scholarly journals Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Thang Van Hoang ◽  
Pietro Coletti ◽  
Yimer Wasihun Kifle ◽  
Kim Van Kerckhove ◽  
Sarah Vercruysse ◽  
...  
Keyword(s):  
Close Contact ◽  
Social Contact ◽  
Additive Models ◽  
Contact Rates ◽  
Contact Patterns ◽  
Time Period ◽  
Social Mixing ◽  
Mixing Patterns ◽  
Contact Survey ◽  
The Impact

Abstract Background In 2010-2011, we conducted a social contact survey in Flanders, Belgium, aimed at improving and extending the design of the first social contact survey conducted in Belgium in 2006. This second social contact survey aimed to enable, for the first time, the estimation of social mixing patterns for an age range of 0 to 99 years and the investigation of whether contact rates remain stable over this 5-year time period. Methods Different data mining techniques are used to explore the data, and the age-specific number of social contacts and the age-specific contact rates are modelled using a generalized additive models for location, scale and shape (GAMLSS) model. We compare different matrices using assortativeness measures. The relative change in the basic reproduction number (R0) and the ratio of relative incidences with 95% bootstrap confidence intervals (BCI) are employed to investigate and quantify the impact on epidemic spread due to differences in sex, day of the week, holiday vs. regular periods and changes in mixing patterns over the 5-year time gap between the 2006 and 2010-2011 surveys. Finally, we compare the fit of the contact matrices in 2006 and 2010-2011 to Varicella serological data. Results All estimated contact patterns featured strong homophily in age and sex, especially for small children and adolescents. A 30% (95% BCI [17%; 37%]) and 29% (95% BCI [14%; 40%]) reduction in R0 was observed for weekend versus weekdays and for holiday versus regular periods, respectively. Significantly more interactions between people aged 60+ years and their grandchildren were observed on holiday and weekend days than on regular weekdays. Comparing contact patterns using different methods did not show any substantial differences over the 5-year time period under study. Conclusions The second social contact survey in Flanders, Belgium, endorses the findings of its 2006 predecessor and adds important information on the social mixing patterns of people older than 60 years of age. Based on this analysis, the mixing patterns of people older than 60 years exhibit considerable heterogeneity, and overall, the comparison of the two surveys shows that social contact rates can be assumed stable in Flanders over a time span of 5 years.

scholarly journals Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011

2020 ◽  
Author(s):  
Thang Van Hoang ◽  
Pietro Coletti ◽  
Yimer Wasihun Kiffe ◽  
Kim Van Kerckhove ◽  
Sarah Vercruysse ◽  
...  
Keyword(s):  
Large Scale ◽  
Close Contact ◽  
Social Contact ◽  
Contact Rates ◽  
Contact Patterns ◽  
Time Period ◽  
Social Mixing ◽  
Mixing Patterns ◽  
Contact Survey ◽  
The Impact

AbstractBackgroundIn 2010-2011, we conducted a social contact survey in Flanders, Belgium, aimed at improving and extending the design of the first social contact survey conducted in Belgium in 2006. This second social contact survey aimed to enable, for the first time, the estimation of social mixing patterns for an age range of 0 to 99 years and the investigation of whether contact rates remain stable over this 5-year time period.MethodsDifferent data mining techniques are used to explore the data, and the age-specific number of social contacts and the age-specific contact rates are modelled using a GAMLSS model. We compare different matrices using assortativeness measures. The relative change in the basic reproduction number (R0) and the ratio of relative incidences with 95% bootstrap confidence intervals (BCI) are employed to investigate and quantify the impact on epidemic spread due to differences in gender, day of the week, holiday vs. regular periods and changes in mixing patterns over the 5-year time gap between the 2006 and 2010-2011 surveys. Finally, we compare the fit of the contact matrices in 2006 and 2010-2011 to Varicella serological data.ResultsAll estimated contact patterns featured strong homophily in age and gender, especially for small children and adolescents. A 30% (95% BCI [17%; 37%] ) and 29% (95% BCI [14%; 40%] ) reduction in R0 was observed for weekend versus weekdays and for holiday versus regular periods, respectively. Significantly more interactions between people aged 60+ years and their grandchildren were observed on holiday and weekend days than on regular weekdays. Comparing contact patterns using different methods did not show any substantial differences over the 5-year time period under study.ConclusionsThe second social contact survey in Flanders, Belgium, endorses the findings of its 2006 predecessor and adds important information on the social mixing patterns of people older than 60 years of age. Based on this analysis, the mixing patterns of people older than 60 years exhibit considerable heterogeneity, and overall, the comparison of the two surveys shows that social contact rates can be assumed stable in Flanders over a time span of 5 years.

