Addressing the Data Gaps on Child and Adolescent Tuberculosis.
Sabine VerkuijlMoorine Penninah SekaddePeter J DoddMoses ArinaitweSilvia S ChiangAnnemieke BrandsKerri VineyCharalambos SismanidisHelen E JenkinsPublished in: Pathogens (Basel, Switzerland) (2022)
The burden of tuberculosis (TB) among children and young adolescents (<15 years old) is estimated at 1.1 million; however, only 400,000 are treated for TB, indicating a large gap between the number who are cared for and the number estimated to have TB. Accurate data on the burden of pediatric TB is essential to guide action. Despite several improvements in estimating the burden of pediatric TB in the last decade, as well as enhanced data collection efforts, several data gaps remain, both at the global level, but also at the national level where surveillance systems and collaborative research are critical. In this article, we describe recent advances in data collection and burden estimates for TB among children and adolescents, and the remaining gaps. While data collection continues to improve, burden estimates must evolve in parallel, both in terms of their frequency and the methods used. Currently, at the global level, there is a focus on age-disaggregation of TB notifications, the collection of data on TB-HIV, multi-drug resistant (MDR)-TB and treatment outcomes, as well as estimates of the disease burden. Additional data from national surveillance systems or research projects on TB meningitis, as well as other forms of extra-pulmonary TB, would be useful. We must capitalize on the current momentum in child and adolescent TB to close the remaining data gaps for these age groups to better understand the epidemic and further reduce morbidity and mortality due to TB.
Keyphrases
- mycobacterium tuberculosis
- electronic health record
- big data
- drug resistant
- young adults
- pulmonary tuberculosis
- multidrug resistant
- quality improvement
- public health
- data analysis
- emergency department
- physical activity
- mass spectrometry
- pulmonary hypertension
- antiretroviral therapy
- hiv positive
- hiv infected
- pseudomonas aeruginosa
- hiv aids
- high resolution
- artificial intelligence
- newly diagnosed
- cystic fibrosis
- adverse drug
- hiv testing
- middle aged