We conducted a descriptive cross-sectional study based on the Centre for Disease Control and Prevention (CDC) logic model for program evaluation .
The study was conducted in Chegutu District, Mashonaland West Province situated in the central northern region of Zimbabwe from March 2021 to May 2021 whilst evaluating the childhood TB program in 2020. The district has 34 health facilities including a district hospital. It has a total population of 180,741 people . Rural residents travel ten to twenty-five kilometres to access health care facilities. All government, rural and urban councils’ health facilities were participating in the childhood TB program. The economic activities in the district consist of indigenous companies, mining, commercial farming and subsistence farming.
Our study population were health care workers from the outpatients’ department, maternal child health department, pediatric wards, laboratory, pharmacy department and environmental health department. The Environmental Health Technicians (EHT) are responsible for transporting TB specimens from the health facilities to the two TB diagnosing centres in the district as well as sending TB results to the health facilities. Moreso, EHTs conduct TB contact tracing as well as provision of health education on infection prevention and control in the community. Caregivers of children being treated for TB in 2021 were interviewed. The District Medical Officer, the District Nursing Officer, Acting District TB Coordinator, District Environmental Health Officer, Senior Nursing Officer, District Pharmacist, Logistic Officer National Pharmaceutical Company, and Laboratory Scientist were key informants in the study.
The TB presumptive register captures information for all patients screened for TB. The information includes demographic data; TB risk group such as being under five, malnourished or HIV positive; type of TB specimen collected; date Chest X-ray was taken and HIV result. The TB register captures all TB cases detected. It contains the following information: date of diagnosis, date of notification, demographic data, TB risk group; TB laboratory results; follow updates; TB/HIV care, contacts screened; TB medicines supply dates and treatment outcome. The TB notification forms, presumptive register and TB registers were reviewed for TB screening done, TB treatments done, TB contacts screened, and TB notifications.
Laboratory stock cards were checked for monthly stocks of TB consumables kits. This kit provides a convenient way to receive all of the needed reagents and consumables to perform 1000 smears using bright field Ziehl Neelsen (ZN) microscopy. Laboratory stock cards were checked for monthly stocks of Gene Xpert cartridges. Pharmacy stock cards were checked for stocks of childhood TB medicines.
Sample size for health care workers
We calculated a sample size of 66 health care workers using the Dobson formula:
n = za2 x p (1-p)/ delta2., assuming that 96% of the health workers knew that TB is curable from a study by Pantha et al. (2020) in Bangladesh  at a 95% confidence interval (CI), 80% power, a margin of error of 5% and a non-response rate of 10%).
Sample size for caregivers of children with TB
There were five caregivers with children who were still on TB treatment as the other children 16 children who were commenced on TB treatment in 2020 had completed their 6 months. We conveniently recruited the five caregivers into the study.
Sampling of health care workers
Health care workers from sixteen high volume sites and three hospitals in the district were recruited into the study. The 31 clinics in the Chegutu District have a staff complement of three nurses at each clinic. On the day of data collection, where three nurses reported for work, simple random sampling using a random number generated by the RANDBETWEEN function in Microsoft Excel was used to select two. If only one nurse reported for work, we recruited him or her into the study. At hospitals (Chegutu District, Mhondoro Rural and Norton) we randomly selected 12 health care workers from (outpatients department, opportunistic infection clinic, maternal child health department, paediatric ward, laboratory, pharmacy department and environmental health department) using random numbers generated by the RANDBETWEEN function in Microsoft Excel. Key informants were purposively recruited into the study.
Health care workers
We collected data from health care workers using a pre-tested interviewer-administered questionnaire on demographic information, reasons for low childhood case detection, knowledge on childhood TB and processes involved in childhood TB. Presumptive registers, TB registers, notification forms, pharmacy ordering forms, laboratory ordering forms and stock cards were reviewed to assess for childhood TB program outputs and outcome indicators. A checklist was used to assess childhood TB program resources availability.
A key informant guide was used to collect data from the key informants on the childhood TB program budget, health care worker training that was conducted, availability of resources and performance of the program in 2020. We used information collected from key informants to triangulate quantitative findings from health care workers, caregivers and childhood TB records.
Caregivers of children with TB
We used a pretested questionnaire to collect information from caregivers on their views regarding childhood TB.
We used Epi Info™ 7 statistical software to capture and analyze data. Descriptive statistics were used to describe the study population and were presented as frequencies, proportions and median. Knowledge of health care workers was assessed using a 3-point Likert scale (good, fair, poor). We used five questions and one mark was awarded for a correct answer to any of the five questions. Four or five marks were considered good knowledge, three marks were fair knowledge, and less than two marks was poor knowledge.
An in-depth assessment of the TB program processes (childhood TB case finding, TB notification process TB contact tracing, the procurement and distribution process of childhood TB medicines and laboratory consumables) was done using the Strengths Weaknesses Opportunities and Threats (SWOT) analysis. Qualitative data from key informants were grouped manually into themes and then analysed by theme.