Fogarty International Center

To analyse the landscape of active US National Institutes of Health (NIH) artificial intelligence (AI) health research grants, with emphasis on studies conducted in low- and middle-income countries (LMICs), to characterise use cases, health challenges addressed and gaps relevant to the ethical and responsible application of AI-enabled health science. Descriptive portfolio analysis of NIH-funded AI health research grants. NIH research portfolio analysis, with a focus on global health studies in LMICs. None. Data are derived from active NIH-funded grants involving AI applications in health research, as of 31 January 2025. Not applicable (portfolio analysis). Primary measures included the proportion and funding of AI health research grants focused on LMICs and their thematic use cases. Secondary measures compared LMIC-focused and high-income country (HIC)-focused grants by research focus and health area and identified gaps relevant to ethical and responsible AI use in global health. Of 1850 active NIH AI health research grants, 97 (5.2%) focused on LMICs, representing US$40.2 million (2.4%) of the total US$1.66 billion portfolio. compared with HICs, LMIC-based studies emphasised diagnostics and treatment (72.2% vs 66.8%), health system optimisation (18.6% vs 15.6%), disease surveillance and outbreak response (14.4% vs 8.8%), and telemedicine and remote care (7.2% vs 4.4%). HIC-based grants more frequently addressed public health education (10.4% vs 8.2%) and ethics and data governance (12.8% vs 7.2%). All settings emphasised data science training and capacity strengthening, as well as basic research and early-stage AI-augmented tools. LMIC-based studies most often targeted non-communicable diseases (39%), communicable diseases (30%) and health system strengthening (24%). 31 awards were made directly to LMIC-based principal investigators (1.7% of the portfolio), most commonly in South Africa, Kenya and Uganda. NIH investment in peer-reviewed AI-enabled health research is expanding globally. LMIC-focused studies prioritise areas aligned with pressing global health needs, including outbreak detection, disease surveillance, diagnostics and treatment, health system optimisation and remote care. Greater attention to ethics, data governance and public health communication, alongside support for digital infrastructure and meaningful collaboration, may help strengthen the relevance and sustainability of AI-enabled research for population health.

Understanding the geographic spread of emerging respiratory viruses is critical for pandemic preparedness, yet the early spatiotemporal dynamics of the 2009 H1N1 pandemic influenza and SARS-CoV-2 in the United States (US) remain unclear. While mobility and genomic data have revealed important aspects of pandemic spatial spread, several key questions remain: Did the two pandemics follow similar spatial transmission routes? How rapidly did they spread across the US? What role did stochastic processes play in early spatial transmission? To address these questions, we integrated high-resolution disease data with a robust, data-efficient inference framework combining air travel, commuting flows, and pathogen superspreading potentials to reconstruct their spatial spread across US metropolitan areas. The two pandemics exhibited distinct transmission pathways across locations; however, both pandemics established local circulation in most metropolitan areas within weeks, driven by several shared transmission hubs. Early spatial spread was more strongly associated with air travel than with commuting, though stochastic dynamics introduced substantial uncertainty in transmission routes, creating challenges for timely detection and control. Simulations indicate that broad wastewater surveillance coverage beyond top transmission hubs coupled with effective infection control may slow initial spatial expansion. Our findings highlight the rapid, stochastic spread of pandemic respiratory pathogens and the difficulties of early outbreak containment.

