Small contribution of gold mines to the ongoing tuberculosis epidemic in South Africa: a modeling-based study

April 12, 2018


Gold mines represent a potential hotspot for Mycobacterium tuberculosis (Mtb) transmission and may be exacerbating the tuberculosis (TB) epidemic in South Africa. However, the presence of multiple factors complicates estimation of the mining contribution to the TB burden in South Africa.


We developed two models of TB in South Africa, a static risk model and an individual-based model that accounts for longer-term trends. Both models account for four populations — mine workers, peri-mining residents, labor-sending residents, and other residents of South Africa — including the size and prevalence of latent TB infection, active TB, and HIV of each population and mixing between populations. We calibrated to mine- and country-level data and used the static model to estimate force of infection (FOI) and new infections attributable to local residents in each community compared to other residents. Using the individual-based model, we simulated a counterfactual scenario to estimate the fraction of overall TB incidence in South Africa attributable to recent transmission in mines.


We estimated that the majority of FOI in each community is attributable to local residents: 93.9% (95% confidence interval 92.4–95.1%), 91.5% (91.4–91.5%), and 94.7% (94.7–94.7%) in gold mining, peri-mining, and labor-sending communities, respectively. Assuming a higher rate of Mtb transmission in mines, 4.1% (2.6–5.8%), 5.0% (4.5–5.5%), and 9.0% (8.8–9.1%) of new infections in South Africa are attributable to gold mine workers, peri-mining residents, and labor-sending residents, respectively. Therefore, mine workers with TB disease, who constitute ~ 2.5% of the prevalent TB cases in South Africa, contribute 1.62 (1.04–2.30) times as many new infections as TB cases in South Africa on average. By modeling TB on a longer time scale, we estimate 63.0% (58.5–67.7%) of incident TB disease in gold mining communities to be attributable to recent transmission, of which 92.5% (92.1–92.9%) is attributable to local transmission.

Fig. 2

Simulated time series of the TB epidemic in different communities in South Africa. Means and 95% CIs were derived from 200 stochastic realizations of the model where input parameters were set at the mode of the posterior distribution of two calibration parameters. a TB incidence in peri-mining, labor-sending, and other South Africa residents. b TB mortality in peri-mining, labor-sending, and other South Africa residents. In a and b, the population-weighted mean of the four populations in the model is also shown. c TB incidence in mine workers. d TB mortality in mine workers. e Methodology for computing the fraction of incidence attributable to recent Mtb transmission in the mines. The upper curve is identical to the curve in c, while the lower curve represents the mean and 95% CI of stochastic realizations that were identical to c until simulated year 2012, after which Mtb transmission from mine workers was stopped but all other aspects of the model remained unchanged. Attribution was calculated from the difference in incidence between simulated years 2014 and 2019


Gold mine workers are estimated to contribute a disproportionately large number of Mtb infections in South Africa on a per-capita basis. However, mine workers contribute only a small fraction of overall Mtb infections in South Africa. Our results suggest that curtailing transmission in mines may have limited impact at the country level, despite potentially significant impact at the mining level.