IDENTIFYING COVIDOGENIC ENVIRONMENTS IN URBAN SECTORS OF KHROUB CITY (ALGERIA): A GIS-BASED APPROACH TO ASSESSING PANDEMIC RISK AND VULNERABILITY
Abstract
This study aims to assess the pandemic risk in the Algerian city of Khroub and develop a monitoring and health management tool to combat Covid-19 and other respiratory infections. To address the lack of statistical data at the micro-urban level, the authors conducted a household survey in Khroub between July and September 2022. The primary objective of this survey was to collect comprehensive data on vulnerability indicators at the scale of Khroub's urban sectors. The study utilized 13 indicators of vulnerability to Covid-19, selected from previous studies and research published by public health organizations and agencies. GIS technology was used to locate covidogenic environments (milieu) in Khroub, resulting in the creation of a GIS database called "Covidogenic Milieu." This study provides valuable insights for identifying vulnerable urban sectors and implementing adaptive measures to mitigate the effects of Covid-19. In the case of Khroub, the research also made relevant suggestions on how to address the identified vulnerability for the benefit of local authorities who commissioned this study.
References
Principles of Epidemiology in Public Health practice. Centers for Disease Control and Prevention. 2006. (Course SS1978). [Available from] https://www.cdc.gov›csels›dsepd
Pardo IF, Napoletano BM, Verges FR, Billa L. Spatial analysis and GIS in the study of COVID-19, a review. Science of The Total Environment.2020; (739); 140033. https://doi.org/10.1016/j.scitotenv.2020.140033.
Xie Z, Zhao R, Ding M, Zhang Z. A review of influencing factors on spatial spread of covid-19 based on geographical perspective. Int. J. Environ. Res. Public Health .2021; (18), 12182. https://doi.org/10.3390/ijerph182212182
Ramadan RH, Ramadan MS. Prediction of highly vulnerable areas to COVID-19 outbreaks using spatial model: Case study of Cairo Governorate, Egypt. The Egyptian Journal of Remote Sensing and Space Sciences. 2022; 25(1): 233–47. doi: 10.1016/j.ejrs.2021.08.003.
Kalla M, Lahmar B, Geullouh S, Kalla M. Health geo-governance to assess the vulnerability of Batna, Algeria to COVID-19: the role of GIS in the fight against a pandemic. GeoJournal . 2022; 87: 3607–3620. https://doi.org/10.1007/s10708-021-10449-8
Chevallier JJ. Systèmes d’aide à la décision à référence spatiale. INFOSIT, Ecole polytechnique fédérale de Lausanne. 1993; 2: 11-15.
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. 2021; (65). doi: 10.1016/j.scs.2020.102627
Mazri M, Chettah S. The geography of covid-19 in Algeria : in search of demographical parameters of vulnerability. Journal of Fundamental and Applied Sciences. 2021; 13(3): 1159-1174. https://doi.org/10.4314/jfas.v13i3.1
COVID-19 high risk groups: World Health Organization.2020. [Available from] https://www.who.int/westernpacific/emergencies/covid-19/information/high-risk-groups.
Galmiche S, Charmet T, Schaeffer L, Grant R, Fontanet A, Pereau J et al. Etude des facteurs sociodémographiques, comportements et pratiques associés à l’infection par le SARSCoV-2 (ComCor). Institut Pasteur; Caisse Nationale d’Assurance Maladie; IPSOS; Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP); Santé Publique France. 2021.
People who are at increased risk for severe illness : Centers for Disease Control & Prevention (CDC) ; 2020. [Available from] https: // www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-increased-risk.html.
Abrams D, Hand D, Heath A, Karlsen S, Mills M, Nazroo J, Richards et al. What factors make a community more vulnerable to COVID-19? The British Academy. 2020, London. doi.org/10.5871/bac19stf/97
Foerster E. Vulnérabilité: état de l’art sur les concepts et méthodologies d’évaluation. Rapport final, RP-57471-FR ; 2009. 32p.
White P, Pelling M, Sen K, Seddon D, Russell S, Few R. Disaster risk reduction- A developpement concern. DFID report; 2005. England, 65p.
Birkmann J. Measuring vulnerability to natural hazards. Towards disaster resilient societies: United Nations University Press; 2006.
Rose A. Economic resilience to natural and man-made disasters ;multidisciplinary origins and contextual dimensions.Environmental hazards.2007; 7(4): 383-398.
