorshealth inequitiesherd immunitySARS-CoV-2

Identifiers

PMID39767445
PMCPMC11675570

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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.