A Neighborhood-level Analysis of Association Between Social Vulnerability and COVID-19 in Ahvaz, Iran

Overview

Journal Int J Disaster Risk Reduct

Date 2023 Jan 2

PMID 36589205

Authors

Mahmoud Arvin

Parisa Beiki

Saeed Zanganeh Shahraki

Affiliations

Soon will be listed here.

Abstract

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.

Citing Articles

An investigation to offer conclusive recommendations on suitable benefit/cost criteria-based normalization methods for TOPSIS.

Krishnan A, Hamid M, Tanakinjal G, Asli M, Boniface B, Ghazali M MethodsX. 2023; 10:102227.

PMID: 37333510 PMC: 10272499. DOI: 10.1016/j.mex.2023.102227.

References

Shafer P, Anderson D, Whitaker R, Wong C, Wright B . Association Of Unemployment With Medicaid Enrollment By Social Vulnerability In North Carolina During COVID-19. Health Aff (Millwood). 2021; 40(9):1491-1500. DOI: 10.1377/hlthaff.2021.00377. View

Tran B, Vu G, Latkin C, Pham H, Phan H, Le H . Characterize health and economic vulnerabilities of workers to control the emergence of COVID-19 in an industrial zone in Vietnam. Saf Sci. 2020; 129:104811. PMC: 7214303. DOI: 10.1016/j.ssci.2020.104811. View

Borojerdnia A, Rozbahani M, Nazarpour A, Ghanavati N, Payandeh K . Application of exploratory and Spatial Data Analysis (SDA), singularity matrix analysis, and fractal models to delineate background of potentially toxic elements: A case study of Ahvaz, SW Iran. Sci Total Environ. 2020; 740:140103. DOI: 10.1016/j.scitotenv.2020.140103. View

Mishra S, Gayen A, Haque S . COVID-19 and urban vulnerability in India. Habitat Int. 2020; 103:102230. PMC: 7434393. DOI: 10.1016/j.habitatint.2020.102230. View

Sharifi A, Khavarian-Garmsir A . The COVID-19 pandemic: Impacts on cities and major lessons for urban planning, design, and management. Sci Total Environ. 2020; 749:142391. PMC: 7499053. DOI: 10.1016/j.scitotenv.2020.142391. View

Tang S, Horter L, Bosh K, Kassem A, Kahn E, Ricaldi J . Change in unemployment by social vulnerability among United States counties with rapid increases in COVID-19 incidence-July 1-October 31, 2020. PLoS One. 2022; 17(4):e0265888. PMC: 9020703. DOI: 10.1371/journal.pone.0265888. View

Bourouiba L . Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19. JAMA. 2020; 323(18):1837-1838. DOI: 10.1001/jama.2020.4756. View

Oztig L, Askin O . Human mobility and coronavirus disease 2019 (COVID-19): a negative binomial regression analysis. Public Health. 2020; 185:364-367. PMC: 7351378. DOI: 10.1016/j.puhe.2020.07.002. View

Brown K, Lewis J, Davis S . An ecological study of the association between neighborhood racial and economic residential segregation with COVID-19 vulnerability in the United States' capital city. Ann Epidemiol. 2021; 59:33-36. PMC: 9761656. DOI: 10.1016/j.annepidem.2021.04.003. View

10.

Lopez-Gay A, Spijker J, Cole H, Marques A, Triguero-Mas M, Anguelovski I . Sociodemographic determinants of intraurban variations in COVID-19 incidence: the case of Barcelona. J Epidemiol Community Health. 2021; 76(1):1-7. DOI: 10.1136/jech-2020-216325. View

11.

Mansour S, Al Kindi A, Al-Said A, Al-Said A, Atkinson P . Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR). Sustain Cities Soc. 2020; 65:102627. PMC: 7709730. DOI: 10.1016/j.scs.2020.102627. View

12.

Requia W, Kondo E, Adams M, Gold D, Struchiner C . Risk of the Brazilian health care system over 5572 municipalities to exceed health care capacity due to the 2019 novel coronavirus (COVID-19). Sci Total Environ. 2020; 730:139144. PMC: 7252142. DOI: 10.1016/j.scitotenv.2020.139144. View

13.

Fletcher P, Worthen D, McSweeney-Feld M, Gibson A, Seblova D, Pagan L . Rural Older Adults in Disasters: A Study of Recovery From Hurricane Michael. Disaster Med Public Health Prep. 2021; :1-5. DOI: 10.1017/dmp.2021.276. View

14.

Islam S, Nayak A, Hu Y, Mehta A, Dieppa K, Almuwaqqat Z . Temporal trends in the association of social vulnerability and race/ethnicity with county-level COVID-19 incidence and outcomes in the USA: an ecological analysis. BMJ Open. 2021; 11(7):e048086. PMC: 8300549. DOI: 10.1136/bmjopen-2020-048086. View

15.

Baghlaninezhad R, Beiromvand M, Veisi M . Analysis of knowledge and attitudes related to parasitic infections among inhabitants of Ahvaz County, Khuzestan Province, Iran. Acta Trop. 2019; 193:211-216. DOI: 10.1016/j.actatropica.2019.03.014. View

16.

Durizzo K, Asiedu E, van der Merwe A, Van Niekerk A, Gunther I . Managing the COVID-19 pandemic in poor urban neighborhoods: The case of Accra and Johannesburg. World Dev. 2020; 137:105175. PMC: 7455159. DOI: 10.1016/j.worlddev.2020.105175. View

17.

Yang Y, Xiang X . Examine the associations between perceived neighborhood conditions, physical activity, and mental health during the COVID-19 pandemic. Health Place. 2021; 67:102505. PMC: 9760872. DOI: 10.1016/j.healthplace.2021.102505. View

18.

Das M, Das A, Giri B, Sarkar R, Saha S . Habitat vulnerability in slum areas of India - What we learnt from COVID-19?. Int J Disaster Risk Reduct. 2021; 65:102553. PMC: 8421084. DOI: 10.1016/j.ijdrr.2021.102553. View

19.

Lak A, Sharifi A, Badr S, Zali A, Maher A, Mostafavi E . Spatio-temporal patterns of the COVID-19 pandemic, and place-based influential factors at the neighborhood scale in Tehran. Sustain Cities Soc. 2022; 72:103034. PMC: 9761301. DOI: 10.1016/j.scs.2021.103034. View

20.

Harris R . Exploring the neighbourhood-level correlates of Covid-19 deaths in London using a difference across spatial boundaries method. Health Place. 2020; 66:102446. PMC: 7539541. DOI: 10.1016/j.healthplace.2020.102446. View