The influenza A H1N1pdm09 virus continues to pose a significant zoonotic threat, with implications for both animal and human health. Italy, which hosts one of the largest swine populations in Europe, is strategically positioned to monitor the evolution of influenza viruses in livestock. This study addresses the genetic diversity and transmission dynamics of H1N1pdm09 in Italian swine, using whole-genome sequencing and dynamic modelling of samples collected from farms across the country. Our findings indicate multiple independent introductions of H1N1pdm09 into Italy. While most were self-limiting, six distinct transmission clusters suggest localized and sustained spread across various regions. Although many introductions were contained, certain lineages demonstrated the ability to circulate within specific areas. Selective pressure analyses showed strong purifying selection across most viral genes in both swine and human hosts, with non-synonymous to synonymous substitution rate (dN/dS) ratios well below 1. The haemagglutinin gene exhibited a higher dN/dS ratio in swine (~0.28) than in humans (~0.22), indicating slightly relaxed selection in swine. Neuraminidase and non-structural proteins were similarly constrained in both hosts. This study underscores the importance of ongoing genomic surveillance to detect viral circulation and mitigate zoonotic risks. Italy’s contribution supports global influenza monitoring and reinforces the need for a One Health approach that integrates human, animal and environmental health. These insights are crucial for informing public health strategies and improving preparedness for future outbreaks.

Orphan genes, which encode species-specific proteins, are common but are rarely investigated. The SARS-CoV-2 orphan gene, ORF10, has been understudied; in vitro work suggests it may modulate innate immunity. Whether ORF10 influences COVID-19 outcomes in humans remained unknown. Here, analyzing millions of SARS-CoV-2 genomes, we find ORF10 sequences are identical to ancestral Wuhan-Hu-1 haplotype. In all variants of concern, <5% of genomes carry any ORF10 mutation. Despite limited statistical power due to the sparsity of mutated sequences, four ORF10 mutations were associated with less severe clinical outcomes in COVID-19 patients: three affect protein structure, one alters RNA structural dynamics. No mutations were linked to increased severity. ORF10 transcript levels in humans and human models are conditionally discordant from other SARS-CoV-2 genes. ORF10 expression in A549 and 293T cells significantly perturbs oxidative phosphorylation gene expression, disrupts immune gene networks, and shifts expression of 14 novel human transcripts. ORF10 is present in multiple Betacoronavirus pandemicum strains, but absent from SARS-CoV-1-like strains. We propose that this strain-restricted orphan gene contributes to severe COVID-19 in humans, with implications for future therapeutic strategies. These findings underscore the importance of studying recently evolved, potentially overlooked, viral orphan genes as a standard approach in pandemic preparedness.

IntroductionData on the burden of SARS-CoV-2 infections by age group and for different severity levels are lacking. We estimated the South African SARS-CoV-2 disease burden and severity, describing changes in the shape of the disease burden pyramid with successive waves.MethodsWe estimated SARS-CoV-2 medically and non-medically attended illness stratified by severity (mild, severe non-fatal and fatal) during the initial five waves, spanning 1 March 2020 through 13 August 2022. We used individual-level national surveillance, healthcare utilisation and serosurvey data to estimate wave-specific hospitalisation-fatality (HFR) and infection-fatality ratios. We estimated wave-specific incidence rates per 100 000 population with 95% CIs derived from bootstrapping the individual-level data.ResultsOn 13 August 2022, the estimated cumulative number of SARS-CoV-2 infections in South Africa was 104.6 million, of which 399 900 (0.38%) were severe non-fatal and 258 800-289 000 (0.25 - 0.28%) fatal. 29% of severe non-fatal illness and 55 - 60% of deaths occurred outside the hospital. The highest burden of severe and fatal illness was during the Delta wave (wave 3), and the HFR across the initial three waves was similar (range 31–34%). Although there were more infections during the Omicron BA.1 wave (wave 4), there was a substantial reduction in HFR (14%). Successive waves saw a reduction in the rate of increase in mortality and hospitalisations with increasing age.ConclusionsThe substantial South African national burden of SARS-CoV-2 for the initial five waves contradicts the belief of minimal impact in Africa. A high proportion of severe non-fatal and fatal illness occurred outside of the hospital, highlighting the importance of studies of health-seeking and vital registration systems to document the full burden of illness. The highest burden of severe illness and death was in the Delta wave. Following the Omicron emergence, severe illness reduced, and with successive waves, proportionately more children were infected and became ill, suggesting a transition to a more endemic pattern.

