当前位置: X-MOL 学术PeerJ › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi
PeerJ ( IF 2.3 ) Pub Date : 2021-02-24 , DOI: 10.7717/peerj.11003
Alfred Ngwira 1 , Felix Kumwenda 1 , Eddons C S Munthali 1 , Duncan Nkolokosa 1
Affiliation  

Background COVID-19 has been one of the greatest challenges the world has faced since the second world war. This study aimed at investigating the distribution of COVID-19 in both space and time in Malawi. Methods The study used publicly available data of COVID-19 cases for the period from 2 April 2020 to 28 October 2020. Semiparametric spatial temporal models were fitted to the number of monthly confirmed cases as an outcome data, with time and district as independent variables, where district was the spatial unit, while accounting for sociodemographic factors. Results The study found significant effects of location and time, with the two interacting. The spatial distribution of COVID-19 risk showed major cities being at greater risk than rural areas. Over time, the COVID-19 risk was increasing then decreasing in most districts with the rural districts being consistently at lower risk. High proportion of elderly people was positively associated with COVID-19 risk (β = 1.272, 95% CI [0.171, 2.370]) than low proportion of elderly people. There was negative association between poverty incidence and COVID-19 risk (β = −0.100, 95% CI [−0.136, −0.065]). Conclusion Future or present strategies to limit the spread of COVID-19 should target major cities and the focus should be on time periods that had shown high risk. Furthermore, the focus should be on elderly and rich people.

中文翻译:


马拉维大流行早期阶段 COVID-19 风险的时空分布



背景 COVID-19 是第二次世界大战以来世界面临的最大挑战之一。本研究旨在调查马拉维 COVID-19 在空间和时间上的分布情况。方法该研究使用了2020年4月2日至2020年10月28日期间公开的COVID-19病例数据。半参数时空模型拟合了每月确诊病例数作为结果数据,以时间和地区作为自变量,其中区是空间单位,同时考虑了社会人口因素。结果 研究发现位置和时间有显着影响,两者相互作用。 COVID-19 风险的空间分布表明,主要城市比农村地区面临更大的风险。随着时间的推移,大多数地区的 COVID-19 风险先增后减,其中农村地区的风险始终较低。与低比例老年人相比,高比例老年人与 COVID-19 风险呈正相关(β = 1.272,95% CI [0.171,2.370])。贫困发生率与 COVID-19 风险之间存在负相关(β = -0.100,95% CI [-0.136,-0.065])。结论 未来或当前限制 COVID-19 传播的策略应针对主要城市,并且重点应放在已显示高风险的时间段。此外,重点应放在老年人和富人身上。
更新日期:2021-02-24
down
wechat
bug