Using wearable proximity sensors to characterize social contact patterns in a village of rural Malawi

Laura Ozella,Jorge P Rodríguez,Simon Haenni,Guilherme Lichand,John Phuka,Onicio B Leal-Neto,Ciro Cattuto,Daniela Paolotti

doi:10.1140/epjds/s13688-021-00302-w

Laura Ozella, Jorge P Rodríguez + Show 6 more

Open Access

https://doi.org/10.1140/epjds/s13688-021-00302-w

Copy DOI

Abstract

Measuring close proximity interactions between individuals can provide key information on social contacts in human communities and related behaviours. This is even more essential in rural settings in low- and middle-income countries where there is a need to understand contact patterns for the implementation of strategies for social protection interventions. We report the quantitative assessment of contact patterns in a village in rural Malawi, based on proximity sensors technology that allows for high-resolution measurements of social contacts. Our results revealed that the community structure of the village was highly correlated with the household membership of the individuals, thus confirming the importance of the family ties within the village. Social contacts within households occurred mainly between adults and children, and adults and adolescents and most of the inter-household social relationships occurred among adults and among adolescents. At the individual level, age and gender social assortment were observed in the inter-household network, and age disassortativity was instead observed in intra-household networks. Moreover, we obtained a clear trend of the daily contact activity of the village. Family members congregated in the early morning, during lunch time and dinner time. In contrast, inter-household contact activity displayed a growth from the morning, reaching a maximum in the afternoon.The proximity sensors technology used in this study provided high resolution temporal data characterized by timescales comparable with those intrinsic to social dynamics and it thus allowed to have access to the level of information needed to understand the social context of the village.

Highlights

Describing close proximity interactions allows to create contact networks representing frequency of social contacts in human communities
We measured group-level patterns by testing for community structure in the whole social network of the village, and we evaluated the performance of a community detection algorithm by their ability to find so-called ground truth communities, and the goal is to find communities that align with age, gender or household membership
We studied the intra-household contact data when the family members wore sensors simultaneously, and this overlapping deployment period was different according to the household

Summary

Introduction

Describing close proximity interactions allows to create contact networks representing frequency of social contacts in human communities. Contact network analysis can be used to better understand social interaction patterns and related behaviours (Borgatti et al [3]; Chami et al [8]) and the transmission of diseases (Funk, et al [17]; Danon et al [12]). (2021) 10:46 lecting high resolution data on the contact rates between individuals is a major challenge in most settings, in rural low- and middle-income areas. Many infectious diseases have emerged or re-emerged in rural low- and middle-income settings in the last century (Fenollar et al [15]). Of these harder to reach populations, in stochastic models of transmissible diseases could help better predict epidemics and has utility in the design of preventive and control measures such as vaccination and social distancing (Mossong et al [35]; Salathé et al [41])

Objectives

Methods

Results

Discussion

Conclusion