Optimising DTwP-containing vaccine infant immunisation schedules (OptImms) - a protocol for two parallel, open-label, randomised controlled trials.

BACKGROUND: Universal immunisation is the cornerstone of preventive medicine for children, The World Health Organisation (WHO) recommends diphtheria-tetanus-pertussis (DTP) vaccine administered at 6, 10 and 14 weeks of age as part of routine immunisation. However, globally, more than 17 unique DTP-containing vaccine schedules are in use. New vaccines for other diseases continue to be introduced into the infant immunisation schedule, resulting in an increasingly crowded schedule. The OptImms trial will assess whether antibody titres against pertussis and other antigens in childhood can be maintained whilst adjusting the current Expanded Programme on Immunisation (EPI) schedule to provide space for the introduction of new vaccines. METHODS: The OptImms studies are two randomised, five-arm, non-inferiority clinical trials in Nepal and Uganda. Infants aged 6 weeks will be randomised to one of five primary vaccination schedules based on age at first DTwP-vaccination (6 versus 8 weeks of age), number of doses in the DTwP priming series (two versus three), and spacing of priming series vaccinations (4 versus 8 weeks). Additionally, participants will be randomised to receive their DTwP booster at 9 or 12 months of age. A further sub-study will compare the co-administration of typhoid vaccine with other routine vaccines at one year of age. The primary outcome is anti-pertussis toxin IgG antibodies measured at the time of the booster dose. Secondary outcomes include antibodies against other vaccine antigens in the primary schedule and their safety. DISCUSSION: These data will provide key data to inform policy decisions on streamlining vaccination schedules in childhood. TRIAL REGISTRATIONS: ISRCTN12240140 (Nepa1, 7th January 2021) and ISRCTN6036654 (Uganda, 17th February 2021).

Achieving optimal heath data impact in rural African healthcare settings: measures to barriers in Bukomansimbi District, Central Uganda.

BACKGROUND: Health data is one of the most valuable assets in health service delivery yet one of the most underutilized in especially low-income countries. Health data is postulated to improve health service delivery through availing avenues for optimal patient management, facility management, and public health surveillance and management. Advancements in information technology (IT) will further increase the value of data, but will also call for capacity readiness especially in rural health facilities. We aimed to understand the current knowledge, attitudes and practices of health workers towards health data management and utilization. METHODS: We conducted key informant interviews (KII) for health workers and data staff, and focus group discussions (FGD) for the village health teams (VHTs). We used both purposive and convenience sampling to recruit key informants, and convenience sampling to recruit village health teams. Interviews and discussions were audiotaped and transcribed verbatim. We manually generated the codes and we used thematic analysis to identify the themes. We also developed a reflexivity journal. RESULTS: We conducted a total of 6 key informant interviews and 3 focus group discussions of 29 participants. Our analysis identified 7 themes: One theme underscored the health workers' enthusiasm towards an optimal health data management setting. The rest of the six themes resonated around working remedies to the systemic challenges that grapple health data management and utilization at facilities in rural areas. These include: Building human resource capacity; Equipping the facilities; Improved coordination with partners; Improved data quality assurance; Promotion of a pull supply system and Reducing information relay time. CONCLUSION: Our findings reveal a plethora of systematic challenges that have persistently undercut optimal routine health data management and utilization in rural areas and suggest possible working remedies. Health care workers express enthusiasm towards an optimal health management system but this isn't matched by their technical capacity, facility readiness, systems and policy willingness. There is an urgent need to build rural lower facilities' capacity in health data management and utilization which will also lay a foundation for exploitation of information technology in health.