Product/Service Development

Develop a release mechanism compatible with Unmanned Aerial Vehicles (UAVs) to ultimately release sterilized male mosquitoes aerially.

Develop, pilot and evaluate the potential to scale the use of Unmanned Aerial Vehicles (UAVs) to strengthen national health systems’ coverage, reach and responsiveness to address existing and future health threats.

Development of Electronic Mosquito Barriers (EMBs), which use high power pulsed electric fields to repel mosquitoes. Using pulsations that vary randomly in both strength and frequency, the EMBs create a mosquito-repelling force field. The unpredictability of the pulsations makes it nearly impossible for mosquitoes to learn or adapt to when, where, and with what force the electric field is coming.

Development of sandals that release highly effective, wide-area spatial mosquito repellents, creating full-time protection against both day-biting and night-biting mosquitoes at individual and household level. The low cost sandals provide protection against Dengue, Zika, Chikungunya and Malaria using hessian strips impregnated with highly effective and safe repellent, transfluthrin.

Development of a treated net impregnated with metofluthrin, which maintains efficacy for a three-week period. Small units of net, or emanators, are hung indoors and create protected zones that prevent mosquito-human contact.

Development of a simple, affordable low-tech transfluthrin emanator that could be readily produced en masse and protects against Culex, Mansonia, Anopheles, and Aedes mosquitoes for months or years.

Janos Zempleni of the University of Nebraska-Lincoln in the U.S. will test whether supplementing milk formula with exosomes from milk could have the potential to improve the growth of babies aged between 6 and 12 months and help protect them from infections. Exosomes are membrane-bound vesicles naturally present in all bodily fluids and are thought to transfer small molecules such as RNAs between different cells to regulate various cell functions. However, during the production of milk formula for babies, the exosomes are destroyed.

Matteo Rinaldi of Northeastern University in the U.S. will develop a miniaturized, maintenance-free chemical sensor that can detect specific volatile organic chemical vapors released from diseased crops as an effective surveillance system suitable for low-resource settings. Manual surveillance is time-consuming and requires prior knowledge of disease symptoms. Automated, sensor-based crop surveillance is far more effective, but relatively expensive, and the sensors constantly consume power, making them unsuitable for low-resource settings.

David Hughes of Pennsylvania State University in the U.S. is leveraging real-time, high-resolution satellite imagery of smallholder farms along with artificial intelligence to automatically detect crop pests and diseases in Africa. In Phase I, together with Nita Bharti also of Penn State University in the U.S.

Jan Kreuze of the International Potato Center in Peru will develop a low-cost, mobile phone-based diagnostic test for African farmers that uses artificial intelligence to quickly and accurately detect plant diseases such as cassava brown streak and banana bunchy top, which devastate crops and are threatening to spread. Accurately diagnosing plant diseases is difficult because visual symptoms can be highly variable. Artificial intelligence (AI) has shown promise for analyzing images of plants taken by mobile phone to detect diseases in low-resource settings, but it is not accurate enough.