App/Software

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.

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.

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.

Matt Berg of Ona in the U.S. will combine high-resolution satellite images, spatial sampling statistics, and mobile data collection to better calculate local immunization coverage in Bangladesh. Current approaches often vastly overestimate coverage because of the difficulty in calculating actual population sizes from nationwide data and birth registries. As a more effective approach, they will use satellite imagery to detect liveable structures within a set area, and software that selects possible households that require verification by community surveillance teams.

The proposal will develop a platform for the analysis and visualization of data that will allow managers, public servants and other stakeholders involved in the Mãe Coruja Program at Pernambuco state (PMCP) to extract strategic information to improve the intervention. The focus will be on the implementation and actual enforcement of public policies, considering the high gestational risk and sexually transmitted infections (STI). Currently, health databases are for consultations only.

Aims to access all 68.3 million living births certificates from Brazil, from 1994 to 2016, and compare them with breastfeeding policies in all Brazilian hospitals to assess the impact of the initiatives on infant health. The study also plans to estimate the number of avoidable deaths during this time period, if those initiatives were adopted in Brazil.

The project will develop a platform to provide services for decision-making support for neonatal death preventive actions by using data from CIDACS cohort. The platform will offer three services: cohort data visualization for decision-making support by comparative human visual analysis, prediction of risk of neonatal death based on machine learning models, and simulator of public policies impact influencing on the risk of neonatal death.

Manish Bhardwaj of Innovators in Health in India will build a social networking platform consisting of voice messages accessed via mobile phone that is monitored by community health workers to connect small groups of young pregnant women and new mothers in India. Currently, community health workers provide home visits to help adolescent mothers combat mental health disorders. However, their capacity is limited. An additional difficulty for adolescent mothers is the lack of social networks caused by moving to new neighborhoods to live with their husbands.

Aleksandra Perczynska from People in Need in Nepal will develop two approaches, namely mobile phone voice messaging (mobile health [mHealth]) and workshops, to improve the mental health of young mothers in Nepal. In 2016, over 15% of Nepali girls aged 15-19 years had children. These adolescents are particularly vulnerable to mental health disorders such as depression, and often have limited support from the community and their new in-laws. They will recruit young mothers and mental health workers to help design the two approaches.