Alkhattab Al-Said
Biographic Data
| ID | 3635978 |
|---|---|
| NAME | Alkhattab Al-Said |
| GIVEN NAMES | Alkhattab |
| FAMILY NAME | Al-Said |
| SIGNATURE | AL-SAID A |
| AFFILIATIONS | Sultan Qaboos University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman
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)
Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman
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)
Spatial Associations between Covid-19 Incidence Rates and Work Sectors: Geospatial Modeling of Infection Patterns among Migrants in Oman
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)