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Adham Al-Said

Biographic Data

ID2064459
NAMEAdham Al-Said
GIVEN NAMESAdham
FAMILY NAMEAl-Said
SIGNATUREAL-SAID A
AFFILIATIONSSultan Qaboos University
VERIFIEDNo
TOTAL WORKS2
TOTAL CITATIONS2
AUTHOR COUNT2
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2022
H-INDEX1
  • Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman

    Shawky Mansour, Ammar Abulibdeh et al.•ARTICLE•Annals of the American…•2022•Cited by: 2•References: 53

    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 infect…

  • Sociodemographic determinants of Covid-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)

    Open Access•Shawky Mansour, Abdullah Al Kindi et al.•ARTICLE•Sustainable Cities and Society•2021

  • Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman

    Shawky Mansour, Ammar Abulibdeh et al.•ARTICLE•Annals of the American…•2022•Cited by: 2•References: 53

    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 infect…

  • Sociodemographic determinants of Covid-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)

    Open Access•Shawky Mansour, Abdullah Al Kindi et al.•ARTICLE•Sustainable Cities and Society•2021

  • Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman

    Shawky Mansour, Ammar Abulibdeh et al.•ARTICLE•Annals of the American…•2022•Cited by: 2•References: 53

    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 infect…

Cartography (2 works) · COVID-19 epidemiological studies (2 works) · COVID-19 impact on air quality (2 works) · COVID-19 Pandemic Impacts (2 works) · Demography (2 works) · Disease (2 works) · Environmental health (2 works) · Geography (2 works) · Geospatial analysis (2 works) · Medicine (2 works)

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