外来劳动力流入对奥里萨邦新冠肺炎早期传播的影响:个案研究

IF 1.2 Q4 REMOTE SENSING ACM Transactions on Spatial Algorithms and Systems Pub Date : 2022-08-23 DOI:10.1145/3558778
S. Behera, D. P. Dogra, M. Satpathy
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引用次数: 2

摘要

奥里萨邦是印度东部的一个邦,人口4600万。每年都有大量的人移民到其他州的金融和工业中心谋生。由于新冠肺炎疫情,他们中的大部分人在全国封锁的早期阶段(2020年3月至6月)返回奥迪沙,因为他们的工作场所成为新冠肺炎热点,而奥迪沙受到的影响要小得多。这促使奥里萨邦政府采取预防措施,如对返回的移民进行强制隔离、设立隔离区和建立临时医疗中心(TMC)。此外,政府有必要制定一项政策,以减缓由于移民流入而导致的新冠肺炎在奥迪沙的传播。作为政府为了解新冠肺炎在奥迪沙的传播动态而成立的工作组的一部分,我们预测了主要由于反向传播而感染的人数。这有助于政府及时调动资源。在分析了流动人口众多的各个地区感染率上升的原因后,我们将预测问题映射到Abraham Wald的序列概率比检验(SPRT)中。与后期获得的真实数据相比,我们的预测非常准确。对政府提供的数据进行了两级SPRT。将SPRT用于新冠肺炎传播分析是一种新颖的方法,特别是预测由于移民的突然流入而可能提前的感染人数。
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Effect of Migrant Labourer Inflow on the Early Spread of Covid-19 in Odisha: A Case Study
Odisha is a state in the eastern part of India with a population of 46 million. Annually, a large number of people migrate to financial and industrial centers in other states for their livelihood earning. Bulk of them returned to Odisha during the early stage of national lockdown (March–June 2020) due to the Covid-19 outbreak as their places of work became Covid hotspots while Odisha was much less affected. This triggered the Odisha government to take precautionary measures such as mandatory quarantine of returning migrants, setting up of containment zones, and establishing temporary medical centres (TMC). Moreover, it was necessary for the government to devise a policy that could slow down the spread of Covid-19 in Odisha due to inflow of migrants. Being part of a task-force constituted by government to understand Covid-19 spread dynamics in Odisha, we predicted the number of people who would get infected primarily due to reverse-migration. This helped the government to make timely resource mobilisation. After analyzing reasons behind the rise in infections at various districts with large migrant population, we mapped the prediction problem to Sequential Probability Ratio Test (SPRT) of Abraham Wald. Our predictions were highly accurate when compared with real data that were obtained at a later stage. Two levels of SPRT were carried out over the data provided by the government. Use of SPRT for Covid-19 spread analysis is novel, particularly to predict the number of possible infections much ahead in time due to the sudden inflow of migrants.
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来源期刊
CiteScore
4.40
自引率
5.30%
发文量
43
期刊介绍: ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.
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