Systems Model for Predicting Climate-Related Tuberculosis Surge Risk in Western Cape Migrant Settlements

This 24-month research project investigates the escalating risk of Tuberculosis (TB) in South Africa’s Western Cape (WC) due to the combined pressures of climate-driven factors and human migration. Seasonal and long-term climatic changes significantly impact communicable diseases like TB, affecting vulnerable groups such as women given their constrained capacity to respond effectively. Health systems, particularly in large migrant settlements like Khayelitsha, lack the tools to anticipate and respond to unpredictable TB incidence surges driven.

The Western Cape faces a lot of risks:

  • A high TB burden, including a significant incidence of rifampicin-resistant TB (RR-TB).
  • High migration volume: about 1/6th of the annual in-migration to South Africa of (>500.000 people) from other African countries arrives in the WC.

Studies indicate a link between migration-adjusted TB prevalence and an increase in both drug-susceptible and RR-TB in South Africa, with a two-year dynamic lag.

Research Gap

The role of climate-driven events in TB incidence and prevalence is poorly known, despite evidence of climate-seasonality effects in parts of South Africa. No credible predictive tool yet exists to quantify and project current and future TB surges and their dynamics in WC, nor attribute surges to key drivers.

Dynamic Simulation Model (DSM)

To address this gap, we are developing an early warning technology using a dynamic simulation model (DSM) approach adapted from an existing prototype, to assist WC health authorities anticipate, mitigate and respond to TB surge risks in vulnerable groups such as women. This model will integrate:

  • Seasonal and long-term climate conditions
  • Population health
  • Migration trends
  • Genomic TB tracing data

This model combines diverse world-leading expertise with high potential to significantly advance surveillance and predictive approaches, transferable to many health risks in Southern Africa.

Core Hypothesis

The overall hypothesis is that a core set of data flowing from climate, migration and health surveillance efforts incorporated in a DSM framework can significantly improve the accuracy of projections of TB surge up to 2050, and enhance health outcomes for vulnerable groups such as women, especially in migratory situations.

Project Leadership

This project is a collaboration between Stellenbosch University and Ghent University, with the Principal Investigators (P.I.s) being:

  • Prof. Guy Midgley and Dr. Neville Sweijd (Stellenbosch University)
  • Dr. Charlotte Scheerens and dr. Els Bekaert (Ghent University)