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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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.
Vincent Cubaka of Partners In Health in the U.S. will build robust data governance structures to enable the utilization of electronic medical records from multiple countries for research purposes to improve health. So-called FAIR (Findable, Accessible, Interoperable, Reusable) data principles enhance the value of personal medical records for research, and CARE principles were developed to protect the owners of these data. However, the rigidity of these principles can create conflicts, which can make it difficult, for example, to open access to datasets across different countries. To address this, for their current project studying the impact of COVID-19 on chronic care patients across four low- and middle-income countries, they will develop data governance structures and set-up a multi-country community oversight committee to enable full access by researchers to appropriately de-identified individual-level data on a suitable platform.
Ida Viktoria Kolte of Fiocruz in Brazil will employ metagenomic next generation sequencing (mNGS) for the analysis of sputum and blood samples from Indigenous patients to identify the causes of severe lung infection in the rural Amambai district. Brazil's one million Indigenous people suffer a disproportionate burden of infectious and respiratory diseases. Lung infections are challenging to diagnose because they can be caused by viral, bacterial and fungal pathogens and are often associated with co-infections. They will collect samples from 170 patients aged over 18 years presenting with symptoms of severe lung infection from five locations and subject them to next generation sequencing to identify the microorganisms present. They will also use implementation research to identify any cultural barriers that have restricted current diagnostic and therapeutic practices to help more effectively implement the new metagenomic next generation sequencing technology into clinical practice.
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.
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.
Marion Jourdan of Danone Nutricia Research in the Netherlands together with Michael Zimmermann of ETH Zürich in Switzerland will test an approach to enhance iron absorption from food in children in Kenya by providing them with live food-grade bacteria to release phytate-bound iron from popular foods such as cereal flour. Phytates bind strongly to iron and inhibit its absorption. Their previous work identified different bacterial strains containing phytases that could grow in milk, degrade phytates, and release nutritionally-relevant levels of free iron in vitro. They will test different strain combinations for their phytate-degrading activity under different conditions, such as in specific foods and in an environment mimicking the upper GI tract, and select the best one for producing a fermented food product. This will then be tested to assess its effect on iron absorption in a cohort of 22 iron-deficient Kenyan school-aged children.
Aida Badiane of the Universite Cheikh Anta Diop de Dakar in Senegal will use shotgun metagenomic next generation sequencing (mNGS) to identify the pathogens causing nosocomial infections in Senegal to improve diagnosis and treatment. Nosocomial infections (i.e., hospital-acquired) cause substantial mortality in Senegal but remain poorly understood. To create a more complete profile of the causative pathogens, they will apply shotgun mNGS to different types of clinical samples from 61 patients at LeDantec hospital to identify and quantify the pathogens. They will also identify the most suitable sample types for diagnosing the most common pathogens. The sequencing data will be analyzed and shared with clinicians, stakeholders and the global research community, and will help in the development of suitable diagnostic assays. This project will help implement sequencing technologies into the national healthcare system.
Haroon Hafeez of Shaukat Khanum Memorial Cancer Hospital and Research Centre in Pakistan 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 Pakistan and in Brazil, with colleagues at Fiocruz 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.
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.
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.