Evidence map›Paper›PMID 36668946›Full record

ArticleTropical medicine and infectious disease2023

Retrospective Modeling of the Omicron Epidemic in Shanghai, China: Exploring the Timing and Performance of Control Measures.

Lishu Lou, Longyao Zhang, Jinxing Guan, Xiao Ning, Mengli Nie, Yongyue Wei, Feng Chen

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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.

Lishu LouDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.
Longyao ZhangDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.
Jinxing GuanDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.
Xiao NingDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.ORCID 0000-0002-5785-2226
Mengli NieDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.
Yongyue WeiDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.ORCID 0000-0002-1132-1796
Feng ChenDepartment of Biostatistics, School of Public Health, Center of Global Health, Nanjing Medical University, Nanjing 211166, China.

Funding

National Natural Science Foundation of China 81973142 to Y.W.
6 · The paper itself

Abstract

backgroundIn late February 2022, the Omicron epidemic swept through Shanghai, and the Shanghai government responded to it by adhering to a dynamic zero-COVID strategy. In this study, we conducted a retrospective analysis of the Omicron epidemic in Shanghai to explore the timing and performance of control measures based on the eventual size and duration of the outbreak.

methodsWe constructed an age-structured and vaccination-stratified SEPASHRD model by considering populations that had been detected or controlled before symptom onset. In addition, we retrospectively modeled the epidemic in Shanghai from 26 February 2022 to 31 May 2022 across four periods defined by events and interventions, on the basis of officially reported confirmed (58,084) and asymptomatic (591,346) cases.

resultsAccording to our model fitting, there were about 785,123 positive infections, of which about 57,585 positive infections were symptomatic infections. Our counterfactual assessment found that precise control by grid management was not so effective and that citywide static management was still needed. Universal and enforced control by citywide static management contained 87.65% and 96.29% of transmission opportunities, respectively. The number of daily new and cumulative infections could be significantly reduced if we implemented static management in advance. Moreover, if static management was implemented in the first 14 days of the epidemic, the number of daily new infections would be less than 10.

conclusionsThe above research suggests that dynamic zeroing can only be achieved when strict prevention and control measures are implemented as early as possible. In addition, a lot of preparation is still needed if China wants to change its strategy in the future.

Indexed as

COVID-19Shanghai Omicron epidemictiming of control measurestransmission dynamics

Identifiers

PMID36668946
PMCPMC9862922

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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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 Socratic graph.