The French Connection : the first large population-based contact survey in France relevant for the spread of infectious diseasesThe French Connection : the first large population-based contact survey in France relevant for the spread of infectious diseases
Faculty of Medicine and Health Sciences
Vaccine & Infectious Disease Institute (VAXINFECTIO)
Engineering sciences. Technology
10(2015):7, 22 p.
University of Antwerp
Background Empirical 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. Methods COMES-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. Results 2033 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 R-0 by 33% and 28%, respectively. Thus, school closures could have an important impact on the spread of close contact infections in France. Conclusions Despite 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.