Evidence map›Paper›PMID 36803678›Full record

ArticleEpidemiology and infection2023

Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination.

Yuhao Zhou, Zhaowan Li, Wei Wu, Jianpeng Xiao, Wenjun Ma, Guanghu Zhu

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Article in Epidemiology and infection, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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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

6 authors.

Yuhao ZhouSchool of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, Guilin, China.
Zhaowan LiSchool of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, Guilin, China.
Wei WuGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Jianpeng XiaoGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Wenjun MaDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.
Guanghu ZhuSchool of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, Guilin, China.ORCID 0000-0002-1416-1476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission.

Indexed as

COVID-19Adaptation, PsychologicalHumansPandemicsSARS-CoV-2VaccinationAdaptive behaviourCOVID-19predictiontransmission modelvaccination

Identifiers

PMID36803678
PMCPMC10024953

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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 OpenQuestion graph.