Evidence map›Paper›PMID 36417445›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong.

Zhanwei Du, Lin Wang, Songwei Shan, Dickson Lam, Tim K Tsang, Jingyi Xiao, Huizhi Gao, Bingyi Yang, Sheikh Taslim Ali, Sen Pei and 7 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  17. Heterogeneous risk tolerance, in-groups, and epidemic waves.Frontiers in applied mathematics and statistics · 2024
    Article
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  19. Article
  20. Local travel behaviour under continuing COVID-19 waves- A proxy for pandemic fatigue?Transportation research interdisciplinary perspectives · 2023
    Article
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

17 authors.

Zhanwei DuWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.ORCID 0000-0002-2020-767X
Lin WangDepartment of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom.ORCID 0000-0002-5371-2138
Songwei ShanWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Dickson LamIndependent Researcher, Hong Kong Special Administrative Region 000000, China.
Tim K TsangWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Jingyi XiaoWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Huizhi GaoWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Bingyi YangWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Sheikh Taslim AliWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Sen PeiDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10027.ORCID 0000-0002-7072-2995
Isaac Chun-Hai FungDepartment of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460.ORCID 0000-0001-5496-2529
Eric H Y LauWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.ORCID 0000-0002-6688-9637
Qiuyan LiaoWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Peng WuWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.ORCID 0000-0003-1157-9401
Lauren Ancel MeyersDepartment of Integrative Biology, University of Texas at Austin, Austin, TX 78712.ORCID 0000-0002-5828-8874
Gabriel M LeungWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.
Benjamin J CowlingWorld Health Organization Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region 000000, China.ORCID 0000-0002-6297-7154

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines and mobile telephones from May 2020 to February 2021. We analyze the epidemiological impact of pandemic fatigue by using the large and detailed cross-sectional telephone surveys to quantify risk perception and self-reported protective behaviors and mathematical models to incorporate population protective behaviors. Our retrospective prediction suggests that an increase of 100 daily new reported cases would lead to 6.60% (95% CI: 4.03, 9.17) more people worrying about being infected, increase 3.77% (95% CI: 2.46, 5.09) more people to avoid social gatherings, and reduce the weekly mean reproduction number by 0.32 (95% CI: 0.20, 0.44). Accordingly, the fourth wave would have been 14% (95% CI%: -53%, 81%) smaller if not for pandemic fatigue. This indicates the important role of mitigating pandemic fatigue in maintaining population protective behaviors for controlling COVID-19.

Indexed as

COVID-19Influenza, HumanCross-Sectional StudiesFatigueHong KongHumansPandemicsRetrospective StudiesCOVID-19mathematical modelpandemic fatigue

Identifiers

PMID36417445
PMCPMC9860288

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.