Evidence map›Paper›PMID 36532873›Full record

ArticleInternational journal of disaster risk reduction : IJDRR2023

A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran.

Mahmoud Arvin, Shahram Bazrafkan, Parisa Beiki, Ayyoob Sharifi

Open access · greenAbstract read
In one paragraph

Article in International journal of disaster risk reduction : IJDRR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 26% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

4 authors at 4 institutions in 2 countries.

Mahmoud ArvinDepartment of Human Geography, Faculty of Geography, University of Tehran, Iran.
Shahram BazrafkanDepartment of Human Geography and Spatial Planning, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran.
Parisa BeikiDepartment of Geography, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Ayyoob SharifiHiroshima University, ،The IDEC Institute, the Graduate School of Humanities and Social Science, and the Network for Education and Research on Peace and Sustainability (NERPS), Japan.
Hiroshima University · JPIslamic Azad University Central Tehran Branch · IRShahid Beheshti University · IRUniversity of Tehran · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social vulnerability is related to the differential abilities of socio-economic groups to withstand and respond to the adverse impacts of hazards and stressors. COVID-19, as a human risk, is influenced by and contributes to social vulnerability. The purpose of this study was to examine the association between social vulnerability and the prevalence of COVID-19 infection in the counties of Khuzestan province, Iran. To determine the social vulnerability of the counties in the Khuzestan province, decision-making techniques and geographic information systems were employed. Also, the Pearson correlation was used to examine the relationship between the two variables. The findings indicate that Ahvaz county and the province's northeastern counties have the highest levels of social vulnerability. There was no significant link between the social vulnerability index of the counties and the rate of COVID-19 cases (per 1000 persons). We argue that all counties in the province should implement and pursue COVID-19 control programs and policies. This is particularly essential for counties with greater rates of social vulnerability and COVID-19 cases.

Indexed as

Community resilienceCOVID-19GISMulti-criteria decision making techniquesSocial vulnerabilityUrban resilience

Identifiers

PMID36532873
PMCPMC9747688
OpenAlexW4311480343

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.