The French Connection: The First Large Population-Based Contact Survey in France Relevant for the Spread of Infectious Diseases

Abstract

BackgroundEmpirical social contact patterns are essential to understand the spread of infectious diseases. To date, no such data existed for France. Although infectious diseases are frequently seasonal, the temporal variation of contact patterns has not been documented hitherto.MethodsCOMES-F is the first French large-scale population survey, carried out over 3 different periods (February-March, April, April-May) with some participants common to the first and the last period. Participants described their contacts for 2 consecutive days, and reported separately on professional contacts when typically over 20 per day.Results2033 participants reported 38 881 contacts (weighted median [first quartile-third quartile]: 8[5–14] per day), and 54 378 contacts with supplementary professional contacts (9[5–17]). Contrary to age, gender, household size, holidays, weekend and occupation, period of the year had little influence on the number of contacts or the mixing patterns. Contact patterns were highly assortative with age, irrespective of the location of the contact, and gender, with women having 8% more contacts than men. Although most contacts occurred at home and at school, the inclusion of professional contacts modified the structure of the mixing patterns. Holidays and weekends reduced dramatically the number of contacts, and as proxies for school closure, reduced R0 by 33% and 28%, respectively. Thus, school closures could have an important impact on the spread of close contact infections in France.ConclusionsDespite no clear evidence for temporal variation, trends suggest that more studies are needed. Age and gender were found important determinants of the mixing patterns. Gender differences in mixing patterns might help explain gender differences in the epidemiology of infectious diseases.

Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies

“…Here we consider three values: 25%, 50% (as declared by participants of a crowdsourced system monitoring COVID-19 associated behaviors in France 30 ), and 70% (from reductions in the number of trips measured from mobile phone data after lockdown 31 ). Household contacts are increased proportionally to each adult staying at home based on statistics comparing weekend vs. weekday contacts 16 and proportion of adults working during the weekend 32 . • Senior isolation: contacts established by seniors are reduced by a given % to model a marked social distancing targeting only the age class at higher risk of complications.…”

Development of a Social Contact Survey Instrument Relevant to the Spread of Infectious Disease and Its Application in a Pilot Study Among Korean Adults

“…The selected studies were reviewed, and variables affecting contact in people's daily lives were identified. The social contact survey instrument similarly comprised 2 parts: part I contained a contact diary for assessing social contacts within a 24hour period (5 a.m. to 5 a.m. the next day), as contact diaries have been frequently used to record social contacts [1][2][3][4][5][6][7][8], while part II contained a questionnaire that assessed perceptions of contacts in daily life and practices of hand hygiene and coughing etiquette. Part I included 5 sections to be filled out by the participant: (I-1) number of family members; (I-2) place of residence; (I-3) information about family members; (I-4) information about the people with whom the participant had been in contact in the last 24 hours as well as the type, duration, location, and frequency of contacts; and (I-5) a request that the participant check the previous 4 entries for accuracy [5,6].…”

“…Understanding the nature of human contact patterns is crucial for predicting the impact of future pandemics and for devising effective control measures [2][3][4]. Presently, reporting systems in many countries measure the numbers and characteristics of contact patterns in the population with the goal of controlling the spread of infection [4][5][6][7][8]. Moreover, mathematical modeling of infectious diseases transmitted by respiratory or close-contact routes (e.g., pandemic influenza) is being increasingly used to predict epidemics and to determine the impact of possible interventions [5].…”

Social Contact Structures and Time Use Patterns in the Manicaland Province of Zimbabwe

“…As a consequence, mathematical modeling of infectious diseases, initially based on simplifying theory-driven assumptions [1] such as homogeneous mixing, have gradually shifted towards using empirical evidence on real individuals’ interactions. In particular, over the past decade, field data on social contacts patterns have been gathered through diary-based surveys for a number of countries in Europe [2–7], North America [8], Oceania [9], Asia [6,10–14], South America [15], and Africa [16–18]. Age-specific mixing matrices built on the gathered data have been largely used to model the spread of epidemics driven by close-contact interactions [19–22], and the transmission of endemic childhood infections [23–27].…”