Background: The potential epidemiological impact of isoniazid preventive therapy (IPT), delivered at levels that could be feasibly scaled up among people living with HIV (PLHIV) in modern, moderate-burden settings, remains uncertain.
Methods: We used routine surveillance and implementation data from a cluster-randomized trial of IPT among HIV-infected clinic patients with good access to antiretroviral therapy in Rio de Janeiro, Brazil, to populate a parsimonious transmission model of tuberculosis (TB)/HIV. We modeled IPT delivery as a constant process capturing a proportion of the eligible population every year. We projected feasible reductions in TB incidence and mortality in the general population and among PLHIV specifically at the end of 5 years after implementing an IPT program.
Results: Data on time to IPT fit an exponential curve well, suggesting that IPT was delivered at a rate covering 20% (95% confidence interval: 16% to 24%) of the 2500 eligible individuals each year. By the end of year 5 after modeled program rollout, IPT had reduced TB incidence by 3.0% [95% uncertainty range (UR): 1.6% to 7.2%] in the general population and by 15.6% (95% UR: 15.5% to 36.5%) among PLHIV. Corresponding reductions in TB mortality were 4.0% (95% UR: 2.2% to 10.3%) and 14.3% (14.6% to 33.7%). Results were robust to wide variations in parameter values on sensitivity analysis.
Conclusions: TB screening and IPT delivery can substantially reduce TB incidence and mortality among PLHIV in urban, moderate-burden settings. In such settings, IPT can be an important component of a multi-faceted strategy to feasibly reduce the burden of TB in PLHIV.
*Center for Tuberculosis Research, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD;
†Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD;
‡Subsecretariat for Primary Care, Surveillance, and Health Promotion, Municipal Health Secretariat, Rio de Janeiro, Brazil;
§Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD;
‖Program of Scientific Computing, Fiocruz, Rio de Janeiro, Brazil;
¶Evandro Chagas Institute of Clinical Research, Fiocruz, Rio de Janeiro, Brazil; and
#Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Correspondence to: David W. Dowdy, MD, PhD, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, E6531, Baltimore, MD 21205 (e-mail: firstname.lastname@example.org).
Supported by the Bill and Melinda Gates Foundation, Grant 19790.01, and by the National Institutes of Health, Grants AI1066994 and AI001637. Dr. Pacheco also acknowledges support from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and FAPERJ (Fundação Carlos Chagas Filho de Apoio a Pesquisa do Estado do Rio de Janeiro).
Presented in part at the 43rd World Lung Conference, November 13–17, 2012, Kuala Lumpur, Malaysia.
The authors have no conflicts of interest to disclose.
D.W.D., J.E.G., L.H.M., R.E.C., and B.D. developed the study concept. D.W.D. wrote the model code and performed all analyses. V.S., S.C.C., and S.C. collected the corresponding field data. J.E.G., L.H.M., and A.G.P. provided statistical support. D.W.D. wrote the first draft, which was revised by J.E.G., V.S., and L.H.M. All authors saw and approved the final manuscript version.
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Received January 12, 2014
Accepted May 05, 2014