Rajeev Shrestha and colleagues at Dhulikhel Hospital, Kathmandu University in Nepal will apply metagenomic, next generation sequencing technology to identify causative pathogens of fatal acute encephalitis to improve diagnosis and treatment. Acute encephalitis syndrome (AES) annually affects over 100,000 individuals in low- and middle-income countries, causing substantial morbidity and mortality. It is a diverse disease caused by over 100 different pathogens, including viruses and parasites, making accurate diagnosis difficult, even in high-resource settings. This hinders prevention and treatment efforts, even though several effective vaccines exist. To better characterize the pathogens causing AES, particularly treatable and emerging ones, they will apply metagenomic, next generation sequencing technology to 60 banked cerebral spinal fluid samples collected from fatal acute encephalitis cases in Nepal as part of a nationwide AES surveillance program that covered 189 hospitals. They will validate and refine their technique using previously validated samples.

Rozina Feroz Ali of IRD Global Limited in Singapore along with Subhash Chandir and Danya Arif will establish a subsidized carpool for Pakistani women in rural areas and urban slums to improve access to immunization centers and increase vaccination coverage. Poor vaccine coverage in Pakistan is a result of the combined effects of poverty, lack of education, poor access to transportation, and distantly located vaccination centers; populations in rural areas and urban slums are vulnerable to outbreaks of vaccine-preventable disease and an increased childhood mortality rate. They will develop a system to provide women with transport to vaccine centers at affordable rates, educate them on the importance of vaccination through short videos played during the ride, and promote the service in the community by branding the commuting vehicles with vaccine and schedule information. Dedicated vehicles will offer fixed-price, round trip transportation to vaccination centers along specific routes with designated pick-up and drop-off times. In addition to improving access to vaccination, this system will work to improve gender equality in Pakistan; the ability to travel independently decreases female dependence on male family members. They will test it in a rural setting or urban slum in Pakistan and evaluate the number of users, number of children vaccinated, and estimated impact on vaccine coverage.

Kindie Tesfaye-Fantaye of the International Maize and Wheat Improvement Center in Mexico will develop a computational model that incorporates the variable characteristics of households and farms to better predict the outcomes of agricultural interventions in Ethiopia in order to inform policy choices. Agriculture is central to the Ethiopian economy; it accounts for almost 50% of the gross domestic product and 80% of total employment, yet the industry struggles with limited infrastructure and environmental challenges. Prioritization of agricultural policies has generally relied on analysis of past observations, which are static and tend to ignore variability. They will build and validate an agent-based model that uses current data to model future outcomes, and input biophysical (e.g., soil, climate) and socioeconomic (e.g., household characteristics, land use, access to market and financing) data. They will test their model by comparing five candidate policy options under consideration by the government in terms of impact, effectiveness, efficiency, and inclusiveness. Once established, the model will be scaled up for policy intervention in other Sub-Saharan countries including Tanzania and Nigeria.

Amit Lal of Geegah LLC in the U.S. will develop battery-powered ultrasonic imagers to collect and wirelessly transmit high-resolution images of soil and airborne pests for the early detection of crop threats across large farming areas in rural Africa. Crop losses due to pest infestation negatively impact both food security and local economies. Damage caused by nematodes is particularly difficult to detect because the symptoms visible above ground are not unique and are often incorrectly attributed to deficiencies in soil nutrients or moisture. Currently the only way to test for nematodes is through root and soil samples taken after harvest, when it is too late to respond to an infestation. They will integrate complementary metal-oxide semiconductors (CMOS) with GHz ultrasonic imagers to detect nematodes and survey soil properties over large areas to detect infestations before crop damage occurs and transmit the data in real time. They will optimize the sensor technology in a controlled laboratory setting to maximize sensitivity and specificity and minimize power consumption and then transition to a farm setting for incorporating data transmission via the radio frequency wireless network.