Evidence map›Paper›PMID 33928060›Full record

ArticleFrontiers in public health2021

A Vulnerability Analysis for the Management of and Response to the COVID-19 Epidemic in the Second Most Populous State in Brazil.

Igor Silva Campos, Vinícius Ferreira Aratani, Karina Baltor Cabral, Jean Ezequiel Limongi, Stefan Vilges de Oliveira

Abstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Age, gender and household infrastructural inequality in COVID-19: Contextual analysis of Mamelodi.South African family practice : official journal of the South African Academy of Family Practice/Primary Care · 2024
    Article
  3. Article
  4. Article
  5. Infrastructural Inequality and Household COVID-19 Vulnerability in a South African Urban Settlement.Journal of urban health : bulletin of the New York Academy of Medicine · 2022
    Article
  6. Article
  7. Article
  8. Analyzing the Risk to COVID-19 Infection using Remote Sensing and GIS.Risk analysis : an official publication of the Society for Risk Analysis · 2021
    Article
  9. 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.

Igor Silva CamposUndergraduate Medical, Faculty of Medicine, Federal University of Uberlândia, Uberlândia, Brazil.
Vinícius Ferreira ArataniUndergraduate Medical, Faculty of Medicine, Federal University of Uberlândia, Uberlândia, Brazil.
Karina Baltor CabralUndergraduate Medical, Faculty of Medicine, Federal University of Uberlândia, Uberlândia, Brazil.
Jean Ezequiel LimongiUndergraduate Course in Collective Health, Institute of Geography, Federal University of Uberlândia, Uberlândia, Brazil.
Stefan Vilges de OliveiraDepartment of Collective Health, Faculty of Medicine, Federal University of Uberlândia, Uberlândia, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. An epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature search and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on Indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1-5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte was the most vulnerable mesoregion, with 42.9 and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.

Indexed as

COVID-19BrazilCitiesHumansPandemicsSARS-CoV-2COVID-19disease outbreaksepidemicshealth policypolicy formulationsocial vulnerability

Identifiers

PMID33928060
PMCPMC8076526

What OpenQuestion holds

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Registered trials

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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.