Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province)
To examine the spatial relationships of the number of patients, effective factors in increasing the number of patients should be determined. The information layers of dependent variables and independent variables were plotted in the GIS system. In the next stage, ordinary least squares regression an...
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Shahid Beheshti University
2023-07-01
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| Series: | Sustainable Earth Trends |
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| Online Access: | https://sustainearth.sbu.ac.ir/article_104247_f6f0b613e593cfcdda7c7e6609d59175.pdf |
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| author | Ghasem Keikhosravi Seyedeh Fatemeh Fadavi |
| author_facet | Ghasem Keikhosravi Seyedeh Fatemeh Fadavi |
| author_sort | Ghasem Keikhosravi |
| collection | DOAJ |
| description | To examine the spatial relationships of the number of patients, effective factors in increasing the number of patients should be determined. The information layers of dependent variables and independent variables were plotted in the GIS system. In the next stage, ordinary least squares regression and the Moran spatial correlation test were used to investigate the significant relationship between the dependent variable and each of the explanatory variables. The results show that the most influential variables in increasing the number of patients are in the first place the urban working population variable and in the second and third place the total population and total working population. The average variable of ambient temperature along with the mentioned variables is an important factor in the release of Covid-19. In the study of the average ambient temperature in three periods, it was found that the number of patients increased with decreasing temperature. Hence, to vaccinate the target groups, it is recommended to vaccinate the urban working population in the first stage, and also the observance of health protocols is strongly recommended in areas where the average ambient temperature is lower. |
| format | Article |
| id | doaj-art-70c5ab3fa1bf4a2897b2c751d73d4218 |
| institution | OA Journals |
| issn | 3060-6225 |
| language | English |
| publishDate | 2023-07-01 |
| publisher | Shahid Beheshti University |
| record_format | Article |
| series | Sustainable Earth Trends |
| spelling | doaj-art-70c5ab3fa1bf4a2897b2c751d73d42182025-08-20T02:36:12ZengShahid Beheshti UniversitySustainable Earth Trends3060-62252023-07-0133172610.48308/ser.2024.233701.1023104247Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province)Ghasem Keikhosravi0Seyedeh Fatemeh Fadavi1Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti, Tehran, IranLaboratory expert, Shahid Beheshti University, Tehran, IranTo examine the spatial relationships of the number of patients, effective factors in increasing the number of patients should be determined. The information layers of dependent variables and independent variables were plotted in the GIS system. In the next stage, ordinary least squares regression and the Moran spatial correlation test were used to investigate the significant relationship between the dependent variable and each of the explanatory variables. The results show that the most influential variables in increasing the number of patients are in the first place the urban working population variable and in the second and third place the total population and total working population. The average variable of ambient temperature along with the mentioned variables is an important factor in the release of Covid-19. In the study of the average ambient temperature in three periods, it was found that the number of patients increased with decreasing temperature. Hence, to vaccinate the target groups, it is recommended to vaccinate the urban working population in the first stage, and also the observance of health protocols is strongly recommended in areas where the average ambient temperature is lower.https://sustainearth.sbu.ac.ir/article_104247_f6f0b613e593cfcdda7c7e6609d59175.pdfcovid-19dependent and independent variableordinary least squares regressionmoran indexp_value |
| spellingShingle | Ghasem Keikhosravi Seyedeh Fatemeh Fadavi Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) Sustainable Earth Trends covid-19 dependent and independent variable ordinary least squares regression moran index p_value |
| title | Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) |
| title_full | Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) |
| title_fullStr | Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) |
| title_full_unstemmed | Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) |
| title_short | Study on the Spatial Relationships in the Number of Covid-19 Patients based on Ordinary Least Squares Regression and Moran's Spatial Autocorrelation Test Case study (Iran, Lorestan Province) |
| title_sort | study on the spatial relationships in the number of covid 19 patients based on ordinary least squares regression and moran s spatial autocorrelation test case study iran lorestan province |
| topic | covid-19 dependent and independent variable ordinary least squares regression moran index p_value |
| url | https://sustainearth.sbu.ac.ir/article_104247_f6f0b613e593cfcdda7c7e6609d59175.pdf |
| work_keys_str_mv | AT ghasemkeikhosravi studyonthespatialrelationshipsinthenumberofcovid19patientsbasedonordinaryleastsquaresregressionandmoransspatialautocorrelationtestcasestudyiranlorestanprovince AT seyedehfatemehfadavi studyonthespatialrelationshipsinthenumberofcovid19patientsbasedonordinaryleastsquaresregressionandmoransspatialautocorrelationtestcasestudyiranlorestanprovince |