title: How can mathematical models advance tuberculosis control in high HIV prevalence settings?
abstract: Existing approaches to tuberculosis (TB) control have been no more than partially successful in areas with high human immunodeficiency virus (HIV) prevalence. In the context of increasingly constrained resources, mathematical modelling can augment understanding and support policy for implementing those strategies that are most likely to bring public health and economic benefits. In this paper, we present an overview of past and recent contributions of TB modelling in this key area, and suggest a way forward through a modelling research agenda that supports a more effective response to the TB-HIV epidemic, based on expert discussions at a meeting convened by the TB Modelling and Analysis Consortium. The research agenda identified high-priority areas for future modelling efforts, including 1) the difficult diagnosis and high mortality of TB-HIV; 2) the high risk of disease progression; 3) TB health systems in high HIV prevalence settings; 4) uncertainty in the natural progression of TB-HIV; and 5) combined interventions for TB-HIV. Efficient and rapid progress towards completion of this modelling agenda will require co-ordination between the modelling community and key stakeholders, including advocates, health policy makers, donors and national or regional finance officials. A continuing dialogue will ensure that new results are effectively communicated and new policy-relevant questions are addressed swiftly.
authors.affiliation: TB Modelling Group, TB Centre, and Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine (LSHTM), London, UK.
authors.forename: R M G J
authors.initials: RM
authors.lastname: Houben
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
authors.forename: D W
authors.initials: DW
authors.lastname: Dowdy
authors.affiliation: Department of Global Health and Development, LSHTM, London, UK.
authors.forename: A
authors.initials: A
authors.lastname: Vassall
authors.affiliation: Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: T
authors.initials: T
authors.lastname: Cohen
authors.affiliation: Division of Medical Microbiology and Institute of Infectious Diseases and Molecular Medicine, University of Cape Town and National Health Laboratory Service, South Africa.
authors.forename: M P
authors.initials: MP
authors.lastname: Nicol
authors.affiliation: Joint United Nations Programme on HIV/AIDS, World Health Organization (WHO), Geneva, Switzerland.
authors.forename: R M
authors.initials: RM
authors.lastname: Granich
authors.affiliation: Oxford-Emergent Tuberculosis Consortium, Wokingham, UK.
authors.forename: J E
authors.initials: JE
authors.lastname: Shea
authors.affiliation: Intellectual Ventures Laboratory, Bellevue, Washington, USA.
authors.forename: P
authors.initials: P
authors.lastname: Eckhoff
authors.affiliation: HIV, TB Malaria and Neglected Tropical Diseases Cluster, WHO, Geneva, Switzerland.
authors.forename: C
authors.initials: C
authors.lastname: Dye
authors.affiliation: Bill and Melinda Gates Foundation, Seattle, Washington, USA.
authors.forename: M E
authors.initials: ME
authors.lastname: Kimerling
authors.affiliation: TB Modelling Group, TB Centre, and Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine (LSHTM), London, UK.
authors.forename: R G
authors.initials: RG
authors.lastname: White
mesh_terms: D019380:Anti-HIV Agents / Q000627:therapeutic use; D000995:Antitubercular Agents / Q000627:therapeutic use*; D060085:Coinfection; D003661:Decision Support Techniques; D058872:Epidemics / Q000517:prevention & control*; D015658:HIV Infections / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology*; D006292:Health Priorities; D006297:Health Services Accessibility; D006301:Health Services Needs and Demand; D006801:Humans; D008962:Models, Theoretical; D020380:Needs Assessment; D015995:Prevalence; D016896:Treatment Outcome; D014376:Tuberculosis / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission
chemical_list: D019380:Anti-HIV Agents; D000995:Antitubercular Agents