Differential impact of physical distancing strategies on social contacts relevant for the spread of SARS-CoV-2: evidence from a cross-national online survey, March–April 2020
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Abstract
We investigate changes in social contact patterns following the gradual introduction of non-pharmaceutical interventions and their implications for infection transmission in the early phase of the pandemic.
Design, setting and participants
We conducted an online survey based on targeted Facebook advertising campaigns across eight countries (Belgium, France, Germany, Italy, the Netherlands, Spain, UK and USA), achieving a sample of 51 233 questionnaires in the period 13 March–12 April 2020. Poststratification weights based on census information were produced to correct for selection bias.
Outcome measures
Participants provided data on social contact numbers, adoption of protective behaviours and perceived level of threat. These data were combined to derive a weekly index of infection transmission, the net reproduction number R t .
Results
Evidence from the USA and UK showed that the number of daily contacts mainly decreased after governments issued the first physical distancing guidelines. In mid-April, daily social contact numbers had decreased between 61% in Germany and 87% in Italy with respect to pre-COVID-19 levels, mostly due to a contraction in contacts outside the home. Such reductions, which were uniform across age groups, were compatible with an R t equal or smaller than one in all countries, except Germany. This indicates lower levels of infection transmission, especially in a period of gradual increase in the adoption rate of the face mask outside the home.
Conclusions
We provided a comparable set of statistics on social contact patterns during the COVID-19 pandemic for eight high-income countries, disaggregated by week and other demographic factors, which could be leveraged by the scientific community for developing more realistic epidemic models of COVID-19.
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SciScore for 10.1101/2020.05.15.20102657: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study has limitations that should be discussed considering the findings. First, we collected data using an opt-in sample of Facebook users. Such non-probabilistic samples are somewhat less accurate than probability samples, but with the appropriate statistical adjustments such as those that we made, they offer a good approximation to …
SciScore for 10.1101/2020.05.15.20102657: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study has limitations that should be discussed considering the findings. First, we collected data using an opt-in sample of Facebook users. Such non-probabilistic samples are somewhat less accurate than probability samples, but with the appropriate statistical adjustments such as those that we made, they offer a good approximation to results that can be obtained from probabilistic samples. Furthermore, such samples can be collected rapidly and therefore can provide us with timely data that could not possibly be collected otherwise during a pandemic. Finally, our data cover a large population at minimal costs compared to more traditional surveys [15]. Second, as survey respondents were recruited through targeted online advertisements, this approach may potentially lead to self-selection bias, which, with online surveys on coronavirus-related behavioral outcomes, has been linked to the risk of underestimating the share of population complying with specific measures [37]. Indeed, our participants might differ to some extent from the general population in terms of their sociability patterns (due to their Facebook use) and their concerns about health-related issues (as they opted in to participate in the survey). We tackled this issue by stratifying our advertising campaigns and constructing post-stratification weights by factors that we believe are linked to both survey participation and the outcomes of interest of the survey [38, 39], and by ensuring that only respondents wh...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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