Skip to main content
Top
Published in: BMC Medicine 1/2016

Open Access 01-12-2016 | Correspondence

TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions

Authors: R. M. G. J. Houben, M. Lalli, T. Sumner, M. Hamilton, D. Pedrazzoli, F. Bonsu, P. Hippner, Y. Pillay, M. Kimerling, S. Ahmedov, C. Pretorius, R. G. White

Published in: BMC Medicine | Issue 1/2016

Login to get access

Abstract

Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria).
TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response.
The explicit aim of TIME Impact’s user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general.
TIME Impact has been effectively applied in a variety of settings. In South Africa, it informed the first South African HIV and TB Investment Cases and successfully leveraged additional resources from the National Treasury at a time of austerity. In Ghana, a long-term TIME model-centred interaction with the NTP provided new insights into the local epidemiology and guided resource allocation decisions to improve impact.
Appendix
Available only for authorised users
Literature
1.
go back to reference World Health Organisation. Global Tuberculosis Report 2015. Geneva: WHO; 2015. World Health Organisation. Global Tuberculosis Report 2015. Geneva: WHO; 2015.
2.
go back to reference Lonnroth K, Glaziou P, Weil D, Floyd K, Uplekar M, Raviglione M. Beyond UHC: monitoring health and social protection coverage in the context of tuberculosis care and prevention. PLoS Med. 2014;11:e1001693.CrossRefPubMedPubMedCentral Lonnroth K, Glaziou P, Weil D, Floyd K, Uplekar M, Raviglione M. Beyond UHC: monitoring health and social protection coverage in the context of tuberculosis care and prevention. PLoS Med. 2014;11:e1001693.CrossRefPubMedPubMedCentral
3.
go back to reference Lonnroth K, Jaramillo E, Williams BG, Dye C, Raviglione M. Drivers of tuberculosis epidemics: the role of risk factors and social determinants. Soc Sci Med. 2009;68(12):2240–6.CrossRefPubMed Lonnroth K, Jaramillo E, Williams BG, Dye C, Raviglione M. Drivers of tuberculosis epidemics: the role of risk factors and social determinants. Soc Sci Med. 2009;68(12):2240–6.CrossRefPubMed
4.
go back to reference World Health Assembly. Post-2015 Global TB Strategy and Targets (A67/62). Geneva: WHO; 2014. World Health Assembly. Post-2015 Global TB Strategy and Targets (A67/62). Geneva: WHO; 2014.
5.
go back to reference Leach-Kemon K, Chou DP, Schneider MT, Tardif A, Dieleman JL, Brooks BP, et al. The global financial crisis has led to a slowdown in growth of funding to improve health in many developing countries. Health Aff. 2012;31(1):228–35.CrossRef Leach-Kemon K, Chou DP, Schneider MT, Tardif A, Dieleman JL, Brooks BP, et al. The global financial crisis has led to a slowdown in growth of funding to improve health in many developing countries. Health Aff. 2012;31(1):228–35.CrossRef
6.
go back to reference Garnett GP, Cousens S, Hallett TB, Steketee R, Walker N. Mathematical models in the evaluation of health programmes. Lancet. 2011;378(9790):515–25.CrossRefPubMed Garnett GP, Cousens S, Hallett TB, Steketee R, Walker N. Mathematical models in the evaluation of health programmes. Lancet. 2011;378(9790):515–25.CrossRefPubMed
7.
go back to reference Walker N, Tam Y, Friberg IK. Overview of the Lives Saved Tool (LiST). BMC Public Health. 2013;13 Suppl 3:S1.CrossRefPubMed Walker N, Tam Y, Friberg IK. Overview of the Lives Saved Tool (LiST). BMC Public Health. 2013;13 Suppl 3:S1.CrossRefPubMed
8.
go back to reference Brown JB, Russell A, Chan W, Pedula K, Aickin M. The global diabetes model: user friendly version 3.0. Diabetes Res Clin Pract. 2000;50 Suppl 3:S15–46.CrossRefPubMed Brown JB, Russell A, Chan W, Pedula K, Aickin M. The global diabetes model: user friendly version 3.0. Diabetes Res Clin Pract. 2000;50 Suppl 3:S15–46.CrossRefPubMed
9.