scholarly journals Characteristics of human encounters and social mixing patterns relevant to infectious diseases spread by close contact: A survey in southwest Uganda

2017 ◽  
Author(s):  
O le Polain de Waroux ◽  
S Cohuet ◽  
D Ndazima ◽  
A J Kucharski ◽  
A Juan-Giner ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Close Contact ◽  
Control Strategies ◽  
Social Contact ◽  
The Elderly ◽  
Human Interactions ◽  
Contact Patterns ◽  
Social Mixing ◽  
Contact Survey ◽  
The Impact

ABSTRACTQuantification of human interactions relevant to infectious disease transmission through social contact is central to predict disease dynamics, yet data from low-resource settings remain scarce. We undertook a social contact survey in rural Uganda, whereby participants were asked to recall details about the frequency, type, and socio-demographic characteristics of any conversational encounter that lasted for ≥5 minutes (henceforth defined as ‘contacts’) during the previous day. An estimate of the number of ‘casual contacts’ (i.e. <5 minutes) was also obtained. A total of 568 individuals were included. On average participants reported having routine contact with 7.2 individuals (range 1-25). Children aged 5-14 years had the highest frequency of contacts and the elderly (≥65 years) the fewest (P<0.001). A strong age-assortative pattern was seen, particularly outside the household and increasingly so for contacts occurring further away from home. Adults aged 25-64 years tended to travel more and further than others, and males travelled more frequently than females. Our study provides detailed information on contact patterns and their spatial characteristics in an African setting. It therefore fills an important knowledge gap that will help more accurately predict transmission dynamics and the impact of control strategies in such areas.

scholarly journals Modelling the SARS-CoV-2 first epidemic wave in Greece: social contact patterns for impact assessment and an exit strategy from social distancing measures

2020 ◽  
Author(s):  
Vana Sypsa ◽  
Sotirios Roussos ◽  
Dimitrios Paraskevis ◽  
Theodore Lytras ◽  
S Sotirios Tsiodras ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Attack Rate ◽  
Social Contact ◽  
Social Distancing ◽  
Relative Contribution ◽  
Contact Patterns ◽  
Social Mixing ◽  
Mixing Patterns ◽  
The Impact ◽  
Epidemic Wave

AbstractIn Greece, a nationwide lockdown to mitigate the transmission of SARS-CoV-2 was imposed on March 23, 2020. As by the end of April the first epidemic wave is waning, it is important to assess the infection attack rate and quantify the impact of physical distancing. We implemented a survey to assess social mixing patterns before the epidemic and during lockdown. We estimated R0 from surveillance data and assessed its decline as a result of physical distancing based on social contacts data. We applied a Susceptible-Exposed-Infectious-Recovered model to estimate the infection attack rate and the infection fatality ratio (IFR). As multiple social distancing measures were implemented simultaneously (schools/work/leisure), we assessed their overall impact as well as their relative contribution. R0 was estimated 2·38 (95%CI: 2·01,2·80). By April 26th, the infection attack rate was 0·12% (95%CrI: 0·06%,0·26%) and the IFR 1·12% (95%CrI: 0·55%,2·31%). During lockdown, daily contacts were reduced by 86·9% and the effective reproduction number reached 0·46 (95%CrI: 0·35,0·57). The reduction in R0 attributed to lockdown was 81·0% (95%CrI: 71·8%,86·0%) whereas the reduction attributed to each measure separately ranged between 10%-24%. We assessed scenarios with less disruptive social distancing measures as well as scenarios where measures are partially lifted after lockdown. This is the first impact assessment of the first wave of SARS-CoV-2 in a European country. It suggests that only multiple measures implemented simultaneously could reduce R0 below 1. Measuring social mixing patterns can be a tool for real-time monitoring of the epidemic potential.

