Awards

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.

Penny Moore of the National Institute for Communicable Diseases in South Africa together with Adriana Bonomo of Fiocruz in Brazil will identify solutions for combating new SARS-CoV-2 variants by developing an in vitro assay to predict new variants and identifying broad specificity antibodies for use as new drugs and diagnostics. Despite the success of vaccines and antibody therapies, the continual emergence of new viral variants, which thwart our immune defenses and therapies, remains a major challenge of the pandemic. They will develop a virus training assay by culturing existing variants with hyper-immune sera from infected individuals in South Africa and Brazil to drive selection of new mutations and identify potential new variants. They will also isolate new monoclonal antibodies directed to conserved cleavage sites of the viral spike protein, which are essential for it to infect cells, that could be used as treatments to block infection by a wide range of variants.

Sana Syed of the University of Virginia in the U.S. together with Imran Nisar of Aga Khan University in Pakistan will utilize metabolic modeling of patient-derived ‘omics data from pre-existing maternal and pediatric cohorts to identify new biomarkers and therapeutic targets for environmental enteropathy (EE), which is associated with impaired childhood growth and development and vaccine responses. They will leverage a computational, flux-balance analysis-based approach to analyze large transcriptomic and proteomic datasets from pregnant mothers and infants with EE to identify disease-associated metabolic signatures. The signatures derived from pregnant mothers might precede the development of EE and reveal pharmaceutical targets for prevention. They will also develop a duodenal enteroid cell culture model derived from biopsies of children with EE to test whether the identified infant-derived metabolic signatures can be disrupted with existing pharmacological agents as potential new treatments.

Elizabeth Batty of the University of Oxford in the United Kingdom will use metagenomic next generation sequencing to identify pathogens in patient samples that are negative by all other diagnostics, to better understand the causes of febrile illness in South and Southeast Asia. Although studies have identified a broad spectrum of pathogens underlying non-malarial febrile illness, the cause of fever remains unknown in more than half of patients. Febrile illness causes substantial morbidity and mortality, and correct diagnoses are needed to ensure that patients receive the appropriate treatments. They will collect samples in multiple healthcare centers in Bangladesh, Lao PDR and Thailand, and use multiplex PCR and serological tests that detect the most common causes of acute fever. Up to 300 samples that test negative using these approaches will be sent to the central Mahidol-Oxford Tropical Medicine Research Unit laboratories in Bangkok for metagenomic sequencing and bioinformatic analysis.

Kanny Diallo of the Centre Suisse de Recherches Scientifiques en Côte d'Ivoire will use metagenomic sequencing to investigate the etiological diversity of meningitis in Mali, Guinea, and Côte d’Ivoire, three countries in the so-called African meningitis belt, to improve diagnosis and public health responses. The African meningitis belt stretches from Senegal to Ethiopia and has the highest burden of meningitis worldwide. Meningitis can be caused by many different types of pathogens (bacteria, virus, fungi, and parasites), which vary between countries. Although 35 meningitis-causing pathogens are detectable by current PCR-based techniques, over 80% of cases remain undiagnosed suggesting that other pathogens are involved. They will perform a prospective study by collecting 65 cerebrospinal fluid samples from children under 5 years old with suspected meningitis and apply an unbiased metagenomic approach to identify both known and unknown pathogens. Their results will also help inform the design of new vaccines.

Jennifer Fitzpatrick of Zambart in Zambia will design and implement a one-step multiplex whole genome sequencing platform for the diagnosis of female genital schistosomiasis (FGS), sexually transmitted infections (STIs) and vaginal microbiome analysis in Zambia. FGS is caused by Schistosoma haematobium and affects around 56 million women in sub-Saharan Africa. Current diagnostic capabilities for STIs and FGS are inadequate and many patients are either incorrectly treated, overtreated or receive no treatment at all. They will use 525 self-taken vaginal swabs to develop the sequencing assay and follow-up with self-taken cervicovaginal swabs and S. haematobium eggs taken from up to 2,000 sexually active girls and women aged 15 to 50 for further development and implementation of the platform to enable the rapid identification of known and new pathogens. They will also characterize the cervicovaginal flora to gain insights into its role in sexual and reproductive health.

Karifa Kourouma of the Centre National de Formation et de Recherche en Santé Rurale (CNFRSR) de Maferinyah in Guinea will integrate metagenomic sequencing into an existing viral hemorrhagic fever surveillance platform in Guinea to enable identification of a broad range of known and unknown infectious pathogens. Guinea is a hotspot for viral hemorrhagic fevers such as Ebola and dengue. The current platform uses PCR-based diagnostics but these lack sensitivity and can only detect a handful of known viruses. Metagenomic sequencing can identify a much broader range of pathogens as well as unknown pathogens enabling earlier detection of outbreaks. They will leverage an existing biobank of plasma and serum samples from patients with viral hemorrhagic fever and test the ability of metagenomic sequencing to identify known and unknown pathogens. They will also implement their approach into the existing platform for ongoing sequencing of new patient samples.

Solomon Langat of the Kenya Medical Research Institute in Kenya will develop a targeted viral enrichment protocol to improve the sensitivity of metagenomic sequencing for detecting known and novel vector-borne and viral hemorrhagic fever viruses. Infectious disease outbreaks caused by arboviruses and other viral infectious pathogens are common, particularly in Kenya. Current methods for diagnosing these infections have limited sensitivity and only detect known pathogens. In contrast, high-throughput sequencing and metagenomics can broaden detection capabilities to unknown pathogens and is also a rapid approach for monitoring outbreaks in real time. However, background noise from host nucleic acids can limit its sensitivity. They will design broadly-targeting hybridization probes to capture entire families of viruses before sequencing to improve the sensitivity of detection and test them on confirmed positive and negative samples. They will also use their method on samples from the ongoing national arbovirus surveillance program.

Vinicius de Araujo Oliveira of Fiocruz in Brazil will develop a framework for the re-use of large clinical and administrative datasets to enable comparative analysis of COVID-19 vaccine safety and effectiveness in Brazil and in Pakistan, with colleagues at Shaukat Khanum Memorial Cancer Hospital and Research Centre there, to improve pandemic responses and promote data-driven evidence generation in the Global South. Monitoring vaccinations across different settings is crucial for containing pandemics. However, comparative analysis of large health datasets in different scenarios is challenging due to concerns around safety and reproducibility and the loss of the context in which the data was collected, which can affect research results. They will adapt data science standards and tools to different local health system scenarios and run individual and joint vaccine effectiveness analyses for the two countries to assess compatibility and reproducibility of the findings. They will also build a public data visualization dashboard for health managers and policymakers to monitor the pandemic, particularly in vulnerable populations.

Henrique Dias of the Instituto de Inteligencia Artificial na Saude in Brazil will determine whether AI can produce an accurate hospital discharge summary to ensure that essential information is passed to the next healthcare provider and patient care is maintained. Discharge summaries are often incomplete, unclear, or delayed in terms of their delivery due to the document construction process. They will test two AI models to produce discharge summaries - one trained by health professionals completing electronic medical records, and the other trained with 46 GB of data in Portuguese, corresponding to 38 million clinical notes from 70 hospitals. They will perform a retrospective, non-inferiority, single-blind study to compare the quality and speed of the discharge summaries produced by both AI models with those produced by medical professionals.