go back to reference Stover J, Johnson P, Hallett T, Marston M, Becquet R, Timaeus IM. The Spectrum projection package: improvements in estimating incidence by age and sex, mother-to-child transmission, HIV progression in children and double orphans. Sex Transm Infect. 2010;86 Suppl 2:ii16–21.PubMed Stover J, Johnson P, Hallett T, Marston M, Becquet R, Timaeus IM. The Spectrum projection package: improvements in estimating incidence by age and sex, mother-to-child transmission, HIV progression in children and double orphans. Sex Transm Infect. 2010;86 Suppl 2:ii16–21.PubMed
10.
go back to reference Stover J, McKinnon R, Winfrey B. Spectrum: a model platform for linking maternal and child survival interventions with AIDS, family planning and demographic projections. Int J Epidemiol. 2010;39 Suppl 1:i7–10.CrossRefPubMedPubMedCentral Stover J, McKinnon R, Winfrey B. Spectrum: a model platform for linking maternal and child survival interventions with AIDS, family planning and demographic projections. Int J Epidemiol. 2010;39 Suppl 1:i7–10.CrossRefPubMedPubMedCentral
11.
go back to reference OECD Development Assistance Committee. The Paris Declaration on Aid Effectiveness. Paris: OECD; 2005. OECD Development Assistance Committee. The Paris Declaration on Aid Effectiveness. Paris: OECD; 2005.
12.
go back to reference Knight GM, Dharan NJ, Fox GJ, Stennis N, Zwerling A, Khurana R, Dowdy DW. Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making. Int J Infect Dis. 2016;42:17–23.CrossRefPubMed Knight GM, Dharan NJ, Fox GJ, Stennis N, Zwerling A, Khurana R, Dowdy DW. Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making. Int J Infect Dis. 2016;42:17–23.CrossRefPubMed
13.
go back to reference Vassall A, van Kampen S, Sohn H, Michael JS, John KR, den Boon S, et al. Rapid diagnosis of tuberculosis with the Xpert MTB/RIF assay in high burden countries: a cost-effectiveness analysis. PLoS Med. 2011;8(11):e1001120.CrossRefPubMedPubMedCentral Vassall A, van Kampen S, Sohn H, Michael JS, John KR, den Boon S, et al. Rapid diagnosis of tuberculosis with the Xpert MTB/RIF assay in high burden countries: a cost-effectiveness analysis. PLoS Med. 2011;8(11):e1001120.CrossRefPubMedPubMedCentral
14.
go back to reference Menzies NA, Cohen T, Lin HH, Murray M, Salomon JA. Population health impact and cost-effectiveness of tuberculosis diagnosis with Xpert MTB/RIF: a dynamic simulation and economic evaluation. PLoS Med. 2012;9(11):e1001347.CrossRefPubMedPubMedCentral Menzies NA, Cohen T, Lin HH, Murray M, Salomon JA. Population health impact and cost-effectiveness of tuberculosis diagnosis with Xpert MTB/RIF: a dynamic simulation and economic evaluation. PLoS Med. 2012;9(11):e1001347.CrossRefPubMedPubMedCentral
15.
go back to reference Trauer JM, Denholm JT, McBryde ES. Construction of a mathematical model for tuberculosis transmission in highly endemic regions of the Asia-Pacific. J Theor Biol. 2014;358:74–84.CrossRefPubMed Trauer JM, Denholm JT, McBryde ES. Construction of a mathematical model for tuberculosis transmission in highly endemic regions of the Asia-Pacific. J Theor Biol. 2014;358:74–84.CrossRefPubMed
16.
go back to reference Sachdeva KS, Raizada N, Gupta RS, Nair SA, Denkinger C, Paramasivan CN, et al. The potential impact of up-front drug sensitivity testing on India’s epidemic of multi-drug resistant tuberculosis. PLoS One. 2015;10(7):e0131438.CrossRefPubMedPubMedCentral Sachdeva KS, Raizada N, Gupta RS, Nair SA, Denkinger C, Paramasivan CN, et al. The potential impact of up-front drug sensitivity testing on India’s epidemic of multi-drug resistant tuberculosis. PLoS One. 2015;10(7):e0131438.CrossRefPubMedPubMedCentral
17.
go back to reference Dowdy DW, Andrews JR, Dodd PJ, Gilman RH. A user-friendly, open-source tool to project impact and cost of diagnostic tests for tuberculosis. Elife. 2014;3:e02565.CrossRefPubMedCentral Dowdy DW, Andrews JR, Dodd PJ, Gilman RH. A user-friendly, open-source tool to project impact and cost of diagnostic tests for tuberculosis. Elife. 2014;3:e02565.CrossRefPubMedCentral
18.
go back to reference Nishikiori N, Van Weezenbeek C. Target prioritization and strategy selection for active case-finding of pulmonary tuberculosis: a tool to support country-level project planning. BMC Public Health. 2013;13:97.CrossRefPubMedPubMedCentral Nishikiori N, Van Weezenbeek C. Target prioritization and strategy selection for active case-finding of pulmonary tuberculosis: a tool to support country-level project planning. BMC Public Health. 2013;13:97.CrossRefPubMedPubMedCentral
