Tracking individuals through time to find TB transmission hot-spots in South Africa
Tuberculosis kills more than 4,200 people worldwide every day, and South Africa has one of the highest TB incidence rates in the world. Like COVID-19, tuberculosis (TB) is a highly infectious respiratory virus transmitted through the air; however, it is not nearly as widespread as the SARS-CoV-2 virus.
Based on routinely collected data, it is evident TB is disproportionately concentrated among regions. Coinciding with other age-, gender-, and race-specific disparities, investigating the spatial component of TB can better inform strategies for implementing effective TB interventions and treatment.
Dr. Helen Jenkins, Associate Professor, and researcher at Boston University’s School of Public Health, is leading a project in the Western Cape of South Africa focused on understanding the hot spots of high TB transmission. This vital work highlights priority locations for targeted interventions to prevent further transmission.
While detailed data to understand the epidemiology of the TB epidemic in South Africa are still needed, all laboratory test results are currently stored in the National Health Laboratory Service dataset (NHLS). However, this dataset is not typically used for research projects, nor does it include unique identifiers, which makes tracking infectious diseases around the country difficult. Through BUSPH idea hub pilot funding, Dr. Helen Jenkins and her PhD research assistant, Sarah Van Ness, will demonstrate how the NHLS data can be used to identify individuals with TB who might be infected and where they are located.
By aggregating these data, they are working to identify geographic hotspots of potential TB transmission. Since this data is routinely collected, their work could ultimately become a tool to monitor hotspots of TB transmission in real-time. Since the pilot funding, they have worked with other BUSPH researchers to link Dr. Jenkins TB NHLS data with HIV tracking data to monitor these co-epidemics simultaneously as well as to study the link between HIV and diabetes. This research has the potential to open more doors for similar tracking models to monitor other infectious diseases as well.