Social contacts and mixing patterns in rural Gambia

Background Close contact between an infectious and susceptible person is an important factor in respiratory disease transmission. Information on social contacts and mixing patterns in a population is crucial to understanding transmission patterns and informing transmission models of respiratory infections. Although West Africa has one of the highest burdens of respiratory infections, there is a lack of data on interpersonal contact and mixing patterns in this region. Methods Between January and November 2022, we conducted a cross-sectional, social contact survey within the population of the Central and Upper River Regions of The Gambia. Selected participants completed a questionnaire about their travel history and social contacts, detailing the number, intensity, location, frequency, duration, and age of contacts. We calculated age-standardized contact matrices to determine contact patterns in the population. Results Overall, individuals made an average of 12.7 (95% CI: 12.4-13.0) contacts per day. Contact patterns were mostly age-assortative and 84.5% of all contacts were physical. School-aged children (5-14 years) had the highest mean number of physical contacts (11.3, 95% CI: 10.9-11.8) while the < 1-year age group had the fewest contacts (9.4, 95% CI: 9.1-9.8). A large proportion of contacts (78%) occurred at home. Daily number of contacts increased with household size. While we did not observe any effect of gender on contact patterns, there were seasonal variations in contact type. Non-physical contacts were higher during the dry season compared to the rainy season. In contrast, there were more physical contacts in the rainy season compared to the dry season. Conclusions In rural Gambia, social contact patterns were primarily driven by household mixing. Most contacts were physical and mostly age-assortative, particularly among school-aged children. Our data can improve infectious disease transmission models of respiratory pathogens in high-transmission settings, which are valuable for optimizing the delivery of different interventions.