Geospatial Analysis of COVID-19 Death Rate and Influencing Factors in the MENA Region
The COVID-19 pandemic has significantly impacted the Middle East and North Africa (MENA) region, with over twenty-eight million cases and 800,000 deaths reported as of August 2023. Spatial analysis can help identify factors associated with the high death toll and develop targeted interventions to r...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Tehran University of Medical Sciences
2024-09-01
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| Series: | Journal of Biostatistics and Epidemiology |
| Subjects: | |
| Online Access: | https://jbe.tums.ac.ir/index.php/jbe/article/view/1339 |
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| Summary: | The COVID-19 pandemic has significantly impacted the Middle East and North Africa (MENA) region, with over twenty-eight million cases and 800,000 deaths reported as of August 2023. Spatial analysis can help identify factors associated with the high death toll and develop targeted interventions to reduce the virus's spread and improve health outcomes. The study uses GIS-based analysis and geostatistical models to analyze the COVID-19 death rate in MENA countries. It identifies demographic, medical, and socioeconomic factors as key factors. The research suggests that hospital bed allocation, unemployment rate, and overall immunizations could be key factors influencing the death rate. The study also highlights the fragility of healthcare infrastructure in developing nations, with poor allocation and insufficient support for vulnerable groups. The findings suggest a positive correlation between death rate, hospital bed allocation, unemployment rate, and vaccination doses, highlighting the importance of social isolation measures. The estimated OLS model, which considers variables like hospital beds, unemployment rate, and total vaccine doses, was found to explain 73.46% of COVID-19 death cases across the Middle East and Africa (MENA). However, the model's spatial autocorrelation was found, requiring the development of spatial lag regression (SLM) and spatial error regression (SEM) models. The geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) models showed higher and lower AIC than global models, with the GWR model showing a clear pattern of impact in the northwestern area and the MGWR model showing a moderate impact in the northwestern area. Understanding COVID-19 death incidence is crucial for controlling transmission. This work could be valuable in future studies.
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| ISSN: | 2383-4196 2383-420X |