Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021.

Sushma Dahal, Ruiyan Luo, Raj Kumar Subedi, Meghnath Dhimal, Gerardo Chowell
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引用次数: 6

Abstract

Nepal was hard hit by a second wave of COVID-19 from April-May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021-22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google's mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41-0.43, reproduction number (Rt) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and Rt at 1.3 (95% CI: 1.3, 1.3)). Across provinces, Rt ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous Rt fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning.

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2019冠状病毒病的传播动态和短期预测:尼泊尔2020/2021。
尼泊尔在2021年4月至5月期间遭受了第二波COVID-19的严重打击。我们利用国家官方情况报告中实验室确诊的RT-PCR阳性病例数据,调查了COVID-19在国家和省级的传播动态。从2021年3月5日至2021年5月22日,我们使用三种动态现象增长模型,在国家层面进行了8周的10天和20天连续预测。我们还使用既定的方法估计了国家和省级的有效和瞬时再生产数量,并使用谷歌的流动性数据评估了流动性趋势。我们的预测估计表明,截至2021年6月,尼泊尔的COVID-19病例呈下降趋势。亚流行病模型和理查兹模型根据标准绩效指标提供了合理的COVID-19病例短期预测。在第一波中,COVID-19的发病率轨迹呈线性模式(生长参数减速(p) = 0.41-0.43,繁殖数(Rt)为1.1 (95% CI: 1.1, 1.2)),在第二波中呈次指数增长模式(p = 0.61 (95% CI: 0.58, 0.64)), Rt为1.3 (95% CI: 1.3, 1.3))。在第二波增长的早期阶段,各省的生育率在1.2到1.5之间。自2021年1月以来,瞬时Rt在1.0左右波动,表明持续传播良好。不同地区人员流动高峰与新冠肺炎发病率上升趋势一致。总之,我们发现亚流行和Richards模型对尼泊尔的COVID-19轨迹进行了合理的短期预测,这对医疗保健利用规划有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.60
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审稿时长
7 weeks
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