A Moran’s I autocorrelation and spatial cluster analysis for identifying Coronavirus disease COVID-19 in Iraq using GIS approach

Document Type : Research Paper

Authors

1 Ministry of Education, Najaf Education Office, Najaf, Iraq

2 Basic Science Department, College of Dentistry, University of Kufa, Kufa, Najaf, Iraq

3 Physics Department, Faculty of Science, University of Kufa, Najaf, Iraq

Abstract

Iraq is one of the states in the world, affected with coronavirus. Mapping spatial patterns analysis distribution of disease incidence and danger can be assist as a suitable tool for detecting exposures of public health concern. A geographical information system (GIS)-based methodology to examine the relationship between the reported incidence of coronavirus and spatial patterns analysis in eighteen provinces of Iraq was analyzed in 2020. So, the study was applying spatial statistics to inspect the spatial patterns and areas of clustering detection to describe the pattern of coronavirus in Iraq. In this study, local Moran's I has been applied to measure spatial distribution of coronavirus in the study area and examined how provinces were spread or clustered. Spatial patterns statistics were used to apply Moran’s I test and it estimated considerable negative spatial autocorrelation of coronavirus disease incidences from 24/02/2020 to 06/04/2020. The results described spatially random clustered and spatial pattern of this disease in the study area. The study determined that the coronavirus cases were increased in the northeastern- and southwestern-side provinces of Iraq.

Keywords

References

Albrecht, J 2007, Key concepts and techniques in GIS. Sage Publications, 101 p.
Algert, SJ, Agrawal, A & Lewis, DS 2006, Disparities in access to fresh produce in low-income neighborhoods in Los Angeles. American Journal of Preventive Medicine, 30: 365-370.
Al-Kindi, KM, Alkharusi, A, Alshukaili, D, Al Nasiri, N, Al-Awadhi, T, Charabi, Y, & El Kenawy, AM 2020, Spatiotemporal sssessment of COVID-19 spread over Oman using GIS techniques. Earth Systems and Environment, 4: 797-811.
Anselin, L 1995, Local indicators of spatial association-LISA. Geographical Analysis, 27: 93-115.
Apparicio, P, Cloutier, MS & Shearmur, R 2007, The case of Montreal's missing food deserts: Evaluation of accessibility to food supermarkets. International Journal of Health Geographics, 6: 1-13.
Bendaif, H, Hammouti, B, Stiane, I, Bendaif, Y, El Ouadi, MA & El Ouadi, Y 2020, Investigation of spread of novel coronavirus (COVID-19) pandemic in MOROCCO & estimated confinement duration to overcome the danger phase. Caspian Journal of Environmental Sciences, 18: 149-156.
Biswas, K, Khaleque, A & Sen, P 2020, Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network. arXiv preprint arXiv:2003.07063.
Boulos, MN & Geraghty, EM 2020, Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: How 21st Century GIS technologies are supporting the global fight against outbreaks and epidemics. BioMed Central.
Briggs, DJ & Elliott, P 1995, The use of geographical information systems in studies on environment and health. World health statistics quarterly. Rapport Trimestriel de Statistiques Sanitaires Mondiales, 48: 85-94.
Chaput, EK, Meek, JI & Heimer, R 2002, Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. Emerging Infectious Diseases, 8: 943.
Danon, L, Brooks-Pollock, E, Bailey, M & Keeling, MJ 2020, A spatial model of CoVID-19 transmission in England and Wales: Early spread and peak timing. MedRxiv.
Getis, A 1996, Local spatial statistics: An overview. Spatial analysis: Modelling in a GIS environment. pp. 261-277.
Kang, L, Li, Y, Hu, S, Chen, M, Yang, C, Yang, BX et al. 2020, The mental health of medical workers in Wuhan, China dealing with the 2019 novel coronavirus. The Lancet Psychiatry. Mar;7(3):e14. DOI: 10.1016/S2215-0366(20)30047-X.
Maliki, I, Elmsellem, H, Hafez, B, EL Moussaoui, A, Reda Kachmar, M & Ouahbi, A 2020, The psychological properties of the Arabic BDI-II and the psychological state of the general Moroccan population during the mandatory quarantine due to the COVID-19 pandemic. Caspian Journal of Environmental Sciences, pp. 111-122.
Miller, HJ 2004, Tobler's first law and spatial analysis. Annals of the Association of American Geographers, 94: 284-289.
Moran, PA 1948, The interpretation of statistical maps. Journal of the Royal Statistical Society: Series B (Methodological), 10: 243-251.
Moran, PA 1950, Notes on continuous stochastic phenomena. Biometrika, 37: 17-23.
Murgante, B & Borruso, G 2012, Analyzing migration phenomena with spatial autocorrelation techniques. International Conference on Computational Science and Its Applications, pp. 670-685.
Novel, CP et al. 2020, The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua liu xing bing xue za zhi= Zhonghua liuxingbingxue zazhi, 41, 145.
Organization, WH et al. 2005, Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV).
Pathirana, S, Kawabata, M & Goonatilake, R 2009, Study of potential risk of dengue disease outbreak in Sri Lanka using GIS and statistical modelling. Journal of Rural and Tropical Public Health, 8: 8-17.
Sarwar, S, Waheed, R, Sarwar, S & Khan, A 2020, COVID-19 challenges to Pakistan: Is GIS analysis useful to draw solutions? Science of the Total Environment, 730: 139089.
Serra-Sogas, N, O’Hara, P, Canessa, R, Bertazzon, S & Gavrilova, M 2008, Exploratory spatial analysis of illegal oil discharges detected off Canada’s Pacific Coast. International Conference on Computational Science and Its Applications, pp. 81-95.
Sithiprasasna, R, Patpoparn, S, Attatippaholkun, W, Suvannadabba, S & Srisuphanunt, M 2004, The geographic information system as an epidemiological tool in the surveillance of dengue virus-infected Aedes mosquitos.
Talen, E & Anselin, L 1998, Assessing spatial equity: an evaluation of measures of accessibility to public playgrounds. Environment and Planning A, 30: 595-613.
Tsou, KW, Hung, YT & Chang, YL 2005, An accessibility-based integrated measure of relative spatial equity in urban public facilities. Cities, 22: 424-435.
Vine, MF, Degnan, D & Hanchette, C 1997, Geographic information systems: Their use in environmental epidemiologic research. Environmental Health Perspectives, 105: 598-605.
Wang, D, Hu, B, Hu, C, Zhu, F, Liu, X, Zhang, J et al. 2020, Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. Jama, 323: 1061-1069.
Zhou, P, Yang, XL, Wang, XG, Hu, B, Zhang, L, Zhang, W et al. 2020, A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579: 270-273.
Caspian Journal of Environmental Sciences
Volume 20, Issue 1
January 2022
Pages 55-60

Files

Share

How to cite

Statistics