ArticlePloS one2020
Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 5 of them syntheses that pooled 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.
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.
Who cites it
27 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Effectiveness of testing, contact tracing and isolation interventions among the general population on reducing transmission of SARS-CoV-2: a systematic review.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Pooled it
- Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Pooled it
- Comparative effectiveness of contact tracing interventions in the context of the COVID-19 pandemic: a systematic review.European journal of epidemiology · 2023Pooled it
- Measures implemented in the school setting to contain the COVID-19 pandemicThe Cochrane database of systematic reviews · 2022Pooled it
- Systematic review of empirical studies comparing the effectiveness of non-pharmaceutical interventions against COVID-19.The Journal of infection · 2021Pooled it
- The Impact of Public Health and Social Measures (PHSMs) on SARS-CoV-2 Transmission in the WHO European Region (2020-2022).Influenza and other respiratory viruses · 2024Article
- A data-driven analysis on the mediation effect of compartment models between control measures and COVID-19 epidemics.Heliyon · 2024Article
- The impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia: Simulation approach.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024Article
- Using a Bayesian hierarchical approach to study the association between non-pharmaceutical interventions and the spread of Covid-19 in Germany.Scientific reports · 2023Article
- Analysis of the COVID-19 pandemic using a compartmental model with time-varying parameters fitted by a genetic algorithm.Expert systems with applications · 2023Article
- Interaction between travel restriction policies and the spread of COVID-19.Transport policy · 2023Article
- Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study.Globalization and health · 2023Article
- Determining the nurses' perception regarding the effectiveness of COVID-19 protocols implemented in Eastern Province: Saudi Arabia.Frontiers in public health · 2023Article
- Communicating risk during early phases of COVID-19: Comparing governing structures for emergency risk communication across four contexts.Frontiers in public health · 2023Article
- Factors driving the implementation of the 'Local New Year' policy to prevent COVID-19 in China.Humanities & social sciences communications · 2023Article
- How Did Governments Address the Needs of People With Disabilities During the COVID-19 Pandemic? An Analysis of 14 Countries' Policies Based on the UN Convention on the Rights of Persons With Disabilities.International journal of health policy and management · 2023Article
- Evaluating scenarios for school reopening under COVID19.BMC public health · 2022Article
- Article
- A causal learning framework for the analysis and interpretation of COVID-19 clinical data.PloS one · 2022Review
- The fading impact of lockdowns: A data analysis of the effectiveness of Covid-19 travel restrictions during different pandemic phases.PloS one · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper reports the results of a Bayesian analysis on large-scale empirical data to assess the effectiveness of eleven types of COVID-control policies that have been implemented at various levels of intensity in 40 countries and U.S. states since the onset of the pandemic. The analysis estimates the marginal impact of each type and level of policy as implemented in concert with other policies. The purpose is to provide policymakers and the general public with an estimate of the relative effectiveness of various COVID-control strategies. We find that a set of widely implemented core policies reduces the spread of virus but not by enough to contain the pandemic except in a few highly compliant jurisdictions. The core policies include the cancellation of public events, restriction of gatherings to fewer than 100 people, recommendation to stay at home, recommended restrictions on internal movement, implementation of a partial international travel ban, and coordination of information campaigns. For the median jurisdiction, these policies reduce growth rate in new infections from an estimated 270% per week to approximately 49% per week, but this impact is insufficient to prevent eventual transmission throughout the population because containment occurs only when a jurisdiction reduces growth in COVID infection to below zero. Most jurisdictions must also implement additional policies, each of which has the potential to reduce weekly COVID growth rate by 10 percentage points or more. The slate of these additional high-impact policies includes targeted or full workplace closings for all but essential workers, stay-at-home requirements, and targeted school closures.
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Registered trials
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.