scholarly journals Social mixing patterns for transmission models of close contact infections: exploring self-evaluation and diary-based data collection through a web-based interface

2006 ◽  
Vol 134 (6) ◽  
pp. 1158-1166 ◽  
Author(s):  
P. BEUTELS ◽  
Z. SHKEDY ◽  
M. AERTS ◽  
P. VAN DAMME
Keyword(s):  
Close Contact ◽  
Social Contact ◽  
Convenience Sample ◽  
Web Based ◽  
Self Evaluation ◽  
Social Mixing ◽  
Contact Data ◽  
Mixing Patterns ◽  
The Difference ◽  
Transmission Models

Although mixing patterns are crucial in dynamic transmission models of close contact infections, they are largely estimated by intuition. Using a convenience sample (n=73), we tested self-evaluation and prospective diary surveys with a web-based interface, in order to obtain social contact data. The number of recorded contacts was significantly (P<0·01) greater on workdays (18·1) vs. weekend days (12·3) for conversations, and vice versa for touching (5·4 and 7·2 respectively). Mixing was highly assortative with age for both (adults contacting other adults vs. 0- to 5-year-olds, odds ratio 8·9–10·8). Respondents shared a closed environment significantly more often with >20 other adults than with >20 children. The difference in number of contacts per day was non-significant between self-evaluation and diary (P=0·619 for conversations, P=0·125 for touching). We conclude that self-evaluation could yield similar results to diary surveys for general or very recent mixing information. More detailed data could be collected by diary, at little effort to respondents.

scholarly journals Augmenting contact matrices with time-use data for fine-grained intervention modelling of disease dynamics: A modelling analysis

2020 ◽  
Author(s):  
Edwin van Leeuwen ◽  
Frank Sandmann ◽  
Keyword(s):  
Time Use ◽  
Large Scale ◽  
Close Contact ◽  
Public Health Intervention ◽  
Social Contact ◽  
Social Activities ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Mixing Patterns ◽  
The Impact

AbstractBackgroundSocial distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as SARS-CoV-2 during the coronavirus disease 2019 (COVID-19) pandemic. We aimed to explore the impact on the epidemic curve of fewer contacts when individuals reduce the time they spend on selected daily activities.MethodsWe combined the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0-15, 16-24, 25-44, 45-64, 65+) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). We assumed that reductions in time are proportional to reductions in contacts. The derived matrices were then applied in an age-structured dynamic-transmission model of COVID-19 to explore the effects.FindingsThe relative reductions in the derived contact matrices were highest when closing schools (in ages 0-14 years), workplaces (15-64 years), and stopping social visits (65+ years). For COVID-19, the closure of workplaces, schools, and stopping social visits had the largest impact on reducing the epidemic curve and delaying its peak, while the predicted impact of fewer contacts in parks, bars/cafes/restaurants, and non-essential shopping were minimal.InterpretationWe successfully augmented contact matrices with time-use data to predict the highest impact of social distancing measures from reduced contacts when spending less time at work, school, and on social visits. Although the predicted impact from other leisure activities with potential for close physical contact were minimal, changes in mixing patterns and time-use immediately after re-allowing social activities may pose increased short-term transmission risks, especially in potentially crowded environments indoors.Research in contextEvidence before this studyWe searched PubMed for mathematical models using social contact matrices and time-use data to explore the impact of reduced social contacts as seen from social distancing measures adopted during the coronavirus disease 2019 (COVID-19) pandemic with the search string ((social OR physical) AND distancing) OR (contact* OR (contact matri*)) AND (time-use) AND (model OR models OR modeling OR modelling) from inception to May 06, 2020, with no language restrictions. We found several studies that used time-use data to re-create contact matrices based on time spent in similar locations or to calculate the length of exposure. We identified no study that augmented social contact matrices with time-use data to estimate the impact on transmission dynamics of reducing selected social activities and lifting these restrictions again, as seen during the COVID-19 pandemic.Added value of this studyOur study combines the empirical data of two large-scale, representative surveys to derive social contact matrices that enrich the frequency of contacts with the duration of exposure for selected social activities, which allows for more fine-grained mixing patterns and infectious disease modelling. We successfully applied the resulting matrices to estimate reductions in contacts from social distancing measures such as adopted during the COVID-19 pandemic, as well as the effect on the epidemic curve from increased social contacts when lifting such restrictions again.Implications of all the available evidenceSocial distancing measures are an important public health intervention to limit the close-contact transmission of emerging infectious pathogens by reducing the social mixing of individuals. Our model findings suggest a higher fraction of close-contact transmission occurs at work, schools, and social visits than from visits to parks, bars/cafes/restaurants, and non-essential shopping. The minimal predicted impact is suggestive of lifting the restrictions on certain activities and excluding them from the list of social distancing measures, unless required to maintain sufficient healthcare capacity. However, potential replacement effects of activities and in mixing patterns remain unclear, particularly immediately after re-allowing social activities again.

