Measuring of the COVID-19 Based on Time-Geography

At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are r...
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Gespeichert in:

Autor*in:	Zhangcai Yin [verfasserIn] Wei Huang [verfasserIn] Shen Ying [verfasserIn] Panli Tang [verfasserIn] Ziqiang Kang [verfasserIn] Kuan Huang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	time geography COVID-19 space-time prism space-time path

Übergeordnetes Werk:	In: International Journal of Environmental Research and Public Health - MDPI AG, 2005, 18(2021), 10313, p 10313
Übergeordnetes Werk:	volume:18 ; year:2021 ; number:10313, p 10313

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.3390/ijerph181910313

Katalog-ID:	DOAJ054553059

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allfields	10.3390/ijerph181910313 doi (DE-627)DOAJ054553059 (DE-599)DOAJ89f6e17e0cb547f4bb33f1dc7e7677e2 DE-627 ger DE-627 rakwb eng Zhangcai Yin verfasserin aut Measuring of the COVID-19 Based on Time-Geography 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy. time geography COVID-19 space-time prism space-time path Medicine R Wei Huang verfasserin aut Shen Ying verfasserin aut Panli Tang verfasserin aut Ziqiang Kang verfasserin aut Kuan Huang verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 10313, p 10313 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:10313, p 10313 https://doi.org/10.3390/ijerph181910313 kostenfrei https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 kostenfrei https://www.mdpi.com/1660-4601/18/19/10313 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 10313, p 10313
spelling	10.3390/ijerph181910313 doi (DE-627)DOAJ054553059 (DE-599)DOAJ89f6e17e0cb547f4bb33f1dc7e7677e2 DE-627 ger DE-627 rakwb eng Zhangcai Yin verfasserin aut Measuring of the COVID-19 Based on Time-Geography 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy. time geography COVID-19 space-time prism space-time path Medicine R Wei Huang verfasserin aut Shen Ying verfasserin aut Panli Tang verfasserin aut Ziqiang Kang verfasserin aut Kuan Huang verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 10313, p 10313 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:10313, p 10313 https://doi.org/10.3390/ijerph181910313 kostenfrei https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 kostenfrei https://www.mdpi.com/1660-4601/18/19/10313 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 10313, p 10313
allfields_unstemmed	10.3390/ijerph181910313 doi (DE-627)DOAJ054553059 (DE-599)DOAJ89f6e17e0cb547f4bb33f1dc7e7677e2 DE-627 ger DE-627 rakwb eng Zhangcai Yin verfasserin aut Measuring of the COVID-19 Based on Time-Geography 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy. time geography COVID-19 space-time prism space-time path Medicine R Wei Huang verfasserin aut Shen Ying verfasserin aut Panli Tang verfasserin aut Ziqiang Kang verfasserin aut Kuan Huang verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 10313, p 10313 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:10313, p 10313 https://doi.org/10.3390/ijerph181910313 kostenfrei https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 kostenfrei https://www.mdpi.com/1660-4601/18/19/10313 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 10313, p 10313
allfieldsGer	10.3390/ijerph181910313 doi (DE-627)DOAJ054553059 (DE-599)DOAJ89f6e17e0cb547f4bb33f1dc7e7677e2 DE-627 ger DE-627 rakwb eng Zhangcai Yin verfasserin aut Measuring of the COVID-19 Based on Time-Geography 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy. time geography COVID-19 space-time prism space-time path Medicine R Wei Huang verfasserin aut Shen Ying verfasserin aut Panli Tang verfasserin aut Ziqiang Kang verfasserin aut Kuan Huang verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 10313, p 10313 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:10313, p 10313 https://doi.org/10.3390/ijerph181910313 kostenfrei https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 kostenfrei https://www.mdpi.com/1660-4601/18/19/10313 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 10313, p 10313
allfieldsSound	10.3390/ijerph181910313 doi (DE-627)DOAJ054553059 (DE-599)DOAJ89f6e17e0cb547f4bb33f1dc7e7677e2 DE-627 ger DE-627 rakwb eng Zhangcai Yin verfasserin aut Measuring of the COVID-19 Based on Time-Geography 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy. time geography COVID-19 space-time prism space-time path Medicine R Wei Huang verfasserin aut Shen Ying verfasserin aut Panli Tang verfasserin aut Ziqiang Kang verfasserin aut Kuan Huang verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 10313, p 10313 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:10313, p 10313 https://doi.org/10.3390/ijerph181910313 kostenfrei https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 kostenfrei https://www.mdpi.com/1660-4601/18/19/10313 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 10313, p 10313
language	English
source	In International Journal of Environmental Research and Public Health 18(2021), 10313, p 10313 volume:18 year:2021 number:10313, p 10313
sourceStr	In International Journal of Environmental Research and Public Health 18(2021), 10313, p 10313 volume:18 year:2021 number:10313, p 10313
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authorswithroles_txt_mv	Zhangcai Yin @@aut@@ Wei Huang @@aut@@ Shen Ying @@aut@@ Panli Tang @@aut@@ Ziqiang Kang @@aut@@ Kuan Huang @@aut@@
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spellingShingle	Zhangcai Yin misc time geography misc COVID-19 misc space-time prism misc space-time path misc Medicine misc R Measuring of the COVID-19 Based on Time-Geography
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title	Measuring of the COVID-19 Based on Time-Geography
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title_full	Measuring of the COVID-19 Based on Time-Geography
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title_sort	measuring of the covid-19 based on time-geography
title_auth	Measuring of the COVID-19 Based on Time-Geography
abstract	At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.
abstractGer	At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.
abstract_unstemmed	At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.
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title_short	Measuring of the COVID-19 Based on Time-Geography
url	https://doi.org/10.3390/ijerph181910313 https://doaj.org/article/89f6e17e0cb547f4bb33f1dc7e7677e2 https://www.mdpi.com/1660-4601/18/19/10313 https://doaj.org/toc/1661-7827 https://doaj.org/toc/1660-4601
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author2	Wei Huang Shen Ying Panli Tang Ziqiang Kang Kuan Huang
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up_date	2024-07-03T23:39:02.051Z
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