Evidence map›Paper›PMID 35861674›Full record

ArticleJMIR public health and surveillance2022

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.

Wei Luo, Zhaoyin Liu, Yuxuan Zhou, Yumin Zhao, Yunyue Elita Li, Arif Masrur, Manzhu Yu

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Wei Luo *Department of Geography, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-8465-5607
Zhaoyin Liu *Department of Geography, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-3488-7389
Yuxuan Zhou *Department of Geography, National University of Singapore, Singapore, Singapore.ORCID 0000-0001-7110-1640
Yumin ZhaoDepartment of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-6573-7551
Yunyue Elita LiDepartment of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, United States.ORCID 0000-0003-4225-2735
Arif MasrurDepartment of Geography, Pennsylvania State University, State College, PA, United States.ORCID 0000-0001-5050-407X
Manzhu YuDepartment of Geography, Pennsylvania State University, State College, PA, United States.ORCID 0000-0001-6769-7517
National University of Singapore · SGPennsylvania State University · USPurdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectiveThe 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.

methodsWe 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.

resultsWe 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.

conclusionsThe 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.

Indexed as

COVID-19Asia, SoutheasternHumansPublic HealthSARS-CoV-2COVID-19Delta variantinterventionSoutheast Asiaspace-time scan

Identifiers

PMID35861674
PMCPMC9364972
OpenAlexW4286378045

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.