Amdaoud M, Arcuri G, Levratto N. Are regions equal in adversity? A spatial analysis of spread and dynamics of COVID-19 in Europe. Eur J Health Econ . 2021; (22): 629-642 . https://doi.org/10.1007/s10198-021-01280-6
Mollalo A, Vahedi B, Rivera KM. GIS-based spatial modeling of COVID-19 incidence rate in the continental United States. Science of the total Environment.2020; (728). https://doi.org/10.1016/j.scitotenv.2020.138884.
Xie Z, Qin Y, Li Y, Shen W, Zheng Z, Liu S. Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors. Science of The Total Environment. 2020; (744). https://doi.org/10.1016/j.scitotenv.2020.140929.
Baser O. Population density index and its use for distribution of Covid-19: A case study using Turkish data. Health Policy.2021; 125(2): 148-154. https://doi.org/10.1016/j.healthpol.2020.10.003.
Liu C, Liu Z, Guan C. The impacts of the built environment on the incidence rate of COVID-19. A case study of King County Washington. Sustainable Cities and Society. 2021; (74). https://doi.org/10.1016/j.scs.2021.103144.
Yip TL, Huang Y, Liang C. Built environment and the metropolitan pandemic: Analysis of the COVID-19 spread in Hong Kong. Build Environ. 2021; (188). doi:10.1016/j.buildenv.2020.107471.
Burridge HC, Bhagat RK, Stettler MEJ, Kumar P, De Mel I, Demis P, et al . The ventilation of buildings and other mitigating measures for COVID-19: a focus on wintertime. Proc Math Phys Eng Sci. 2021; 477. doi: 10.1098/rspa.2020.0855.
Note d'information COVID-19 et MNT. Organisation mondiale de la santé .2020. [Available from] https://www.who.int/docs/default-source/inaugural-who-partners-forum/french-covid-19-and-ncds.
Cummings MJ, Baldwin MR, Abrams D, Jacobson SD, Meyer BJ, Balough EM, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020; (395):1763-1770. doi: 10.1016/S0140-6736(20)31189-2.
Upadhyay AK, Shukla S. Correlation study to identify the factors affecting COVID-19 case fatality rates in India. Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2021; 15 (3): Pages 993-999. https://doi.org/10.1016/j.dsx.2021.04.025.
Huang C, Yang L, Pan J, Xu X, Peng R. Correlation between vaccine coverage and the COVID-19 pandemic throughout the world: based on real-world data. J Med Virol. 2022; 94: 2181- 2187. https://doi:10.1002/jmv.27609
Andersen LM, Harden SR, Sugg MM, Runkle JD, Lundquist TE. Analyzing the spatial determinants of local Covid-19 transmission in the United States. Science of The Total Environment.2021; 754. https://doi.org/10.1016/j.scitotenv.2020.142396.
Nakada L.Y.K , Urban RC. COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in São Paulo, Brazil. Environ Sci Pollut Res .2021;28: 40322–40328 . https://doi.org/10.1007/s11356-020-10930-w
Green H, Fernandez R, MacPhail C. The social determinants of health and health outcomes among adults during the COVID-19 pandemic: A systematic review. Public Health Nursing.2021; 38: 942– 952. https://doi.org/10.1111/phn.12959
Paul R, Arif A, Pokhrel K, Ghosh S. The association of social determinants of health with COVID-19 mortality in rural and urban counties. Journal of Rural Health. 2021; 37: 278– 286. https://doi.org/10.1111/jrh.12557
Qiu Y, Chen X, Shi W. Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China. Journal of Population Economics.2020;33(4): 1127 1172. https://doi.org/10.1007/s00148-020-00778-
Krejcie RV, Morgan DW. Determining Sample Size for Research Activities. Educational and Psychological Measurement.1970;30(3): 607-610. https://doi.org/10.1177/001316447003000308
Choumert-Nkolo J, Phélinas P. Nouveaux principes d’élaboration des enquêtes ménage dans les pays du Sud. Revue d'économie du développement.2018, 26 :121-151. https://doi.org/10.3917/edd.323.0121
Wilkinson R, Marmot M. Les déterminants sociaux de la santé : les faits. Organisation mondiale de la Santé. Bureau régional de l'Europe. 2004 ; 2e éd. https://apps.who.int/iris/handle/10665/107343
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