20.
go back to reference Pretorius C, Glaziou P, Dodd PJ, White R, Houben R. Using the TIME model in Spectrum to estimate tuberculosis-HIV incidence and mortality. AIDS. 2014;28 Suppl 4:S477–87.CrossRefPubMedPubMedCentral Pretorius C, Glaziou P, Dodd PJ, White R, Houben R. Using the TIME model in Spectrum to estimate tuberculosis-HIV incidence and mortality. AIDS. 2014;28 Suppl 4:S477–87.CrossRefPubMedPubMedCentral
21.
go back to reference Dowdy DW, Dye C, Cohen T. Data needs for evidence-based decisions: a tuberculosis modeler’s ‘wish list’. Int J Tuberc Lung Dis. 2013;17(7):866–77.CrossRefPubMedPubMedCentral Dowdy DW, Dye C, Cohen T. Data needs for evidence-based decisions: a tuberculosis modeler’s ‘wish list’. Int J Tuberc Lung Dis. 2013;17(7):866–77.CrossRefPubMedPubMedCentral
22.
go back to reference Dodd PJ, Gardiner E, Coghlan R, Seddon JA. Burden of childhood tuberculosis in 22 high-burden countries: a mathematical modelling study. Lancet Glob Health. 2014;2(8):e453–9.CrossRefPubMed Dodd PJ, Gardiner E, Coghlan R, Seddon JA. Burden of childhood tuberculosis in 22 high-burden countries: a mathematical modelling study. Lancet Glob Health. 2014;2(8):e453–9.CrossRefPubMed
24.
go back to reference Buse K, Mays N, Walt G. Making Health Policy. London: Open University Press; 2005. Buse K, Mays N, Walt G. Making Health Policy. London: Open University Press; 2005.
25.
go back to reference Cookson R. Evidence-based policy making in health care: what it is and what it isn’t. J Health Serv Res Policy. 2005;10(2):118–21.CrossRefPubMed Cookson R. Evidence-based policy making in health care: what it is and what it isn’t. J Health Serv Res Policy. 2005;10(2):118–21.CrossRefPubMed
26.
go back to reference Basu S, Andrews JR, Poolman EM, Gandhi NR, Shah NS, Moll A, et al. Prevention of nosocomial transmission of extensively drug-resistant tuberculosis in rural South African district hospitals: an epidemiological modelling study. Lancet. 2007;370(9597):1500–7.CrossRefPubMedPubMedCentral Basu S, Andrews JR, Poolman EM, Gandhi NR, Shah NS, Moll A, et al. Prevention of nosocomial transmission of extensively drug-resistant tuberculosis in rural South African district hospitals: an epidemiological modelling study. Lancet. 2007;370(9597):1500–7.CrossRefPubMedPubMedCentral
27.
go back to reference Suen SC, Bendavid E, Goldhaber-Fiebert JD. Cost-effectiveness of improvements in diagnosis and treatment accessibility for tuberculosis control in India. Int J Tuberc Lung Dis. 2015;19(9):1115–24. i-xv.CrossRefPubMed Suen SC, Bendavid E, Goldhaber-Fiebert JD. Cost-effectiveness of improvements in diagnosis and treatment accessibility for tuberculosis control in India. Int J Tuberc Lung Dis. 2015;19(9):1115–24. i-xv.CrossRefPubMed
28.
go back to reference Andrews JR, Basu S, Dowdy DW, Murray MB. The epidemiological advantage of preferential targeting of tuberculosis control at the poor. Int J Tuberc Lung Dis. 2015;19(4):375–80.CrossRefPubMedPubMedCentral Andrews JR, Basu S, Dowdy DW, Murray MB. The epidemiological advantage of preferential targeting of tuberculosis control at the poor. Int J Tuberc Lung Dis. 2015;19(4):375–80.CrossRefPubMedPubMedCentral
29.
go back to reference Uplekar M, Weil D, Lonnroth K, Jaramillo E, Lienhardt C, Dias HM, et al. WHO’s new End TB Strategy. Lancet. 2015;385:1799–801.CrossRefPubMed Uplekar M, Weil D, Lonnroth K, Jaramillo E, Lienhardt C, Dias HM, et al. WHO’s new End TB Strategy. Lancet. 2015;385:1799–801.CrossRefPubMed
Metadata
Title
TIME Impact – a new user-friendly tuberculosis (TB) model to inform TB policy decisions
Authors
R. M. G. J. Houben
M. Lalli
T. Sumner
M. Hamilton
D. Pedrazzoli
F. Bonsu
P. Hippner
Y. Pillay
M. Kimerling
S. Ahmedov
C. Pretorius
R. G. White
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2016
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-016-0608-4

Other articles of this Issue 1/2016

BMC Medicine 1/2016 Go to the issue