scholarly journals Characteristics of human encounters and social mixing patterns relevant to infectious diseases spread by close contact: a survey in Southwest Uganda

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
O. le Polain de Waroux ◽  
S. Cohuet ◽  
D. Ndazima ◽  
A. J. Kucharski ◽  
A. Juan-Giner ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Close Contact ◽  
Social Mixing ◽  
Mixing Patterns

scholarly journals Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
James D. Munday ◽  
Christopher I. Jarvis ◽  
Amy Gimma ◽  
Kerry L. M. Wong ◽  
Kevin van Zandvoort ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Transmission Risk ◽  
Individual Level ◽  
Face To Face ◽  
School Settings ◽  
Contact Rates ◽  
Contact Survey ◽  
The Uk ◽  
The Impact

Abstract Background Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

scholarly journals The influence of risk perceptions on close contact frequency during the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
James Wambua ◽  
Lisa Hermans ◽  
Pietro Coletti ◽  
Frederik Verelst ◽  
Lander Willem ◽  
...  
Keyword(s):  
Public Health ◽  
Health Communication ◽  
Risk Perceptions ◽  
Close Contact ◽  
Social Contact ◽  
Perceived Severity ◽  
Public Health Communication ◽  
Contact Behaviour ◽  
Contact Frequency ◽  
The Impact

Abstract Human behaviour is known to be crucial in the propagation of infectious diseases through respiratory or close-contact routes like the current SARS-CoV-2 virus. Intervention measures implemented to curb the spread of the virus mainly aim at limiting the number of close contacts, until vaccine roll-out is complete. Our main objective was to assess the relationships between SARS-CoV-2 perceptions and social contact behaviour in Belgium. Understanding these relationships is crucial to maximize interventions' effectiveness, e.g. by tailoring public health communication campaigns. In this study, we surveyed a representative sample of adults in Belgium in two longitudinal surveys (8 waves of survey 1 in April 2020 to August 2020, and 11 waves of survey 2 in November 2020 to April 2021). Generalized linear mixed effects models were used to analyse the two surveys. Participants with low and neutral perceptions on perceived severity made a significantly higher number of social contacts as compared to participants with high levels of perceived severity after controlling for other variables. Furthermore, participants with higher levels of perceived effectiveness of measures and perceived adherence to measures made fewer contacts. However, the differences were small. Our results highlight the key role of perceived severity on social contact behaviour during a pandemic. Nevertheless, additional research is required to investigate the impact of public health communication on severity of COVID-19 in terms of changes in social contact behaviour.

scholarly journals Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors

2019 ◽  
Vol 4 ◽  
pp. 84 ◽  
Author(s):  
Moses Chapa Kiti ◽  
Alessia Melegaro ◽  
Ciro Cattuto ◽  
David James Nokes
Keyword(s):  
Urban Areas ◽  
Respiratory Infections ◽  
Social Contact ◽  
Simulation Models ◽  
Face To Face ◽  
Rural And Urban Areas ◽  
Contact Patterns ◽  
Rural And Urban ◽  
Syncytial Virus ◽  
The Impact

Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.

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