Is IPT more effective in high-burden settings? Modelling the effect of tuberculosis incidence on IPT impact

Ragonnet, R. , Trauer, J.M. , McBryde, E.S., Houben, R.M.G.J., Denholm, J.T., Handel, A., and Sumner, T. (2017) Is IPT more effective in high-burden settings? Modelling the effect of tuberculosis incidence on IPT impact. The International Journal of Tuberculosis and Lung Disease, 21 (1). pp. 60-66.

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Abstract

Setting: Isoniazid preventive therapy (IPT) is effective for preventing active tuberculosis (TB), although its mechanism of action is poorly understood and the optimal disease burden for IPT use has not been defined.

Objective: To describe the relationship between TB incidence and IPT effectiveness.

Methods: We constructed a model of TB transmission dynamics to investigate IPT effectiveness under various epidemiological settings. The model structure was intended to be highly adaptable to uncertainty in both input parameters and the mechanism of action of IPT. To determine the optimal setting for IPT use, we identified the lowest number needed to treat (NNT) with IPT to prevent one case of active TB.

Results: We found that the NNT as a function of TB incidence shows a ‘U-shape’, whereby IPT impact is greatest at an intermediate incidence and attenuated at both lower and higher incidence levels. This U-shape was observed over a broad range of parameter values; the optimal TB incidence was between 500 and 900 cases per 100 000 per year.

Conclusions: TB burden is a critical factor to consider when making decisions about communitywide implementation of IPT. We believe that the total disease burden should not preclude programmatic application of IPT.

Item ID: 47364
Item Type: Article (Research - C1)
ISSN: 1027-3719
Keywords: latent tuberculous infection, preventive therapy, optimal impact
Funders: Bill and Melinda Gates Foundation (BMGF)
Projects and Grants: BMGF OPP1084276
Date Deposited: 07 Mar 2017 00:56
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1103 Clinical Sciences > 110309 Infectious Diseases @ 50%
16 STUDIES IN HUMAN SOCIETY > 1605 Policy and Administration > 160508 Health Policy @ 50%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 50%
92 HEALTH > 9202 Health and Support Services > 920207 Health Policy Evaluation @ 50%
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