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      The impact of HIV and tuberculosis interventions on South African adult tuberculosis trends, 1990-2019: a mathematical modeling analysis

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          Highlights

          • We developed a tuberculosis (TB) transmission dynamic model for South Africa.

          • We quantified TB incidence and mortality attributable to HIV between 1990 and 2019.

          • We estimated the impact of TB programmatic interventions on TB incidence between 1996 and 2019.

          • A significant proportion of TB incidence and mortality was attributable to HIV.

          • TB screening and antiretroviral therapy led to substantial TB incidence reductions.

          Abstract

          Objectives

          To quantify the South African adult tuberculosis (TB) incidence and mortality attributable to HIV between 1990 and 2019 and to estimate the reduction in TB incidence due to directly observed therapy, antiretroviral therapy (ART), isoniazid preventive therapy, increased TB screening, and Xpert MTB/RIF.

          Methods

          We developed a dynamic TB transmission model for South Africa. A Bayesian approach was used to calibrate the model to South African-specific data sources. Counterfactual scenarios were simulated to estimate TB incidence and mortality attributable to HIV and the impact of interventions on TB incidence.

          Results

          Between 1990 and 2019, 8.8 million (95% confidence interval [CI] 8.3-9.3 million) individuals developed TB, and 2.1 million (95% CI 2.0-2.2 million) died from TB. A total of 55% and 69% of TB cases and mortality were due to HIV, respectively. Overall, TB screening and ART substantially reduced TB incidence by 28.2% (95% CI 26.4-29.8%) and 20.0% (95% CI 19.2-20.7%), respectively, in 2019; other interventions had minor impacts.

          Conclusion

          HIV has dramatically increased TB incidence and mortality in South Africa. The provision of ART and intensification of TB screening explained most recent declines in TB incidence.

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          Most cited references35

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          HIV infection and tuberculosis in South Africa: an urgent need to escalate the public health response.

          One of the greatest challenges facing post-apartheid South Africa is the control of the concomitant HIV and tuberculosis epidemics. HIV continues to spread relentlessly, and tuberculosis has been declared a national emergency. In 2007, South Africa, with 0.7% of the world's population, had 17% of the global burden of HIV infection, and one of the world's worst tuberculosis epidemics, compounded by rising drug resistance and HIV co-infection. Until recently, the South African Government's response to these diseases has been marked by denial, lack of political will, and poor implementation of policies and programmes. Nonetheless, there have been notable achievements in disease management, including substantial improvements in access to condoms, expansion of tuberculosis control efforts, and scale-up of free antiretroviral therapy (ART). Care for acutely ill AIDS patients and long-term provision of ART are two issues that dominate medical practice and the health-care system. Decisive action is needed to implement evidence-based priorities for the control of the HIV and tuberculosis epidemics. By use of the framework of the Strategic Plans for South Africa for tuberculosis and HIV/AIDS, we provide prioritised four-step approaches for tuberculosis control, HIV prevention, and HIV treatment. Strong leadership, political will, social mobilisation, adequate human and financial resources, and sustainable development of health-care services are needed for successful implementation of these approaches.
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            The growing burden of tuberculosis: global trends and interactions with the HIV epidemic.

