Seasonal variations in social contact patterns in a rural population in north India: Implications for pandemic control

• Published in: PloS one 2024-02, Vol.19 (2), p.e0296483-e0296483
• Main Authors: Nagpal, Sargun, Kumar, Rakesh, Noronha, Riz Fernando, Kumar, Supriya, Gupta, Debayan, Amarchand, Ritvik, Gosain, Mudita, Sharma, Hanspria, Menon, Gautam I, Krishnan, Anand
• Format: Article
• Language: English
• Subjects: Analysis; Communicable diseases; Computer and Information Sciences; Control; Disease transmission; Earth Sciences; Epidemics; Epidemiology; Health aspects; India; Medicine and Health Sciences; People and Places; Physical Sciences; Prevention; Research and Analysis Methods; Social networks; Social Sciences; Surveys
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0296483

Social contact mixing patterns are critical to model the transmission of communicable diseases, and have been employed to model disease outbreaks including COVID-19. Nonetheless, there is a paucity of studies on contact mixing in low and middle-income countries such as India. Furthermore, mathematical models of disease outbreaks do not account for the temporal nature of social contacts. We conducted a longitudinal study of social contacts in rural north India across three seasons and analysed the temporal differences in contact patterns. A contact diary survey was performed across three seasons from October 2015-16, in which participants were queried on the number, duration, and characteristics of contacts that occurred on the previous day. A total of 8,421 responses from 3,052 respondents (49% females) recorded characteristics of 180,073 contacts. Respondents reported a significantly higher number and duration of contacts in the winter, followed by the summer and the monsoon season (Nemenyi post-hoc, p80%) of contacts that were reported in schools or on public transport involved physical contact. To the best of our knowledge, our study is the first from India to show that contact mixing patterns vary by the time of the year and provides useful implications for pandemic control. We compared the differences in the number, duration and location of contacts by age-group and gender, and studied the impact of the season, age-group, employment and day of the week on the number and duration of contacts using multivariate negative binomial regression. We created a social network to further understand the age and gender-specific contact patterns, and used the contact matrices in each season to parameterise a nine-compartment agent-based model for simulating a COVID-19 epidemic in each season. Our results can be used to parameterize more accurate mathematical models for prediction of epidemiological trends of infections in rural India.