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Risk Analysis of COVID‐19 Infections in Kolkata Metropolitan City: A GIS‐Based Study and Policy Implications
GeoHealth ( IF 4.3 ) Pub Date : 2021-01-19 , DOI: 10.1029/2020gh000368
Bibhash Nath 1 , Santanu Majumder 2 , Jayanta Sen 3 , Mohammad Mahmudur Rahman 4
Affiliation  

The COVID‐19 pandemic has affected daily lives of people around the world. People have already started to live wearing masks, keeping a safe distance from others, and maintaining a high level of hygiene. This paper deals with an in‐depth analysis of riskness associated with COVID‐19 infections in Kolkata Municipal Corporation (KMC) at the subcity (ward) level. Attempts have been made to identify the areas with high or low risk of infections using GIS‐based geostatistical approach. Cosine Similarity Index has been used to rank different wards of KMC according to the degree of riskness. Four indices were computed to address intervention objectives and to determine “Optimized Prevention Rank” of wards for future policy decisions. The highest risk areas were located in the eastern and western part of the city, to a great extent overlapped with wards containing larger share of population living in slums and/or below poverty level. On the other hand, highly infected areas lie in central Kolkata and in several wards at the eastern and northeastern periphery of the KMC. The “Optimized Prevention Rank” have indicated that the lack of social awareness along with lack of social distancing have contributed to the increasing number of containments of COVID‐19 cases. The rankings of the wards would no doubt provide the policy makers a basis to control further spread of the disease. Since effective antiviral drugs are already in the market, the best application of our research would be in the ensuing vaccination drive against further COVID‐19 infections.

中文翻译:

加尔各答大都会 COVID-19 感染的风险分析:基于 GIS 的研究和政策影响

COVID-19 大流行已经影响了世界各地人们的日常生活。人们已经开始戴着口罩生活,与他人保持安全距离,并保持高水平的卫生。本文深入分析了加尔各答市政公司 (KMC) 在次城市 (病房) 级别与 COVID-19 感染相关的风险。已经尝试使用基于 GIS 的地统计方法来确定感染风险高或低的区域。余弦相似度指数已用于根据风险程度对 KMC 的不同病房进行排名。计算了四个指数来解决干预目标并确定病房的“优化预防等级”以用于未来的政策决策。风险最高的地区位于城市的东部和西部,在很大程度上与居住在贫民窟和/或贫困线以下的人口比例较大的选区重叠。另一方面,高度感染的地区位于加尔各答中部以及 KMC 东部和东北部外围的几个区。“优化预防等级”表明,缺乏社会意识以及缺乏社会距离导致了越来越多的 COVID-19 病例的遏制。病房的排名无疑将为决策者提供控制疾病进一步传播的依据。由于有效的抗病毒药物已经上市,我们研究的最佳应用将是随后的疫苗接种驱动,以防止进一步的 COVID-19 感染。高度感染的地区位于加尔各答中部以及 KMC 东部和东北部外围的几个区。“优化预防等级”表明,缺乏社会意识以及缺乏社会距离导致了越来越多的 COVID-19 病例的遏制。病房的排名无疑将为决策者提供控制疾病进一步传播的依据。由于有效的抗病毒药物已经上市,我们研究的最佳应用将是随后的疫苗接种驱动,以防止进一步的 COVID-19 感染。高度感染的地区位于加尔各答中部以及 KMC 东部和东北部外围的几个区。“优化预防等级”表明,缺乏社会意识以及缺乏社会距离导致了越来越多的 COVID-19 病例的遏制。病房的排名无疑将为决策者提供控制疾病进一步传播的依据。由于有效的抗病毒药物已经上市,我们研究的最佳应用将是随后的疫苗接种驱动,以防止进一步的 COVID-19 感染。“优化预防等级”表明,缺乏社会意识以及缺乏社会距离导致了越来越多的 COVID-19 病例的遏制。病房的排名无疑将为决策者提供控制疾病进一步传播的依据。由于有效的抗病毒药物已经上市,我们研究的最佳应用将是随后的疫苗接种驱动,以防止进一步的 COVID-19 感染。“优化预防等级”表明,缺乏社会意识以及缺乏社会距离导致了越来越多的 COVID-19 病例的遏制。病房的排名无疑将为决策者提供控制疾病进一步传播的依据。由于有效的抗病毒药物已经上市,我们研究的最佳应用将是随后的疫苗接种驱动,以防止进一步的 COVID-19 感染。
更新日期:2021-01-19
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