Abstract

BackgroundChildhood tuberculosis (TB) is a major global public health concern contributing to significant child morbidity and mortality. A records review of the TB notification for Chegutu District Health Information System 2 (DHIS2) showed a low childhood TB case detection rate. For 2018 and 2019, childhood TB notifications were 4% and 7% respectively against the annual national childhood 12% case detection rate. We evaluated the performance of the childhood TB program in Chegutu.MethodsWe conducted a descriptive cross-sectional study. Sixty-six health workers (HW) participated in the study. Interviewer-administered questionnaires and checklists were used to collect data on reasons for low TB case detection, HW childhood TB knowledge, program inputs, processes, and outputs. Strengths, Weaknesses, Opportunities and Threats analysis was used to assess the childhood TB processes. We analyzed the data using Epi Info 7™ to generate frequencies, proportions and means. A Likert scale was used to assess health worker knowledge.ResultsThe majority 51/66(77%) of HW were nurses and 51/66(67%) of respondents were females. Reasons for the low childhood TB case detection were lack of HW confidence in collecting gastric aspirates 55/66(83%) and HW’s negative attitudes towards gastric aspirate collection 23/66(35%). HW 24/66 (37%) had a fair knowledge of childhood TB notification. The district had only one functional X-ray machine for 34 health facilities. Only 6/18 motorcycles were functional with inadequate fuel supply. No desk guide for the management of TB in children for HW (2018) was available in 34 health facilities. Ethambutol 400 mg was out of stock and adult 800 mg tablets were used. Funds allocated for motor vehicle and motorcycles service ($1612USD/year) were inadequate. The district failed to perform planned quarterly TB review meetings, contact tracing and childhood TB training due to funding and COVID-19 lockdown restrictions.ConclusionThe childhood TB program failed to meet its targets due to inadequate inputs, HW suboptimal knowledge and COVID-19 lockdown measures. Case detection and notification can be improved through on-job training, mentorship, support and supervision and adequate resources.

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