ArticleCommunications medicine2023
Epidemic modelling of monitoring public behavior using surveys during pandemic-induced lockdowns.
Article in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
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Who cites it
4 citing papers in PubMed.
- Explaining COVID-19 dynamics through user activity data from digital platforms with Yandex's self-isolation index as a case study.Scientific reports · 2025Article
- Comparative evaluation of behavioral epidemic models using COVID-19 data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Short, stringent lockdowns halted SARS-CoV-2 transmissions in Danish municipalities.Scientific reports · 2024Article
- A practical agenda for incorporating trust into pandemic preparedness and response.Bulletin of the World Health Organization · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundImplementing a lockdown for disease mitigation is a balancing act: Non-pharmaceutical interventions can reduce disease transmission significantly, but interventions also have considerable societal costs. Therefore, decision-makers need near real-time information to calibrate the level of restrictions.
methodsWe fielded daily surveys in Denmark during the second wave of the COVID-19 pandemic to monitor public response to the announced lockdown. A key question asked respondents to state their number of close contacts within the past 24 hours. Here, we establish a link between survey data, mobility data, and hospitalizations via epidemic modelling of a short time-interval around Denmark's December 2020 lockdown. Using Bayesian analysis, we then evaluate the usefulness of survey responses as a tool to monitor the effects of lockdown and then compare the predictive performance to that of mobility data.
resultsWe find that, unlike mobility, self-reported contacts decreased significantly in all regions before the nation-wide implementation of non-pharmaceutical interventions and improved predicting future hospitalizations compared to mobility data. A detailed analysis of contact types indicates that contact with friends and strangers outperforms contact with colleagues and family members (outside the household) on the same prediction task.
conclusionsRepresentative surveys thus qualify as a reliable, non-privacy invasive monitoring tool to track the implementation of non-pharmaceutical interventions and study potential transmission paths.
Identifiers
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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.