Quantifying age-related rates of social contact using diaries in a rural coastal population of Kenya
Kiti MC, Kinyanjui TM, Koech DC, Munywoki PK, Medley GF, Nokes DJ
PLoS One. 2014;9
BACKGROUND: Improved understanding and quantification of social contact patterns that govern the transmission dynamics of respiratory viral infections has utility in the design of preventative and control measures such as vaccination and social distancing. The objective of this study was to quantify an age-specific matrix of contact rates for a predominantly rural low-income population that would support transmission dynamic modeling of respiratory viruses. METHODS AND FINDINGS: From the population register of the Kilifi Health and Demographic Surveillance System, coastal Kenya, 150 individuals per age group (<1, 1-5, 6-15, 16-19, 20-49, 50 and above, in years) were selected by stratified random sampling and requested to complete a day long paper diary of physical contacts (e.g. touch or embrace). The sample was stratified by residence (rural-to-semiurban), month (August 2011 to January 2012, spanning seasonal changes in socio-cultural activities), and day of week. Usable diary responses were obtained from 568 individuals ( approximately 50% of expected). The mean number of contacts per person per day was 17.7 (95% CI 16.7-18.7). Infants reported the lowest contact rates (mean 13.9, 95% CI 12.1-15.7), while primary school students (6-15 years) reported the highest (mean 20.1, 95% CI 18.0-22.2). Rates of contact were higher within groups of similar age (assortative), particularly within the primary school students and adults (20-49 years). Adults and older participants (>50 years) exhibited the highest inter-generational contacts. Rural contact rates were higher than semiurban (18.8 vs 15.6, p = 0.002), with rural primary school students having twice as many assortative contacts as their semiurban peers. CONCLUSIONS AND SIGNIFICANCE: This is the first age-specific contact matrix to be defined for tropical Sub-Saharan Africa and has utility in age-structured models to assess the potential impact of interventions for directly transmitted respiratory infections.