Building Data Triangulation Capacity for Routine Immunization and Vaccine Preventable Disease Surveillance Programs...

Area of Science:

• Public Health
• Epidemiology
• Health Informatics

Background:

• Expanded Programme on Immunization (EPI) and Vaccine Preventable Disease (VPD) Surveillance (VPDS) programs generate diverse, yet siloed, data.
• Challenges in data accessibility and timely analysis hinder effective programmatic decision-making.
• Siloed data contribute to missed vaccinations, immunity gaps, and VPD outbreaks, particularly in underserved populations.

Purpose of the Study:

• To describe data triangulation processes for improving immunization program performance.
• To identify key indicators for assessing immunization coverage and identifying gaps.
• To share lessons learned from implementing data triangulation in Bangladesh, Nigeria, and Rwanda.

Main Methods:

• Data triangulation involving the integration of routine administrative data, VPD case data, and coverage surveys.
• Prioritization of key indicators to identify immunization coverage gaps, under-immunized (UI), and zero-dose (ZD) children.
• Capacity building efforts and specific analyses to generate meaningful data for programmatic decision-making.

Main Results:

• Data triangulation enhances the availability of crucial indicators for identifying immunization coverage inequities.
• The process effectively identifies under-immunized (UI) and zero-dose (ZD) children, crucial for targeted interventions.
• Programmatic improvements were observed through better identification of performance gaps at all healthcare system levels.

Conclusions:

• Data triangulation is a valuable strategy for overcoming data silos in immunization programs.
• Leveraging triangulation processes and lessons learned can lead to programmatic changes that improve vaccination service access and utilization.
• This approach supports the identification of UI and ZD children, ultimately strengthening VPD prevention efforts.