Evidence map›Paper›PMID 33771391›Full record

ArticleVaccine2021

Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use.

Mingwang Shen, Jian Zu, Christopher K Fairley, José A Pagán, Li An, Zhanwei Du, Yuming Guo, Libin Rong, Yanni Xiao, Guihua Zhuang and 2 more

Abstract read
In one paragraph

Article in Vaccine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 3 pooled it
–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

55 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
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  19. Cost-effectiveness analysis of BNT162b2 COVID-19 booster vaccination in the United States.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
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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

12 authors.

Mingwang ShenChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Jian ZuSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Christopher K FairleyChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
José A PagánDepartment of Public Health Policy and Management, School of Global Public Health, New York University, New York, NY, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
Li AnCenter for Complex Human-Environment Systems, San Diego State University, San Diego, CA, USA; Department of Geography, San Diego State University, San Diego, CA, USA.
Zhanwei DuDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX, USA.
Yuming GuoCentral Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
Libin RongDepartment of Mathematics, University of Florida, Gainesville, FL, USA.
Yanni XiaoSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Guihua ZhuangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Yan LiDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: yan.li1@mountsinai.org.
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China. Electronic address: lei.zhang1@xjtu.edu.cn.

Funding

Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS)R01HL141427 · NHLBI · NEW YORK ACADEMY OF MEDICINE · PI LIU, BIAN, YI, STELLA S · 2018 to 2021
$3.5M
Medical Research CouncilNHLBI NIH HHS R01 HL141427
6 · The paper itself

Abstract

backgroundMultiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon.

methodsWe developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases from 26th January to 15th September 2020 were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration.

resultsWithout a vaccine (scenario 1), the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8-4 million infections and 15,000-240,000 deaths across these four states over the next 12 months. Under this circumstance, introducing a vaccine (scenario 2) would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50% (scenario 3), a vaccine that is only 50% effective (weak vaccine) would require coverage of 55-94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32-57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely (scenario 4), a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48-78% or a strong vaccine (100% effective) with coverage of 33-58% would be required to suppress the epidemic. Delaying vaccination rollout for 1-2 months would not substantially alter the epidemic trend if the current non-pharmaceutical interventions are maintained.

conclusionsThe degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic.

Indexed as

MasksPhysical DistancingCaliforniaCOVID-19COVID-19 VaccinesFloridaHumansModels, TheoreticalNew YorkTexasUnited StatesCOVID-19 VaccinesCOVID-19 vaccineFace mask useSocial distancingVaccine coverageVaccine effectiveness

Identifiers

PMID33771391
PMCPMC7914016

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.