Nele Goeyvaerts

BACKGROUND: Mathematical modelling of infectious disease is increasingly used to help guide public health policy. As directly transmitted infections, such as influenza and tuberculosis, require contact between individuals, knowledge about contact patterns is a necessary pre-requisite of accurate model predictions. Of particular interest is the potential impact of school closure as a means of controlling pandemic influenza (and potentially other pathogens). METHODS: This paper uses a population-based prospective survey of mixing patterns in eight European countries to study the relative change in the basic reproduction number (R0--the average number of secondary cases from a typical primary case in a fully susceptible population) on weekdays versus weekends and during regular versus holiday periods. The relative change in R0 during holiday periods and weekends gives an indication of the impact collective school closures (and prophylactic absenteeism) may have during a pandemic. RESULTS: Social contact patterns differ substantially when comparing weekdays to the weekend and regular to holiday periods mainly due to the reduction in work and/or school contacts. For most countries the basic reproduction number decreases from the week to weekends and regular to holiday periods by about 21% and 17%, respectively. However for other countries no significant decrease was observed. CONCLUSION: We use a large-scale social contact survey in eight different European countries to gain insights in the relative change in the basic reproduction number on weekdays versus weekends and during regular versus holiday periods. The resulting estimates indicate that school closure can have a substantial impact on the spread of a newly emerging infectious disease that is transmitted via close (non sexual) contacts.

BACKGROUND: Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts. METHODS: Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved. For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days. A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established. RESULTS: People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure. CONCLUSION: We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models.

BACKGROUND: Few studies have quantified social mixing in remote rural areas of developing countries, where the burden of infectious diseases is usually the highest. Understanding social mixing patterns in those settings is crucial to inform the implementation of strategies for disease prevention and control. We characterized contact and social mixing patterns in rural communities of the Peruvian highlands. METHODS AND FINDINGS: This cross-sectional study was nested in a large prospective household-based study of respiratory infections conducted in the province of San Marcos, Cajamarca-Peru. Members of study households were interviewed using a structured questionnaire of social contacts (conversation or physical interaction) experienced during the last 24 hours. We identified 9015 reported contacts from 588 study household members. The median age of respondents was 17 years (interquartile range [IQR] 4-34 years). The median number of reported contacts was 12 (IQR 8-20) whereas the median number of physical (i.e. skin-to-skin) contacts was 8.5 (IQR 5-14). Study participants had contacts mostly with people of similar age, and with their offspring or parents. The number of reported contacts was mainly determined by the participants' age, household size and occupation. School-aged children had more contacts than other age groups. Within-household reciprocity of contacts reporting declined with household size (range 70%-100%). Ninety percent of household contact networks were complete, and furthermore, household members' contacts with non-household members showed significant overlap (range 33%-86%), indicating a high degree of contact clustering. A two-level mixing epidemic model was simulated to compare within-household mixing based on observed contact networks and within-household random mixing. No differences in the size or duration of the simulated epidemics were revealed. CONCLUSION: This study of rural low-density communities in the highlands of Peru suggests contact patterns are highly assortative. Study findings support the use of within-household homogenous mixing assumptions for epidemic modeling in this setting.

Summary In dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so-called ‘who acquires infection from whom’ matrix. These imposed mixing patterns are based on prior knowledge of age-related social mixing behaviour rather than observations. Alternatively, we can assume that transmission rates for infections transmitted predominantly through non-sexual social contacts are proportional to rates of conversational contact which can be estimated from a contact survey. In general, however, contacts reported in social contact surveys are proxies of those events by which transmission may occur and there may be age-specific characteristics that are related to susceptibility and infectiousness which are not captured by the contact rates. Therefore, we model transmission as the product of two age-specific variables: the age-specific contact rate and an age-specific proportionality factor, which entails an improvement of fit for the seroprevalence of the varicella zoster virus in Belgium. Furthermore, we address the effect on the estimation of the basic reproduction number, using non-parametric bootstrapping to account for different sources of variability and using multimodel inference to deal with model selection uncertainty. The method proposed makes it possible to obtain important information on transmission dynamics that cannot be inferred from approaches that have been traditionally applied hitherto.