            The increasing global burden of tuberculosis (TB) is linked to human immunodeficiency virus (HIV) infection. We reviewed data from notifications of TB cases, cohort treatment outcomes, surveys of Mycobacterium tuberculosis infection, and HIV prevalence in patients with TB and other subgroups. Information was collated from published literature and databases held by the World Health Organization (WHO), the Joint United Nations Programme on HIV/Acquired Immunodeficiency Syndrome (UNAIDS), the US Census Bureau, and the US Centers for Disease Control and Prevention. There were an estimated 8.3 million (5th-95th centiles, 7.3-9.2 million) new TB cases in 2000 (137/100,000 population; range, 121/100,000-151/100,000). Tuberculosis incidence rates were highest in the WHO African Region (290/100,000 per year; range, 265/100,000-331/100,000), as was the annual rate of increase in the number of cases (6%). Nine percent (7%-12%) of all new TB cases in adults (aged 15-49 years) were attributable to HIV infection, but the proportion was much greater in the WHO African Region (31%) and some industrialized countries, notably the United States (26%). There were an estimated 1.8 million (5th-95th centiles, 1.6-2.2 million) deaths from TB, of which 12% (226 000) were attributable to HIV. Tuberculosis was the cause of 11% of all adult AIDS deaths. The prevalence of M tuberculosis-HIV coinfection in adults was 0.36% (11 million people). Coinfection prevalence rates equaled or exceeded 5% in 8 African countries. In South Africa alone there were 2 million coinfected adults. The HIV pandemic presents a massive challenge to global TB control. The prevention of HIV and TB, the extension of WHO DOTS programs, and a focused effort to control HIV-related TB in areas of high HIV prevalence are matters of great urgency.
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              Short-term and long-term risk of tuberculosis associated with CD4 cell recovery during antiretroviral therapy in South Africa.

              To determine the short-term and long-term risks of tuberculosis (TB) associated with CD4 cell recovery during antiretroviral therapy (ART). Observational community-based ART cohort in South Africa. TB incidence was determined among patients (n = 1480) receiving ART for up to 4.5 years in a South African community-based service. Updated CD4 cell counts were measured 4-monthly. Person-time accrued within a range of CD4 cell count strata (CD4 cell strata) was calculated and used to derive CD4 cell-stratified TB rates. Factors associated with incident TB were identified using Poisson regression models. Two hundred and three cases of TB were diagnosed during 2785 person-years of observation (overall incidence, 7.3 cases/100 person-years). During person-time accrued within CD4 cell strata 0-100, 101-200, 201-300, 301-400, 401-500 and more than 500 cells/microl unadjusted TB incidence rates were 16.8, 9.3, 5.5, 4.6, 4.2 and 1.5 cases/100 person-years, respectively (P < 0.001). During early ART (first 4 months), adjusted TB rates among those with CD4 cell counts 0-200 cells/microl were 1.7-fold higher than during long-term ART (P = 0.026). Updated CD4 cell counts were the only patient characteristic independently associated with long-term TB risk. Updated CD4 cell counts were the dominant predictor of TB risk during ART in this low-resource setting. Among those with baseline CD4 cell counts less than 200 cells/microl, the excess adjusted risk of TB during early ART was consistent with 'unmasking' of disease missed at baseline screening. TB incidence rates at CD4 cell counts of 200-500 cells/microl remained high and adjunctive interventions are required. TB prevention would be improved by ART policies that minimized the time patients spend with CD4 cell counts below a threshold of 500 cells/microl.
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                Author and article information

                Contributors
                Journal
                Int J Infect Dis
                Int J Infect Dis
                International Journal of Infectious Diseases
                Elsevier
                1201-9712
                1878-3511
                1 September 2022
                September 2022
                : 122
                : 811-819
                Affiliations
                [1 ]Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
                [2 ]Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
                [3 ]School of Human Sciences, Faculty of Education, Health and Human Sciences, University of Greenwich, London, United Kingdom
                [4 ]Western Cape Provincial Department of Health, Cape Town, South Africa
                Author notes
                [* ]Correspondence to: Associate Professor Leigh F. Johnson, Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, South Africa, Telephone: +27 21 406 6981. leigh.johnson@ 123456uct.ac.za
                Article
                S1201-9712(22)00438-6
                10.1016/j.ijid.2022.07.047
                9439958
                35872098
                504b279f-dc1d-40ca-82f2-a4b6ef9cebae
                © 2022 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 May 2022
                : 14 July 2022
                : 18 July 2022
                Categories
                Article

                Infectious disease & Microbiology
                mathematical modeling,tuberculosis,human immunodeficiency virus,tuberculosis programmatic interventions,south africa

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