Social Mixing Patterns in Rural India

2017 
An important input into mathematical models of respiratory infection transmission is the contact duration and rate between people—i.e. who mixes with whom. These rates differ by age of the respondent in all studies to-date. Evidence regarding differences in contact rates by gender and day of the week is available from some locations, and the patterns appear to differ by region or country. In a rural Indian location with known gender hierarchies, low formal employment rates among women, and large household sizes, it is unknown if contact rates are different by the day of the week. This study uses social contact data from 2943 individuals, in 5 villages of the Faridabad district of Haryana, India. Respondents were interviewed on one day from October 20, 2015 to February 29, 2016 about their contacts on the previous day. We examined the differences in the total daily number of contacts per respondent and the total duration spent with others per respondent by different day-types (Sunday vs weekday, holidays vs. non-holidays, school break periods vs non-break periods, and self-reported atypical days vs typical days), sex, and age group. We found that school-aged individuals had more contacts and contact duration on weekdays than Sundays. Females aged 0-4 and 20-59 had more contacts on school break days than on non-school break days, and females ages 20-59 had greater contact duration on school break days. Holidays were not found to be a significant predictor of contact duration or number of contacts. Finally, there were significant differences between different typical and atypical day types, as well as by age category, warranting further investigation into self-reported atypical days as a significant modeling variable. These results expand on existing literature regarding social mixing variation by sex, day type, and age, and can be used to better inform models of respiratory infection transmission. Such models are of great public health significance in their potential to evaluate the efficacy of interventions aimed at limiting the spread of infectious diseases.
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