Infrastructure

James Lavery of Emory University in the U.S. will adapt an organizational learning tool to enable global health campaigns to draw on their experiences, improve their partner interactions, and enhance their overall impact. Global health campaigns are primarily evaluated in terms of program delivery and outcomes. However, these large and complex organizations interact with many different partners, and there is an untapped opportunity to improve their performance by learning about how their design and approaches affect each other.

Mosokah Fallah of the National Public Health Institute of Liberia will provide health campaign staff with activity tracking devices and movement-based bonuses to encourage more accurate reporting of coverage to improve impact. There have been large inconsistences between the reported and actual numbers of drugs and vaccines administered during health campaigns in Liberia. This may be due to the lack of motivation and accountability of health campaign staff.

Pascal Geldsetzer of Stanford University in the U.S. will develop a computational tool to support health campaigns in low- and middle-income countries that can predict the number and location of the people that need targeting. They will use freely available databases, including the Demographic and Health Surveys (DHS), covering over 10 million households and high-resolution population estimates to estimate the percentage of children under 5-years-old who are un- or under-vaccinated within each 30m by 30m area.

Laura Smith of Research Foundation for the State University of New York in the U.S. will develop a decision-making tool that can plan more effective health campaigns in low- and middle-income countries by considering any competing interests of stakeholders. Health campaigns involve many different government and private stakeholders with differing interests.

Sangeeta Jobanputra of Connecti3 LLC in the U.S. together with the University of Rwanda and Multiverse Investments will develop a method that uses existing datasets and predictive analytics to better plan all types of health campaigns to broaden their coverage and minimize costs. The challenge of identifying those in need of a specific health service is a barrier to successful health campaigns. To address this, they will use existing databases to identify and score predictors of higher risk to a specific health condition, such as level of poverty in vitamin A deficiency.

Hannah Wild of Stanford University in the U.S. will develop a modelling-based approach that uses remote sensing and geospatial analysis to include neglected and high-risk nomadic populations in health databases and for campaign planning. Nomadic pastoralists are some of the poorest populations but they are often missed by health services and campaigns because they are difficult to track. They will design algorithms and methods that use satellite imagery and open access geospatial data to capture population movements over time, which will be validated in the field.

Simon Mutembo of the Macha Research Trust in Zambia will develop a method to identify and map children who have never received vaccinations so that they can be targeted during mass vaccination campaigns. Many of these children live in remote areas and are missed by population estimates. Their method combines field work by community health workers with spatial intelligence using a geospatial application on smart phones to develop geographical maps of vaccination coverage at the household level. Households with low or no vaccinations can then be targeted directly by campaign health workers.

Qingfeng Li of Johns Hopkins Bloomberg School of Public Health in the U.S. will develop a computational simulation tool to optimize the design of health campaigns in low-income settings. Health campaigns are complex events involving multiple, interconnected components, such as families and socioeconomic contexts, as well as being time restricted and targeting specific populations. Their tool uses geospatial measures and community maps, and it includes an automated algorithm to test different design strategies to identify the optimal design.

This project will allow the design, construction, laboratory testing, and initial field trial, of our novel solar powered oxygen system.This is the first ever solar powered oxygen system that functions without the need for batteries or inverters.

Atomo is a specialist medical device company that has invented a unique casing for an RDT that incorporates the lancet, transfer of blood and reading of the result into one easy-to-use platform. This makes the Atomo test significantly easier to perform than traditional test strips and enables point-of-care and at-home testing. It dramatically lowers user errors, making it attractive for both at-home testing and usage in medical facilities without the need for highly-trained caregivers.