Tuberculosis (TB) is the single biggest infectious cause of death globally, a situation worsened by COVID-19. Revolutionary new TB triage tests are required, including at facilities where people are accessible and efficiently referable to confirmatory testing. The Cough Audio triaGE for TB (CAGE-TB) study was EDCTP2-funded to 1) collect cough sounds at people’s point-of-entry into primary care facilities (South Africa) and derive an audio classifier, 2) validate diagnostic accuracy in independent cohorts (South Africa, Uganda), and 3) deploy mixed methods research (costing, implementation science, medical anthropology) to inform design and implementation so that this classifier, which will report people as “likely TB” or “unlikely TB” for confirmatory testing, is embedded within a user-friendly mHealth app with on-device offline computation. Per the original call’s objective, CAGE-TB’s goal was to deliver an accurate validated mHealth app usable in trials assessing clinical outcomes (necessary for adoption). Uniquely, this pure mHealth innovation mitigates barriers that jeopardise target product profile criteria (e.g., reagents, cold-chain, transport, infrastructure). After CAGE-TB hired personnel, COVID-19 prevented and slowed recruitment (people had limited clinic access, recruitment interrupted by successive COVID-19 waves). Throughout this, CAGE-TB paid personnel and trainees, resulting in severe budget overruns without participant recruitment, and limited trainee progress and site visits. In 4-CAGE-TB we request essential support over two years to accomplish the original scope-of-work, ensure trainees can finish degrees and, due to the longer recruitment period, accommodate critical additional site visits. COVID-19 has only reinforced our premise: it caused TB to increase for the first time in a decade, damaged already weak facility-based triage practices, and accelerated cough classification technologies.

SoNAR-Global is a global consortium led by social scientists specializing in emerging infectious diseases (EID) and antimicrobial resistance (AMR). It will build a sustainable international social science network to engage the active participation of social sciences and promote complementarity and synergy in the governance of prevention and response to infectious threats and AMR. As such, it will become an integral part of emergency response. Partnering with major international and regional institutions, it will lead activities through a program that builds governance from the ground up. It will: • Develop an open-access platform to support the SoNAR-Global activities and to share them broadly. • Adapt, test, and evaluate vulnerability assessment tools on the ground and engagement models to facilitate collaboration across multiple stakeholders. • Create, pilot, and evaluate curricula for training social scientists in preparedness and response to infectious threats and through curricular development and piloting social science knowledge of infectious threats among non-social sciences actors.

The 21st century witnesses increased incidence of epidemics (Zika, dengue, Ebola, SARS), with as latest highlight the recent COVID-19. Following the outbreak of several infectious diseases during the last few decade, the need for generating real-time pathogen genomic data for public health action has become more important than ever. In the African context, infrastructure, human resource capability, data analysis, including bioinformatics, lack of linkage between clinical, epidemiological, and pathogen genomic data as well the interaction between clinicians, researchers and decision makers are some of the major challenges. The aim of the EpiGen project is to build a capacity for integrated pathogen genomic surveillance for informed public health decision process. The overarching specific objectives include strengthening collection and analysis of clinical and epidemiological data, enhancing the capacity and capability for pathogen genomic sequencing, including strengthening the laboratory infrastructure, human work force, pathogen genomic data analysis, and the integration of metadata with genomic data, developing and implementing innovative digital diagnostic platforms, creating semi-real time mobile phone applications for policy decisions, and promoting communities of practice and knowledge exchange through fostering African collaboration and networking in the domain of pathogen genomic surveillance for infectious diseases. EpiGen project’s multi-disciplinary consortium is drawn from several institutions from Ethiopia engaged in National Public Health Programs, and EU partners (The Netherlands, Spain and Germany). Overall, the model approach proposed by EpiGen will enhance Ethiopia’s national effort in mitigating the threat of infectious diseases. The implementation of a national genomic-informed surveillance for infectious diseases will play significant public health role towards contributing to disease prevention and control programmes in Ethiopia and beyond.

The END-VOC consortium will support the European and global response to the COVID-19 pandemic and Variants of Concern (VOC) through well characterised cohorts and linked with existing European and international initiatives. END-VOC consists of 19 partners in Europe (UK, Spain, Italy, Germany, Netherlands, Norway, Italy), South America (Brazil and Peru), Africa (Mozambique, South Africa, Nigeria and 13 ANTICOV African countries), Middle East (Palestine) and Asia (India, Pakistan, Philippines) with a focus on countries affected by VOCs and VOIs. We will elucidate the global circulation of the current and emerging SARS-CoV-2 VOCs and their characteristics, including transmissibility, pathogenicity and propensity to cause reinfection, to support best control strategies and the development of diagnostics; evaluate the impact of VOCs on the effectiveness of different vaccines and vaccination strategies; and assess the implications of VOCs on the choice of optimal treatment options. END-VOC will also investigate how VOCs alter long-term post-infection sequelae and where new VOCs emerge within hosts using our clinical cohorts. We will inform future preparedness and response working closely with international and national public health organisations and existing cohort consortia. Specific beyond state-of-the-art components of END-VOC include the use of novel phylogenetic prediction tools and mathematical modelling; generation of powerful cohorts through sentinel surveillance in low and middle income settings and cohorts of travellers to increase our global reach; use of novel predictive modelling of clinical outcomes by VOC and comorbidity/treatment and evaluation of differences in natural and vaccine immunity by VOC; antiviral screening models within cohorts and an artificial intelligence driven tool for the prediction of long COVID.