Prediction for the spread of COVID-19 in India and effectiveness of preventive measures
Prediction for the spread of COVID-19 in India and effectiveness of preventive measures
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DOI：
10.1016/j.scitotenv.2020.138762
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发表时间：
2020-08-01
影响因子：
9.8
通讯作者：
Gupta, Neeraj
中科院分区：
文献类型：
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作者：
Tomar, Anuradha;Gupta, Neeraj
COVID-19在全球的蔓延使人类面临风险。由于这种疾病的传染性和传播性很强，一些最大经济体的资源紧张。由于病例数量的不断增加及其对行政和卫生专业人员的压力，需要一些预测方法来预测未来的病例数量。在本文中，我们使用数据驱动的估计方法，如长短期记忆（LSTM）和曲线拟合，预测印度30天前的COVID-19病例数，以及社会隔离和封锁等预防措施对COVID-19传播的影响。各种参数的预测（阳性病例数、痊愈病例数等）结果表明，该方法在一定范围内具有较好的准确性，可为卫生行政部门提供参考。
The spread of COVID-19 in the whole world has put the humanity at risk. The resources of some of the largest economies are stressed out due to the large infectivity and transmissibility of this disease. Due to the growing magnitude of number of cases and its subsequent stress on the administration and health professionals, some prediction methods would be required to predict the number of cases in future. In this paper, we have used data-driven estimation methods like long short-term memory (LSTM) and curve fitting for prediction of the number of COVID-19 cases in India 30 days ahead and effect of preventive measures like social isolation and lockdown on the spread of COVID-19. The prediction of various parameters (number of positive cases, number of recovered cases, etc.) obtained by the proposed method is accurate within a certain range and will be a beneficial tool for administrators and health officials.