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PhD defence of Larissa Otero

Pulmonary tuberculosis case detection in a medium incidence middle-income country

20 Oct 2016

Booking recommended

Supervisors:

  • Prof. dr. Patrick Van der Stuyft (Institute of Tropical Medicine/Ghent University)
  • Prof. dr. Carlos Seas Ramos (Universidad Peruana Cayetano Heredia, Lima, Peru)

Abstract:

Case detection is central to tuberculosis (TB) control. Missed or delayed diagnoses lead to longer periods of infectiousness that sustain TB transmission. Modelling indicates that detecting 70% of smearpositive pulmonary TB cases and curing 85% of them - the present World Health Organization targets - can decrease TB incidence by 10% per year. However, in 2014, worldwide, only 63% of the estimated smearpositive cases were detected and notified and TB incidence is declining at only 2% per year. Most research addressing case detection is biomedical and focuses on developing new diagnostic tests that perform better than the traditional ones. However, implementation of these tests has hardly had an impact on TB incidence. This thesis combined a health system and an operational perspective to investigate the broader process of case detection. We designed and conducted, in Lima Peru, six studies on pulmonary TB and MDR-TB case detection: from the criteria used in the selection of suspects to be tested, to their identification and the testing procedure itself, up to the start of treatment. The studies aimed to generate evidence on performance gaps at these steps and propose potential solutions for improvement. The study setting was San Juan de Lurigancho, a peri-urban district in Lima with over one million inhabitants where TB and MDR-TB prevalence are amongst the highest in the country.