Infectious Disease

Development of the Rapid SBCC Habit Optimization Tool (R-SHOT), a simple field tool that combines local data with evidence-based principles to recommend the optimal habit and motivational tactics for a given audience and setting. The tool will help communities determine how to disrupt existing habits and insert new vector control habits into people’s lives, what the most effective motivational levers to drive behavior change are, and how these tactics should be tailored/optimized for different settings and audiences.

Chinedu Chugbo of Avigo Health L.L.C. in the U.S. will develop an approach to crowdsource reports of infant births and deaths from community members by health workers to better monitor vaccine coverage in low- to middle-income countries. In Nigeria, only 30% of births are registered, making it difficult to estimate numbers of vaccine-eligible children and ensure every child is properly vaccinated. Current methods for estimating population sizes include household surveys, which are costly, or records from health clinics, which suffer from limited coverage.

Aaditeshwar Seth of OnionDev Technologies Pvt. Ltd. in India in collaboration with the University of Montreal Hospital Research Centre (CRCHUM) via the Tika Vaani project, will develop a smartphone application and digital processing techniques to digitize childhood immunization data from photographs of vaccination cards taken by health workers during clinic visits and store the data in a cloud to monitor adherence and send reminders to families.

Mustafa Naseem of the University of Michigan in the U.S. will apply machine-learning algorithms to identify potentially falsified digital vaccination records in Pakistan. Pakistan is one of only three remaining countries where polio is still endemic. Particularly rural healthcare facilities are struggling to provide enough vaccinations due to highly populous provinces and a lack of resources and staff, and there is a risk that records are falsified to save time or bias the results.

Benjamin Fels and Suvrit Sra of Macro-Eyes, Inc. in the U.S. will engage with frontline health workers in immunization centers and combine their knowledge with existing supply chain and immunization data using machine learning to better predict vaccine demand and thereby improve immunization coverage. Vaccine supply levels in Ethiopia are predicted using data that may be inaccurate or outdated.

Chibuzo Opara of DrugStoc E Hub Ltd. in Nigeria will equip vaccine storage and transport sites with calibrated weighing mats (Digimats) that automatically transmit vaccine quantities in real time to better monitor delivery chains in the community and improve supply. Monitoring the movement of vaccines at the national and district level is currently performed by the Nigerian immunization program. However, accurate monitoring at the local level requires alternative, more automated approaches to avoid human error.

Michael Nunan of Beyond Essential Systems in Australia will build on their existing data platform to collect and analyze vaccine data in real-time to provide an early warning of areas or facilities with low immunization coverage. The platform integrates data from various sources, including vaccine supply and healthcare infrastructure such as equipment and staff. They will further develop it to record actual vaccine administrations from health workers entering details on mobile phones, and to produce local estimates of vaccine demand and actual coverage and provide alerts.

James Njeru of the Field Epidemiology Society of Kenya will develop an integrated electronic platform that collects immunization and health data from existing registries and automatically sends regular, user-defined reports via SMS and email to health workers to improve vaccine coverage. Healthcare facilities record their immunization data on District Health Information Systems, but access to the data is limited.

Ross Boyce at the University of North Carolina in the U.S. will develop an approach that uses new methods of mapping households together with available health data to better identify places that have limited access to healthcare to improve immunization coverage. Many sub-Saharan African countries have very poor rates of childhood vaccination coverage. Improving coverage requires identifying those households and areas with poor access to healthcare, but this is challenging with the limited data available.

Ali Turab of IRD Global Ltd. in Singapore will develop a decision support tool that can be integrated with digital immunization registries to automatically construct optimal appointment schedules for every child that can adjust for missed immunizations and the introduction of new vaccines. A large majority of children, in both developing and developed countries, are not immunized at the recommended times, which can increase the risk of severe diseases.