كليدواژه :
تحليل جغرافيايي , كوويد- 01 , كروناويروس , رويكرد تحليل اكتشافي داده هاي مكاني , ايران
چكيده فارسي :
زﻣﯿﻨﻪ و ﻫﺪف: اﺳﺘﻔﺎده از ﺗﺤﻠﯿﻞﻫﺎي ﺟﻐﺮاﻓﯿﺎﯾﯽ اﭘﯿﺪﻣﯿﻮﻟﻮژي ﮐﻮوﯾﺪ-19، ﺟﻬﺖ ﺷﻨﺎﺳﺎﯾﯽ ﻋﻮاﻣﻞ ﺟﻐﺮاﻓﯿﺎﯾﯽ ﻣﺆﺛﺮ ﺑﺮ ﺷﯿﻮع اﯾﻦ ﺑﯿﻤﺎري ﻣﯽﺗﻮاﻧﺪ ﺑﺮ ﺳﯿﺎﺳﺖ ﮔﺬارىﻫﺎى ﺑﻬﺪاﺷﺘﻰ ﺟﺎﻣﻌﻪ، ﻣﺒﻨﯽ ﺑﺮ ﮐﻨﺘﺮل روﻧﺪ ﺷﯿﻮع اﯾﻦ وﯾﺮوس ﻣﺆﺛﺮ واﻗﻊ ﺷﻮد. از اﯾﻦرو، ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﺑﻪ ﺗﺤﻠﯿﻞﺟﻐﺮاﻓﯿﺎﯾﯽ اﭘﯿﺪﻣﯿﻮﻟﻮژي
وﯾﺮوسﮐﺮوﻧﺎ در ﮐﺸﻮر ﭘﺮداﺧﺘﻪ اﺳﺖ. روشﻫﺎ: اﯾﻦ ﺗﺤﻘﯿﻖ از ﻧﻈﺮ روشﺷﻨﺎﺳﯽ، ﺗﻮﺻﯿﻔﯽ-ﺗﺤﻠﯿﻠﯽ ﺑﻮده و ﺑﺮاي ﺗﺠﺰﯾﻪوﺗﺤﻠﯿﻞ دادهﻫﺎ از ﻧﺮماﻓﺰارﻫﺎي ArcGIS و GeoDa اﺳﺘﻔﺎد ﺷﺪ. ﺟﺎﻣﻌﻪ آﻣﺎري ﺗﺤﻘﯿﻖ، ﺷﺎﻣﻞ ﺗﻌﺪاد ﻣﺒﺘﻠﺎﯾﺎن ﺑﻪ وﯾﺮوسﮐﺮوﻧﺎ )21638 ﻧﻔﺮ( در اﺳﺘﺎنﻫﺎيﮐﺸﻮر و در ﻣﺤﺪوده زﻣﺎﻧﯽ3 اﺳﻔﻨﺪ 1398 اﻟﯽ 3 ﻓﺮوردﯾﻦ 1399 اﺳﺖ. دادهﻫﺎي ﻣﺒﺘﻠﺎﯾﺎن ﺑﻪ ﮐﺮوﻧﺎ ﺑﻪ ﺗﻔﮑﯿﮏ ﻫﺮ اﺳﺘﺎن وارد ﻧﺮماﻓﺰار ArcGIS ﺷﺪ. ﺟﻬﺖ ﻧﻤﺎﯾﺶ ﭘﺮاﮐﻨﺪﮔﯽﻓﻀﺎﯾﯽ ﻣﺒﺘﻠﺎﯾﺎن ﺑﻪ ﮐﺮوﻧﺎ در ﮐﺸﻮر ﺑﺮ اﺳﺎس ﺑﺎزه زﻣﺎﻧﯽ ﻣﺬﮐﻮر از ﺗﺮاﮐﻢ ﻧﻘﻄﻪاي اﺳﺘﻔﺎده ﺷﺪ. ﺳﭙﺲ ﺑﺎ اﺳﺘﻔﺎده از ﺿﺮﯾﺐ ﻣﻮران ﭘﺮاﮐﻨﺶ ﻓﻀﺎﯾﯽ آن ﺑﺮرﺳﯽ ﺷﺪ. ﻫﻤﭽﻨﯿﻦ ﺑﺎ اﺳﺘﻔﺎده از ﺧﻮدﻫﻤﺒﺴﺘﮕﯽﻓﻀﺎﯾﯽ ﻣﯿﺰان ﻓﺎﺻﻠﻪ ﮔﺴﺘﺮش ﺷﯿﻮع وﯾﺮوسﮐﺮوﻧﺎ در ﺑﯿﻦ اﺳﺘﺎنﻫﺎيﮐﺸﻮر ﺗﺤﻠﯿﻞ ﺷﺪ. در ﻧﻬﺎﯾﺖ ﺑﺎ اﺳﺘﻔﺎده از ﺷﺎﺧﺺ ﻣﺤﻠﯽ ﭘﯿﻮﻧﺪ ﻓﻀﺎﯾﯽ ﻣﻮران ﺗﮏ ﻣﺘﻐﯿﺮه،
ﺧﻮﺷﻪﺑﻨﺪي ﻓﻀﺎﯾﯽ اﺳﺘﺎنﻫﺎي ﮐﺸﻮر ﺑﺮ اﺳﺎس وﯾﺮوسﮐﺮوﻧﺎ ﺻﻮرت ﮔﺮﻓﺖ. ﯾﺎﻓﺘﻪﻫﺎ: آﻣﺎرﻫﺎ ﺣﺎﮐﯽ از آن اﺳﺖ ﮐﻪ ﮔﺮوه ﺳﻨﯽ 50-21 ﺳﺎل، ﺑﯿﺸﺘﺮﯾﻦ درﺻﺪ ﻣﺒﺘﻠﺎﯾﺎن ﺑﻪ وﯾﺮوسﮐﺮوﻧﺎ را ﺗﺸﮑﯿﻞ ﻣﯽدﻫﻨﺪ. ﻧﺘﺎﯾﺞ ﺣﺎﺻﻞ از ﺗﺤﻘﯿﻖ ﻧﺸﺎن داد ﮐﻪ ﻣﻬﻤﺘﺮﯾﻦ ﻋﺎﻣﻞ اﻧﺘﺸﺎر ﻓﻀﺎﯾﯽ وﯾﺮوسﮐﺮوﻧﺎ در ﮐﺸﻮر، ﻓﺎﺻﻠﻪ و ﻣﺠﺎورت ﻣﮑﺎﻧﯽ اﺳﺘﺎنﻫﺎي درﮔﯿﺮ ﺑﺎ اﯾﻦ ﺑﯿﻤﺎري اﺳﺖ ﺑﻄﻮرﯾﮑﻪ در ﻓﺎﺻﻠﻪ 383/8 ﮐﯿﻠﻮﻣﺘﺮي ﺑﯿﻦ اﺳﺘﺎنﻫﺎيﮐﺸﻮر ﺿﺮﯾﺐ ﻣﻮران 0/136627 ﻣﯽﺑﺎﺷﺪ و ﻧﺸﺎندﻫﻨﺪه ﺧﻮدﻫﻤﺒﺴﺘﮕﯽ ﻣﮑﺎﻧﯽ ﻣﺜﺒﺖ اﺳﺖ. در ﻓﺎﺻﻠﻪ 762/6 ﮐﯿﻠﻮﻣﺘﺮي ﺑﯿﻦ اﺳﺘﺎنﻫﺎ ﺿﺮﯾﺐﻣﻮران ﺑﺮاﺑﺮ 0/040246- اﺳﺖ ﮐﻪ ﻧﺸﺎندﻫﻨﺪه ﺧﻮدﻫﻤﺒﺴﺘﮕﯽ ﻣﮑﺎﻧﯽ ﻣﻨﻔﯽ ﺑﻮده ﺑﺪﯾﻦ ﻣﻌﻨﯽ ﮐﻪ از اﯾﻦ ﻓﺎﺻﻠﻪ ﺑﻪ ﺑﻌﺪ از ﺗﻌﺪاد ﻣﺒﺘﻠﺎﯾﺎن ﺑﻪ ﮐﺮوﻧﺎ ﮐﺎﺳﺘﻪ ﻣﯽﺷﻮد. در ﺧﻮﺷﻪﺑﻨﺪي ﻓﻀﺎﯾﯽ، ﺧﻮﺷﻪ HH ﺷﺎﻣﻞ اﺳﺘﺎنﻫﺎي )ﺗﻬﺮان، اﻟﺒﺮز، ﻗﻢ، ﻣﺎزﻧﺪران، ﮔﯿﻠﺎن، ﻗﺰوﯾﻦ، اﺻﻔﻬﺎن، ﺳﻤﻨﺎن، ﻣﺮﮐﺰي و ﯾﺰد( ﺑﻪ ﻋﻨﻮان ﮐﺎﻧﻮن اﺻﻠﯽ اﻧﺘﺸﺎرﻓﻀﺎﯾﯽ اﭘﯿﺪﻣﯽ وﯾﺮوسﮐﺮوﻧﺎ ﺷﻨﺎﺧﺘﻪ ﻣﯽﺷﻮﻧﺪ ﮐﻪ ﺑﺎﯾﺪ ﺑﺮاي ﮐﻨﺘﺮل و ﮐﺎﻫﺶ ﺷﯿﻮع اﯾﻦ وﯾﺮوس در ﮐﺸﻮر ﺗﻤﻬﯿﺪات و ﻣﺤﺪودﯾﺖﻫﺎﯾﯽ در زﻣﯿﻨﻪ ﻋﺒﻮر و ﻣﺮور ﺑﯿﻦ اﺳﺘﺎنﻫﺎي واﻗﻊ در اﯾﻦ ﺧﻮﺷﻪ و ﺳﺎﯾﺮ اﺳﺘﺎنﻫﺎ اﻋﻤﺎل ﺷﻮد. ﻫﻤﭽﻨﯿﻦ ﺧﻮﺷﻪ LH )ﺷﺎﻣﻞ اﺳﺘﺎنﻫﺎي ﮔﻠﺴﺘﺎن، ﺧﺮاﺳﺎن رﺿﻮي، ﺧﺮاﺳﺎن ﺷﻤﺎﻟﯽ، اردﺑﯿﻞ و ﻫﻤﺪان( ﺑﻪ ﻋﻨﻮان ﺣﻠﻘﮥ ﭘﯿﺮاﻣﻮنﮐﺎﻧﻮنآﺳﯿﺐ ﻣﯽﺑﺎﺷﻨﺪ ﮐﻪ ﺑﻪ ﻟﺤﺎظ ﺗﻌﺎﻣﻞﻓﻀﺎﯾﯽ و ﻣﺠﺎورت ﺑﺎ ﺧﻮﺷﻪ HH ﺑﺎﯾﺪ ﮐﻨﺘﺮلﻫﺎي ﺟﺪي در زﻣﯿﻨﻪ ﻣﻤﻨﻮﻋﯿﺖ رﻓﺖوآﻣﺪ ﺑﻪ آﻧﻬﺎ ﺻﻮرت ﺑﮕﯿﺮد ﺗﺎ از اداﻣﻪ ﮔﺴﺘﺮش ﺷﯿﻮع وﯾﺮوسﮐﺮوﻧﺎ ﺑﻪ اﺳﺘﺎنﻫﺎي واﻗﻊ در ﺧﻮﺷﻪ LH ﺟﻠﻮﮔﯿﺮي
ﺷﻮد. ﻧﺘﯿﺠﻪﮔﯿﺮي: از ﻣﻬﻤﺘﺮﯾﻦ ﻋﻮاﻣﻞ ﺟﻐﺮاﻓﯿﺎﯾﯽ ﻣﺆﺛﺮ ﺑﺮ ﺷﯿﻮع وﯾﺮوسﮐﺮوﻧﺎ ﺑﺮاﺳﺎس ﻧﻈﺮﯾﻪ ﭘﺨﺶ ﻓﻀﺎﯾﯽ، ﻓﺎﺻﻠﻪ و ﻣﺠﺎورت ﻣﮑﺎﻧﯽ ﻣﯽﺑﺎﺷﺪ ﮐﻪ ﻣﺴﺌﻮﻟﺎن و ﺑﺮﻧﺎﻣﻪرﯾﺰان ﺑﺎﯾﺪ ﺑﺎ ﻫﻮﺷﻤﻨﺪﺳﺎزي از ﻣﺮاﺟﻌﻪ اﻓﺮاد ﺑﻪ ادارات و ﺳﺎزﻣﺎنﻫﺎ ﮐﺎﺳﺘﻪ و ﺑﺎ ﻓﺮاﻫﻢ ﻧﻤﻮدن زﻣﯿﻨﻪ دورﮐﺎري، از اداﻣﻪ روﻧﺪ ﺻﻌﻮدي ﺷﯿﻮع وﯾﺮوسﮐﺮوﻧﺎ در ﮐﺸﻮر ﺟﻠﻮﮔﯿﺮي ﻧﻤﺎﯾﻨﺪ.
چكيده لاتين :
