Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Annals of the American Association of Geographers on 05/04/2022 available online https://www.tandfonline.com/doi/full/10.1080/24694452.2021.2015281
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Spatial Associations between COVID-19 Incidence Rates and Work Sectors
T2 - Geospatial Modeling of Infection Patterns among Migrants in Oman
AU - Mansour, Shawky
AU - Abulibdeh, Ammar
AU - Alahmadi, Mohammed
AU - Al-Said, Adham
AU - Al-Said, Alkhattab
AU - Watmough, Gary
AU - Atkinson, Peter M.
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Annals of the American Association of Geographers on 05/04/2022 available online https://www.tandfonline.com/doi/full/10.1080/24694452.2021.2015281
PY - 2022/9/30
Y1 - 2022/9/30
N2 - Migrants are among the groups most vulnerable to infection with viruses due to the social and economic conditions in which they live. Therefore, spatial modeling of virus transmission among migrants is important for controlling and containing the COVID-19 pandemic. This research focused on modeling spatial associations between COVID-19 incidence rates and migrant workers. The aim was to understand the spatial relationships between COVID-19 infection rates of migrants and the type of workplace at the subnational level in Oman. Using empirical Bayes smoothing as well as local indicators of spatial associations, six work sectors (health, agriculture, retail and business, administrative, manufacturing, and mining) were investigated as risk factors for disease incidence. The results indicated that the six work sectors each had a significant spatial association with cases of COVID-19. High rates of COVID-19 cases in relation to the workplace were clustered in the densely populated areas of Muscat. Similarly, high rates of COVID-19 cases were located in the northern part of the country, along the Al-Batnah plain, where migrants are often employed in the agricultural sector. Further, the rate of COVID-19 in migrants employed in the health sector was higher than that for the other sectors. Therefore, working in the health sector can be considered a hot spot for the spread of COVID-19 infections. Due to a paucity of studies addressing the spatial analysis of COVID-19 associations with workplaces, the findings of this research are useful for decision makers to set the necessary policies and plans to control the outbreak of the virus not only in Oman or the Gulf Cooperation Council but also in other developing societies.
AB - Migrants are among the groups most vulnerable to infection with viruses due to the social and economic conditions in which they live. Therefore, spatial modeling of virus transmission among migrants is important for controlling and containing the COVID-19 pandemic. This research focused on modeling spatial associations between COVID-19 incidence rates and migrant workers. The aim was to understand the spatial relationships between COVID-19 infection rates of migrants and the type of workplace at the subnational level in Oman. Using empirical Bayes smoothing as well as local indicators of spatial associations, six work sectors (health, agriculture, retail and business, administrative, manufacturing, and mining) were investigated as risk factors for disease incidence. The results indicated that the six work sectors each had a significant spatial association with cases of COVID-19. High rates of COVID-19 cases in relation to the workplace were clustered in the densely populated areas of Muscat. Similarly, high rates of COVID-19 cases were located in the northern part of the country, along the Al-Batnah plain, where migrants are often employed in the agricultural sector. Further, the rate of COVID-19 in migrants employed in the health sector was higher than that for the other sectors. Therefore, working in the health sector can be considered a hot spot for the spread of COVID-19 infections. Due to a paucity of studies addressing the spatial analysis of COVID-19 associations with workplaces, the findings of this research are useful for decision makers to set the necessary policies and plans to control the outbreak of the virus not only in Oman or the Gulf Cooperation Council but also in other developing societies.
KW - COVID-19 incidence
KW - geospatial modeling
KW - migrants
KW - Oman
KW - work sectors
U2 - 10.1080/24694452.2021.2015281
DO - 10.1080/24694452.2021.2015281
M3 - Journal article
VL - 112
SP - 1974
EP - 1993
JO - Annals of the American Association of Geographers
JF - Annals of the American Association of Geographers
SN - 2469-4452
IS - 7
ER -