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

BackgroundGold 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.MethodsWe 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.ResultsWe 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.ConclusionsGold 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.

[1]  D. Kielkowski,et al.  Occupational disease trends in black South African gold miners. An autopsy-based study. , 1996, American journal of respiratory and critical care medicine.

[2]  M. Egger,et al.  Tuberculosis in Cape Town: An age-structured transmission model. , 2016, Epidemics.

[3]  A. Vassall,et al.  How can mathematical models advance tuberculosis control in high HIV prevalence settings? , 2014, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[4]  S. Lawn,et al.  Tuberculosis in a South African prison - a transmission modelling analysis. , 2011, South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde.

[5]  J. Hargrove,et al.  Tuberculosis transmission to young children in a South African community: modeling household and community infection risks. , 2010, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[6]  M. Behr,et al.  Transmission of tuberculosis in a high incidence urban community in South Africa. , 2004, International journal of epidemiology.

[7]  B. Girdler-brown,et al.  Three Decades of Silicosis: Disease Trends at Autopsy in South African Gold Miners , 2009, Environmental health perspectives.

[8]  S. Rosen,et al.  Prevalence of HIV in workforces in southern Africa, 2000-2001. , 2004, South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde.

[9]  M. Begon,et al.  A clarification of transmission terms in host-microparasite models: numbers, densities and areas , 2002, Epidemiology and Infection.

[10]  L. Myer,et al.  Rates of tuberculosis transmission to children and adolescents in a community with a high prevalence of HIV infection among adults. , 2008, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[11]  P. Sonnenberg,et al.  Oscillating migration and the epidemics of silicosis, tuberculosis, and HIV infection in South African gold miners. , 2009, American journal of industrial medicine.

[12]  G. Churchyard,et al.  Silicosis prevalence and exposure-response relations in South African goldminers , 2004, Occupational and Environmental Medicine.

[13]  R. Gie,et al.  No decrease in annual risk of tuberculosis infection in endemic area in Cape Town, South Africa , 2009, Tropical medicine & international health : TM & IH.

[14]  L. Johnson,et al.  Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa , 2017, Southern African journal of HIV medicine.

[15]  Philip A. Eckhoff,et al.  Targeting HIV services to male migrant workers in southern Africa would not reverse generalized HIV epidemics in their home communities: a mathematical modeling analysis , 2015, International health.

[16]  S. Basu,et al.  The production of consumption: addressing the impact of mineral mining on tuberculosis in southern Africa , 2009, Globalization and health.

[17]  Jason R Andrews,et al.  Modeling the role of public transportation in sustaining tuberculosis transmission in South Africa. , 2013, American journal of epidemiology.

[18]  R. Chaisson,et al.  Thibela TB: design and methods of a cluster randomised trial of the effect of community-wide isoniazid preventive therapy on tuberculosis amongst gold miners in South Africa. , 2011, Contemporary clinical trials.

[19]  P. Kaye Infectious diseases of humans: Dynamics and control , 1993 .

[20]  L. Corno,et al.  Mines, Migration and HIV/AIDS in Southern Africa , 2012 .

[21]  Ziv Shkedy,et al.  Modeling Infectious Disease Parameters Based on Serological and Social Contact Data , 2012 .

[22]  J. Sterne,et al.  Protection by BCG vaccine against tuberculosis: a systematic review of randomized controlled trials. , 2014, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[23]  Christophe Fraser,et al.  Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era. , 2015, The Lancet. Global health.

[24]  C. Sismanidis,et al.  Annual Risk of Tuberculous Infection Using Different Methods in Communities with a High Prevalence of TB and HIV in Zambia and South Africa , 2009, PloS one.

[25]  S. Dorman,et al.  Molecular epidemiology of Mycobacterium tuberculosis among South African gold miners. , 2015, Annals of the American Thoracic Society.

[26]  L. Gammaitoni,et al.  Using a mathematical model to evaluate the efficacy of TB control measures. , 1997, Emerging infectious diseases.

[27]  D. Labadarios,et al.  South African National HIV Prevalence, Incidence and Behaviour Survey, 2012 , 2014 .

[28]  R. Hayes,et al.  Stable incidence rates of tuberculosis (TB) among human immunodeficiency virus (HIV)-negative South African gold miners during a decade of epidemic HIV-associated TB. , 2003, The Journal of infectious diseases.

[29]  Adrian E Raftery,et al.  Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling , 2010, Biometrics.

[30]  S. Lawn,et al.  Changing prevalence of tuberculosis infection with increasing age in high-burden townships in South Africa. , 2010, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[31]  S. Basu,et al.  Introduction: ‘Dying for Gold’: The Effects of Mineral Miningon HIV, Tuberculosis, Silicosis, and Occupational Diseases in Southern Africa , 2013, International journal of health services : planning, administration, evaluation.

[32]  R. White,et al.  Post-treatment effect of isoniazid preventive therapy on tuberculosis incidence in HIV-infected individuals on antiretroviral therapy , 2016, AIDS.

[33]  N. Mcglashan,et al.  Changes in the geographical and temporal patterns of cancer incidence among black gold miners working in South Africa, 1964–1996 , 2003, British Journal of Cancer.

[34]  Christopher Dye,et al.  The growing burden of tuberculosis: global trends and interactions with the HIV epidemic. , 2003, Archives of internal medicine.

[35]  Richard G. White,et al.  Tuberculosis Prevention in South Africa , 2015, PloS one.

[36]  Richard G. White,et al.  Impact and cost-effectiveness of current and future tuberculosis diagnostics: the contribution of modelling , 2014, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[37]  L. Myer,et al.  Transmission of tuberculosis in a South African community with a high prevalence of HIV infection. , 2015, The Journal of infectious diseases.

[38]  R. Chaisson,et al.  A trial of mass isoniazid preventive therapy for tuberculosis control. , 2014, The New England journal of medicine.

[39]  D. Celentano,et al.  Does marital status matter in an HIV hyperendemic country? Findings from the 2012 South African National HIV Prevalence, Incidence and Behaviour Survey , 2016, AIDS care.

[40]  Philip A. Eckhoff,et al.  Description of the EMOD-HIV Model v0:7 , 2012, 1206.3720.

[41]  D. Chin,et al.  Tuberculosis control strategies to reach the 2035 global targets in China: the role of changing demographics and reactivation disease , 2015, BMC Medicine.

[42]  Andreas Handel,et al.  Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: a combined analysis of 11 mathematical models , 2016, The Lancet. Global health.

[43]  Valeria Saraceni,et al.  Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics , 2012, Proceedings of the National Academy of Sciences.

[44]  Richard G. White,et al.  Tuberculosis Control in South African Gold Mines: Mathematical Modeling of a Trial of Community-Wide Isoniazid Preventive Therapy , 2015, American journal of epidemiology.

[45]  D. Westreich,et al.  Prevalence of latent tuberculosis infection and predictive factors in an urban informal settlement in Johannesburg, South Africa: a cross-sectional study , 2016, BMC Infectious Diseases.

[46]  P. Sonnenberg,et al.  Tuberculosis control and molecular epidemiology in a South African gold-mining community , 2000, The Lancet.

[47]  M. Mckee,et al.  Mining and risk of tuberculosis in sub-Saharan Africa. , 2011, American journal of public health.

[48]  P. V. van Helden,et al.  Historic and recent events contribute to the disease dynamics of Beijing-like Mycobacterium tuberculosis isolates in a high incidence region. , 2002, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[49]  Alimuddin Zumla,et al.  The WHO 2014 global tuberculosis report--further to go. , 2015, The Lancet. Global health.