ArticlePloS one2020
Evolving social contact patterns during the COVID-19 crisis in Luxembourg.
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 40 papers.
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.
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
40 citing papers in PubMed.
- The impact of public health and social measures on social contact patterns and transmission of COVID-19 in Hong Kong.BMC medicine · 2026Article
- Health beliefs and their relation to household, necessary, and unnecessary contacts across COVID-19 epidemic waves in Taiwan.BMC public health · 2025Article
- Social Contact Patterns and Age Mixing before and during COVID-19 Pandemic, Greece, January 2020-October 2021.Emerging infectious diseases · 2025Article
- Contact Tracing Different Age Groups During the COVID-19 Pandemic: Retrospective Study From South-West Germany.Online journal of public health informatics · 2024Article
- Social contact patterns following the COVID-19 pandemic: a snapshot of post-pandemic behaviour from the CoMix study.Epidemics · 2024Article
- Social contact patterns during the early COVID-19 pandemic in Norway: insights from a panel study, April to September 2020.BMC public health · 2024Article
- Longitudinal social contact data analysis: insights from 2 years of data collection in Belgium during the COVID-19 pandemic.BMC public health · 2023Article
- Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts.Epidemics · 2023Article
- Impact of tiered measures on social contact and mixing patterns of in Italy during the second wave of COVID-19.BMC public health · 2023Article
- Quantifying social contact patterns in Minnesota during stay-at-home social distancing order.BMC infectious diseases · 2023Article
- Social contact patterns during the COVID-19 pandemic in 21 European countries - evidence from a two-year study.BMC infectious diseases · 2023Article
- Dynamics of non-household contacts during the COVID-19 pandemic in 2020 and 2021 in the Netherlands.Scientific reports · 2023Article
- Was it really different? COVID-19-pandemic period in long-term recreation monitoring - A case study from Polish forests.Journal of outdoor recreation and tourism · 2023Article
- Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium.Frontiers in public health · 2023Article
- Article
- Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study.Vaccine · 2022Article
- Changes in structure and function of social networks of independently living middle-aged and older adults in diverse sociodemographic subgroups during the COVID-19 pandemic: a longitudinal study.BMC public health · 2022Article
- Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States.PLoS computational biology · 2022Article
- Session 3 of the RSS Special Topic Meeting on Covid-19 Transmission: Replies to the discussion.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022Article
- Investigation of turning points in the effectiveness of Covid-19 social distancing.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We conducted an internet survey using Survey Monkey over six weeks to evaluate the impact of the government interventions on social contact patterns in Luxembourg. Participants were recruited via the science.lu website on March 25, April 2, April 16, May 1 during lockdown, and June 12 and June 25 after the lockdown to provide an estimate of their number of contacts within the previous 24 hours. During the lockdown, a total of 5,644 survey participants with a mean age of 44.2 years reported 18,118 contacts (mean = 3.2, IQR 1-4). The average number of contacts per day increased by 24% from 2.9 to 3.6 over the lockdown period. The average number of contacts decreased with age: 4.2 (IQR 2-5) for participants below 25 years and 1.7 (IQR 1-2) for participants above 64 years. Residents of Portuguese nationality reported a higher number of contacts (mean = 4.3, IQR 2-5) than Luxembourgish (mean = 3.5, IQR 2-4) or other foreign residents, respectively. After lockdown, 1,119 participants reported 7,974 contacts with 7.1 (IQR 3-9) contacts per day on average, of which 61.7% (4,917/7,974) occurred without a facemask (mean = 4.9, IQR 2-6). While the number of social contacts was substantially lower during the lockdown by more than 80% compared to the pre-pandemic period, we observed a more recent 121% increase during the post lockdown period showing an increased potential for COVID-19 spread. Monitoring social contacts is an important indicator to estimate the possible impact of government interventions on social contacts and the COVID-19 spread in the coming months.
Indexed as
Identifiers
What OpenQuestion holds
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.