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调查 COVID-19 德尔塔变异株时空模式与东南亚公共卫生干预措施之间的关联:前瞻性时空扫描统计分析方法。

Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method.

机构信息

Department of Geography, National University of Singapore, Singapore, Singapore.

Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore.

出版信息

JMIR Public Health Surveill. 2022 Aug 9;8(8):e35840. doi: 10.2196/35840.

Abstract

BACKGROUND

The COVID-19 Delta variant has presented an unprecedented challenge to countries in Southeast Asia (SEA). Its transmission has shown spatial heterogeneity in SEA after countries have adopted different public health interventions during the process. Hence, it is crucial for public health authorities to discover potential linkages between epidemic progression and corresponding interventions such that collective and coordinated control measurements can be designed to increase their effectiveness at reducing transmission in SEA.

OBJECTIVE

The purpose of this study is to explore potential linkages between the spatiotemporal progression of the COVID-19 Delta variant and nonpharmaceutical intervention (NPI) measures in SEA. We detected the space-time clusters of outbreaks of COVID-19 and analyzed how the NPI measures relate to the propagation of COVID-19.

METHODS

We collected district-level daily new cases of COVID-19 from June 1 to October 31, 2021, and district-level population data in SEA. We adopted prospective space-time scan statistics to identify the space-time clusters. Using cumulative prospective space-time scan statistics, we further identified variations of relative risk (RR) across each district at a half-month interval and their potential public health intervention linkages.

RESULTS

We found 7 high-risk clusters (clusters 1-7) of COVID-19 transmission in Malaysia, the Philippines, Thailand, Vietnam, and Indonesia between June and August, 2021, with an RR of 5.45 (P<.001), 3.50 (P<.001), 2.30 (P<.001), 1.36 (P<.001), 5.62 (P<.001), 2.38 (P<.001), 3.45 (P<.001), respectively. There were 34 provinces in Indonesia that have successfully mitigated the risk of COVID-19, with a decreasing range between -0.05 and -1.46 due to the assistance of continuous restrictions. However, 58.6% of districts in Malaysia, Singapore, Thailand, and the Philippines saw an increase in the infection risk, which is aligned with their loosened restrictions. Continuous strict interventions were effective in mitigating COVID-19, while relaxing restrictions may exacerbate the propagation risk of this epidemic.

CONCLUSIONS

The analyses of space-time clusters and RRs of districts benefit public health authorities with continuous surveillance of COVID-19 dynamics using real-time data. International coordination with more synchronized interventions amidst all SEA countries may play a key role in mitigating the progression of COVID-19.

摘要

背景

COVID-19 的德尔塔变异株给东南亚国家(SEA)带来了前所未有的挑战。在各国在疫情期间采取不同的公共卫生干预措施后,其传播在 SEA 呈现出空间异质性。因此,公共卫生当局必须发现疫情发展与相应干预措施之间的潜在联系,以便制定集体协调的控制措施,提高其在 SEA 减少传播的效果。

目的

本研究旨在探讨 COVID-19 德尔塔变异株在 SEA 的时空传播与非药物干预(NPI)措施之间的潜在联系。我们检测了 COVID-19 的时空爆发集群,并分析了 NPI 措施如何与 COVID-19 的传播有关。

方法

我们收集了 2021 年 6 月 1 日至 10 月 31 日 SEA 地区的每日新的 COVID-19 病例和地区级人口数据。我们采用前瞻性时空扫描统计方法来识别时空集群。使用累积前瞻性时空扫描统计,我们进一步确定了每半个月各地区相对风险(RR)的变化及其潜在的公共卫生干预联系。

结果

我们发现,2021 年 6 月至 8 月期间,马来西亚、菲律宾、泰国、越南和印度尼西亚有 7 个高风险 COVID-19 传播集群(集群 1-7),RR 分别为 5.45(P<.001)、3.50(P<.001)、2.30(P<.001)、1.36(P<.001)、5.62(P<.001)、2.38(P<.001)、3.45(P<.001)。印度尼西亚有 34 个省份成功降低了 COVID-19 的风险,由于持续的限制措施,范围在-0.05 到-1.46 之间。然而,马来西亚、新加坡、泰国和菲律宾的 58.6%的地区感染风险增加,这与他们放宽限制有关。持续的严格干预措施在减轻 COVID-19 方面是有效的,而放宽限制可能会加剧疫情的传播风险。

结论

使用实时数据对 COVID-19 动态进行连续监测的时空集群和地区 RR 分析有助于公共卫生当局。SEA 各国之间的国际协调与更同步的干预措施可能在减轻 COVID-19 进展方面发挥关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a55/9364972/5c97ce293612/publichealth_v8i8e35840_fig1.jpg

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