Houben, Rein; Parwati, Cicilia Gita; Farid, Muhammad Noor; Nasution, Helmi Suryani; Sulistyo, Sulistyo; Basri, Carmelia; Gebhard, Agnes; Tiemersma, Edine; Pambudi, Imran; Surya, Asik; (2020) Subnational burden estimation in Tuberculosis: generation and application of a new tool in Indonesia. International Journal of Tuberculosis and Lung Disease, 24 (2). pp. 250-257. ISSN 1027-3719 https://researchonline.lshtm.ac.uk/id/eprint/4655392
Permanent Identifier
Use this permanent URL when citing or linking to this resource.
https://researchonline.lshtm.ac.uk/id/eprint/4655392
Abstract
Setting In many high tuberculosis (TB) burden countries, there is substantial geographical heterogeneity in TB burden. In addition, decisions on TB funding and policy are highly decentralised. Subnational estimates of burden however are usually unavailable for planning and target-setting. Objective and Design We developed SUBsET to distribute national TB incidence through a weighted score using selected variables, and applied for the 514 districts in Indonesia, which have substantial policy and budgetary autonomy in TB. Estimated incidence was compared to reported facility and domicile-based notifications to estimate the case detection rate (CDR). Local stakeholders led model development and dissemination. Results The final SUBsET model included district population size, level of urbanisation, socio-economic indicators (living floor space and high school completion), HIV prevalence and air pollution. We estimated district-level TB incidence between 201 and 2,485/100,000/year. The facility-based CDR varied between 0 and 190% with high variation between neighbouring districts, e.g. suggesting strong cross-district health utilisation, which was confirmed by domicile-based CDR estimation. SUBsET results informed district-level TB action plans across Indonesia. Conclusion Applying SUBsET to estimate the subnational burden can be important for high-burden countries and inform TB policy-setting at the relevant, decentralised administrative level.
Item Type | Article |
---|---|
Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology |
Research Centre |
TB Centre Centre for the Mathematical Modelling of Infectious Diseases TB Modelling Group |
Elements ID | 141919 |
Download
Filename: Parwati-etal-2019_subnational_burden_estimation_in_tuberculosis.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0
Download