Evaluating tuberculosis service accessibility in Pakistan by analyzing population movement patterns from telecom...

Geographical distance is an important dimension of access to healthcare and is considered in a wide range of settings to aid strategic planning and evaluation of healthcare interventions. Evidence has shown that in addition to geographic distance, multiple factors influence the travel behavior of people seeking health services. Yet most studies have largely framed the issue from the perspective of how far people should travel, while few have explained how far people actually travel, thereby overlooking potential insights into travel behaviors.

In this research, we used in-person interviews, telecom mobility data, and spatial analysis to estimate peoples' accessibility to TB service points in Pakistan. Characteristics of TB service points, including sector (public versus private), urbanicity, socioeconomic class, and administrative province were further analyzed for their association with TB service accessibility. We constructed decay curves to compare the accessibility rates obtained from in-person interviews among people visiting TB service points with those derived from telecom mobility data. We applied generalized linear models to assess whether these measured population movements to TB service points differ by data source, and to explore associations with the TB service point characteristics.

Our results show that significant variations in TB service accessibility are associated with administrative provinces, and the density of TB service points. We found a significant difference between the geographic accessibility measured by the two data sources across distance bands. We also found that relative, and not absolute, TB service accessibility is similar across both data sources. However there is a steeper decay curve in the interview data, reflecting lower accessibility at each successively distal distance band relative to the telecom mobility data.

While telecom mobility data and survey data capture different population movement patterns, both provide insights which may help to align service availability with population needs. These findings are highly relevant for the geoprioritization of TB case-finding services, the efficacy of which hinge on early and efficient screening and diagnosis.