CoMix: comparing mixing patterns in the Belgian population during and after lockdown

Abstract

The COVID-19 pandemic has shown how a newly emergent communicable disease can lay considerable burden on public health. To avoid system collapse, governments have resorted to several social distancing measures. In Belgium, this included a lockdown and a following period of phased re-opening. A representative sample of Belgian adults was asked about their contact behaviour from mid-April to the beginning of August, during different stages of the intervention measures in Belgium. Use of personal protection equipment (face masks) and compliance to hygienic measures was also reported. We estimated the expected reproduction number computing the ratio of $$\hbox {R}_{0}$$ R 0 with respect to pre-pandemic data. During the first two waves (the first month) of the survey, the reduction in the average number of contacts was around 80% and was quite consistent across all age-classes. The average number of contacts increased over time, particularly for the younger age classes, still remaining significantly lower than pre-pandemic values. From the end of May to the end of July , the estimated reproduction number has a median value larger than one, although with a wide dispersion. Estimated $$\hbox {R}_{0}$$ R 0 fell below one again at the beginning of August. We have shown how a rapidly deployed survey can measure compliance to social distancing and assess its impact on COVID-19 spread. Monitoring the effectiveness of social distancing recommendations is of paramount importance to avoid further waves of COVID-19.

Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020

“…Our study had some limitations. Firstly, the number of reported contacts per case was smaller (mean in August: 2.0; 95% CI: 1.8–2.0) and less heterogenous than what participants in a Belgian contact survey reported (mean: 3.5 during the period 27 July to 10 August) [ 13 ]. This was probably a result of our analyses only considering high-risk contacts (physical or cumulative 15 min non-physical contact within 1.5 m) and a result of poor recall of context-specific accidental social contacts (e.g.…”

Individual social contact data reflected SARS-CoV-2 transmission dynamics during the first wave in Germany better than population mobility data – an analysis based on the COVIMOD study

“…As of March 2021, over 100 million confirmed cases and over 2.5 million deaths have been recorded worldwide [2]. SARS-CoV-2 is primarily transmitted via droplets and aerosols, so that person-to-person contacts are a strong determinant of transmission dynamics [2][3][4]. Non-pharmaceutical interventions (NPIs) focusing on the reduction of person-to-person contacts are one of the cornerstones of the pandemic response.…”

“…Social contact patterns are known to be a critical factor for the transmission dynamics of respiratory infections [4,[6][7][8][9][10]. However, empirical social contact data have been scarce before the emergence of SARS-CoV-2 [11][12][13].…”

“…In 2005/2006, POLYMOD measured contacts of more than 7,000 participants across eight European countries [12]. Contact patterns observed in POLYMOD have been widely used to parametrize various mathematical models of infectious disease dynamics [3,4,12,14].…”

“…During the SARS-CoV-2 pandemic, contact surveys were initiated in several countries to understand the effect of contact precaution measures on social contact patterns [3,4,10,15,16].…”