# Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries

> **NIH NIH R01** · EMORY UNIVERSITY · 2021 · $528,353

## Abstract

PROJECT SUMMARY/ABSTRACT
Dynamic transmission models of infectious diseases are increasingly influential for
developing interventions and informing policy. Infectious disease transmissibility and
hence, the effectiveness of control strategies, is strongly influenced by social
interactions. Consequently, accurate data on social contact rates and mixing patterns
are fundamental parameters in the calculation of the force of infection (i.e. the rate of
susceptible individuals becoming infected). Despite the strong role social mixing
patterns play in the accurate parameterization of mathematical models, these data
remain limited, particularly in low and middle-income countries (LMICs). There are also
limited data on the social interactions of young infants that are too young to be
vaccinated or the diversity in patterns between rural and urban populations at the
community level, which are important factors for understanding infectious disease
transmission.
We propose the first multi-site study with the overall goal to use standardized methods to
collect social contact data from urban and rural populations in LMICs. Special focus will
be given to study the social interactions of infants less than six months of age. Data will
be rigorously collected from four different LMICs: Guatemala, Pakistan, India and
Mozambique. We will use standardized social contact diaries to characterize the patterns
of social contacts and mixing across the age range in urban and rural LMIC settings. We
will also comprehensively profile the social contacts of infants with their household
members in LMICs by analyzing high resolution measurements collected using wearable
proximity-sensing devices.
Moreover, through this project, we will create a database of social mixing data on LMIC
populations. We will make this database publicly available using contemporary standards
in Open Access data sharing and documentation. These data can be used by infectious
disease modelers and other researchers in the biomedical and social science
communities.

## Key facts

- **NIH application ID:** 10148557
- **Project number:** 5R01HD097175-03
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Benjamin A Lopman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $528,353
- **Award type:** 5
- **Project period:** 2019-06-19 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10148557

## Citation

> US National Institutes of Health, RePORTER application 10148557, Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries (5R01HD097175-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10148557. Licensed CC0.

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