Background and Aim: The use of geophysical analysis of the epidemiology to identify geographical factors affecting the prevalence of the disease can be effective on community health policies to control the prevalence of the virus. Therefore, the present study is a geographical analysis of the COVID-19 epidemiology in Iran.
Therefore, the purpose of this study is the geographical analysis of coronavirus transmission in the country.
Methods: This is a descriptive-analytical study and ArcGIS and GeoDa software has been used to analyze the data. The statistical population included the total number of people infected with COVID-19 (n=21638) in Iran during February 22, 2020, and March 22, 2020. Data entered ArcGIS software by each province. In order to show the spatial distribution of COVID-19 patients in Iran, point density has been used based on the mentioned time period. Then, by using the Moran coefficient, its spatial distribution was examined. Also, by using spatial correlation, the distance between the spread of coronavirus in all provinces of Iran was analyzed. Finally, by using the local index of the single-variable Moran spatial bond, the spatial clustering of the countrychr('39')s provinces was calculated based on the coronavirus.
Results: Statistics show that the age group of 21-50 years is the highest percentage of people infected with COVID-19. The results showed that the most important factor in the spatial spread of coronavirus in Iran is the distance and proximity of the provinces affected by this disease so that at a distance of 383.8 km between the provinces, the Moran coefficient is 0.66627 and shows a positive spatial correlation. It is located at a distance of 762.6 km between the provinces and the Moran coefficient is -0.040246, which indicates a negative spatial correlation, which means that this distance decreases after the number of people with COVID-19. In spatial clustering, HH clusters including provinces (Tehran, Alborz, Qom, Mazandaran, Gilan, Qazvin, Isfahan, Semnan, Markazi and Yazd) are known as the main spatial propagation centers of the Coronavirus epidemic, which should be controlled and reduced. Also, LH clusters (including Golestan, Khorasan Razavi, North Khorasan, Ardabil and Hamedan provinces) are the ring around the center of damage, which should be controlled in terms of spatial interaction and proximity to HH clusters. Serious travel bans should be put in place to prevent the spread of coronavirus to the provinces in the LH cluster.
Conclusion: One of the most important geographical factors affecting the prevalence of coronavirus is based on spatial distribution theory, distance and spatial proximity. Officials and planners should intelligently reduce the number of people visiting offices and organizations, and by providing telecommuting, to prevent the upward trend of the outbreak of coronavirus in Iran.
