Grand Challenges is a family of initiatives fostering innovation to solve key global health and development problems. Each initiative is an experiment in the use of challenges to focus innovation on making an impact. Individual challenges address some of the same problems, but from differing perspectives.
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Xiao-Guang Chen, Zetian Lai and Chunmei Wang of Southern Medical University in China and their international partner Guiyun Yan of the University of California, Irvine in the U.S. will develop new traps that are more attractive to malaria vectors. They will incorporate the new traps with infrared vector detection, automatic recording and wireless transmission technologies, and test the efficacy of the new trap and the automated malaria vector surveillance apparatus both in the laboratory and in the field. This novel, real-time malaria vector surveillance tool can help efficiently monitor biting behavior, population abundance and transmission dynamics of malaria vectors, and tremendously enhance malaria transmission surveillance and facilitate the evaluation of new vector control measures targeting outdoor malaria vectors.
Zhang Dongjing, Zheng Xiaoying, Wu Yu and Wang Gang of Sun Yat-sen University in China together with their international partners Badria El-Sayed, Tellal Ageep, Ammar Hassan and Mohamed Korti all from the National Centre for Research in Sudan, and Jeremy Bouyer, Maiga Hamidou, Hanano Yamada and Adly Abdalla of Insect Pest Control Laboratory in Austria will develop highly specific and environmentally friendly Sterile Insect Technique (SIT) to control outdoor Anopheles mosquitoes. Once the feasibility evaluation is passed, the results will form a systematic technical package of SIT to control Anopheles stephensi and provide the scientific basis and technical support for subsequent field trials of SIT to control this outdoor malaria vector in African countries such as Sudan or other Asian countries.
Weiguo Fang of Zhejiang University and Guoding Zhu of Jiangsu Institute of Parasitic Diseases in China together with their international partner Abdoulaye Diabaté of Institut de Recherche en Sciences de La Santé in Burkina Faso, by referring to the widely used small farmer-operated factories for production of entomopathogenic fungal spores in China, will develop a spore production technology for the transgenic Metarhizium strain, which is cost-effective, of low technological bar and can be easily implemented in low-and middle-income countries and regions. A novel bifunctional device will also be provided for outdoor mosquito control. Currently, mycoinsecticides and their release devices are only suitable for indoor mosquito control.
GuoXiong Peng, Yuxian Xia, Yueqing Cao and ZhengBo He of Chongqing University in China together with their international partner Raymond J. St. Leger of the University of Maryland in the U.S. will screen mosquitocidal fungal strains from China and abroad for high-yield virulent and stable production strains against larvae and adults, test the safety of the production strains, optimize solid fermentation medium, fermentation process and the components and proportion in the formulation to develop oil-based fungal mosquitocides for outdoor application. This will help address issues including mosquito resistance and environmental pollution caused by massive use of chemical insecticides.
Biao Jiang, Jianhua Yao, Ping Xing, Jia Li and Wanjun Wang of the Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences together with their international partners Ole Skovmand and Sérgio Sousa both of Landcent (Europe) B.V. in The Netherlands will utilize in silico screening to discover mosquito insecticide or repellent compounds in traditional Chinese medicine. At least one safe, environmentally friendly and efficient novel mosquito insecticide or repellent insecticide is expected to be obtained, which will then be used to further develop outdoor vector control technology or products. The development of such mosquito insecticides or repellent compounds will help address insecticide resistance issues and accelerate the global malaria elimination process.
Sibao Wang of the Institute for Biological Sciences, Chinese Academy of Sciences and Duoquan Wang from the China CDC together with their international partners Abdoulaye Diabaté of Institut de Recherche en Sciences de La Santé in Burkina Faso and Marcelo Jacobs-Lorena of Johns Hopkins University in the U.S. will develop procedures to efficiently introduce a specific bacterium into field mosquitoes in order to evaluate effectiveness of the bacterium spread through mosquito populations and to block parasite transmission in a more realistic setting. Introducing anti-Plasmodial symbiotic bacteria into mosquito populations can potentially transform mosquitoes into ineffective vectors. This unconventional approach has already shown promise in the laboratory.
Sanjeev Kumar of The Goat Trust in India will develop animated mobile applications that provide information on improving productivity, veterinary and financial services, and markets for women goat herders in the Indian states of Uttar Pradesh and Bihar to increase their income. These women work in remote regions with limited support, and many are illiterate. They will develop simple applications with health, nutrition, animal husbandry, a marketplace, and management components, and integrate value-chain players such as products and services suppliers. In health, they will develop a decision support tool to help farmers identify diseases using 141 symptoms and to select the most suitable treatment in consultation with vets. For the marketplace, farmers will be able to order quality products and pay directly. There will also be a web-based platform for goat sales. They will develop the applications in consultation with farmers and other stakeholders, and perform pilot testing.
Esther Muiruri of Equity Group Foundation in Kenya will expand their Equity Online-Agriculture platform to provide information on agricultural best practices, including smart-farming innovations, as well as access to financing and markets to initially 200,000, and subsequently up to two million, small-scale farmers in Kenya to improve their productivity and income. They will build the platform to digitally disseminate agricultural information such as soil testing and pest and disease control, which will improve timely planting and crop and livestock management. They will also build in training in financial literacy targeted towards women, who make up the majority of agricultural workers, and access to financial support and tailored insurance products by implementing e-vouchers and loans, digital wallets and a credit scoring system. Market information and direct contacts with potential buyers will also be provided through an online platform.
Shafiq-ul Islam of ACME AI in Bangladesh will produce a smartphone-based system that uses computer vision and machine learning to accurately estimate the weight of cows and goats to help smallholder livestock farmers in rural Bangladesh maximize productivity and profits. Accurately determining livestock weight is challenging for these farmers but critical for determining the right amounts of food and medicines. They will develop a machine learning model and mobile application that uses the smartphone’s camera to process distance, height, and depth information and calculate the weight of the animal to within >90% accuracy. They will test three different business cases, including combining the computer vision-based weighing system with products and service providers, and evaluate the impact on food and medicine purchases, and animal growth and quality, which are directly linked with income.
Mukhlid Yousif of Wits Health Consortium in South Africa will sequence SARS-CoV-2 in sewage samples collected periodically from 40 wastewater treatment facilities across South Africa for the early detection of potentially dangerous variants to inform public health policies. Genome sequencing using sewage samples can monitor the molecular epidemiology and diversity of circulating SARS-CoV-2 variants, and also identify new variants even before they can be detected in the clinic. They will collect a total of 528 wastewater samples over a twelve-month period and process them for sequencing to identify novel mutations or mutations that are unique to variants-of-concern, especially those not yet reported in Africa. They will also compare these data with sequences of SARS-CoV-2 variants from local COVID-19 patients to support interpretation of wastewater sequencing results. Results will be immediately published online and communicated to provincial and national COVID incident management teams.