论文标题
南亚的Covid-19：实时监测复制和病例死亡率
COVID-19 in South Asia: Real-time monitoring of reproduction and case fatality rate
论文作者
论文摘要
随着COVID-19引起的大流行造成的破坏在每时每刻都变得不可避免，监测和理解传播和死亡率对于包含其传播的范围变得更加重要。该分析的关键目的是报告南亚地区Covid-19的实时有效繁殖率（$ r_t $）和病例死亡率（CFR）。这项研究的数据始于截至2020年7月31日的JHU CSSE COVID-19数据源。$ r_t $是使用指数增长和时间依赖性方法估算的。通过安装现有的流行病曲线，使用R-Lan语言中的R0软件包来估计$ R_T $。病例死亡率是通过使用幼稚和卡普兰 - 同位方法来估计的。由于COVID-19案件的指数增长，大流行将在印度，马尔代夫和尼泊尔随之而来，因为这些国家估计$ r_T $估计要大于1。尽管与世界上其他受影响的地区相比，发现病例死亡率较小，但强调对更好的医疗机构和患者护理的严格监测。更具区域层面的合作和努力是需要时间来最大程度地减少病毒的有害影响。
As the ravages caused by COVID-19 pandemic are becoming inevitable with every moment, monitoring and understanding of transmission and fatality rate has become even more paramount for containing its spread. The key purpose of this analysis is to report the real-time effective reproduction rate ($R_t$ ) and case fatality rates (CFR) of COVID-19 in South Asia region. Data for this study are extracted from JHU CSSE COVID-19 Data source up to July 31, 2020. $R_t$ is estimated using exponential growth and time-dependent methods. R0 package in R-language is employed to estimate $R_t$ by fitting the existing epidemic curve. Case fatality rate is estimated by using Naive and Kaplan-Meier methods. Owing to exponential increase in cases of COVID-19, the pandemic will ensue in India, Maldives and in Nepal as $R_t$ was estimated greater than 1 for these countries. Although case fatality rates are found lesser as compared to other highly affected regions in the world, strict monitoring of deaths for better health facilities and care of patients is emphasized. More regional level cooperation and efforts are the need of time to minimize the detrimental effects of the virus.