Background: Research capacity is a critical element of health emergency preparedness, but metrics are not readily available for many countries. The COVID‑19 pandemic provided an opportunity to use publicly available data to assess correlations between national pre‑pandemic research activity, pandemic research response, and other national socioeconomic characteristics. Methods: National pre‑pandemic (2018-19) research activity was defined as the average of percentile rankings of (1) the average annual number of health science publications in Scopus and (2) the average annual number of clinical trials in the International Clinical Trials Research Platform (ICTRP). National pandemic research response (2020-21) was defined as the average of percentile rankings of (1) average annual number of COVID‑19‑related publications in Scopus and (2) average annual number of COVID‑19‑related clinical trials in ICTRP. Findings: During 2018-19, the median (interquartile range [IQR]) of national annual average health science publications was 415 (108-3,398) and of clinical trials was 21 (4-273). During 2020-21, the median (IQR) of national annual average COVID‑19‑related publications was 85 (18-798) and that of COVID‑19‑related clinical trials was 1.5 (0-11). National COVID‑19‑related research output was strongly correlated with pre‑pandemic research activity (R‑squared 0.89) and much less correlated with Human Development Index (0.26), COVID‑19 case number (0.16), case rate (0.14), gross domestic product (0.11), or population (0.10). In a multivariable linear regression analysis, national pre‑COVID‑19 research activity was the only factor with substantial or statistically significant contribution to explaining variations in COVID‑19‑related research output. Interpretation: National pandemic research responses were most strongly correlated with pre‑pandemic research activity, much more so than with other country characteristics. These findings strongly support global efforts to strengthen research capacity as a critical element of preparedness for health emergencies.

Agency scientists say Trump's assault has left the health institutes demoralized and diminished, their future uncertain.

In 2023, an interdisciplinary group of global health experts from five continents convened a plenary panel at the Consortium of Universities for Global Health (CUGH) annual conference entitled "Reimagining Global Health for the 21st Century." At the heart of this viewpoint article lies a fundamental question: How can we reimagine global health to best confront existing challenges and meet the demands of the future? To fully assess the scope of global health challenges and identify sustainable solutions, a clear definition of the aims and strategic approaches is needed. Such an assessment is also critical for progress in promoting equity, including decolonizing global health. Key issues examined are the following: equity, governance, research, education, and sustainability. To assure a sustainable global health enterprise, we propose the following three strategic imperatives as guiding principles: a holistic, unified approach grounded in mutual benefit, joint investment, long‑term collaborative commitment, and solidarity across low‑ to middle‑income countries (LMICs) and high‑income countries (HICs); joint priority setting of investments in research, education, practice, and workforce development; and collaborative governance, maximizing a multisectoral approach among local, national, regional, and global strategies. The viewpoint sets the stage for the development of an action roadmap to develop a unified concept of global health; identify strategies to ensure sustained funding for global health research, education and training, and practice; establish benchmarks and metrics to measure progress; and design a collaborative governance system to promote interconnectedness and engagement among local, regional, national, and global stakeholders.

Adolescents (10-19 years old) have poor outcomes across the prevention-to-treatment HIV care continuum, leading to significant mortality and morbidity. We conducted a systematic review and meta-analysis of interventions that documented HIV outcomes among adolescents in HIV high-burden countries. We searched PubMed, EMBASE, Scopus, and the Cochrane Library for studies published between January 2015 and September 2024, assessing at least one HIV outcome along the prevention-to-care cascade, including PrEP uptake, HIV testing, awareness of HIV infections, ARV adherence, retention, and virological suppression. We included studies from 37 HIV high-burden countries evaluating interventions with a comparator group. Random-effects meta-analysis was used to pool the effects of the interventions on study outcomes. While the primary focus was on outcomes related to the HIV care cascade, we also evaluated social outcomes and mental health outcomes when sufficient data were available. Adolescent engagement in studies was assessed using Hart's ladder. The study was registered in PROSPERO, CRD42024569203. We identified 12,411 unique records, of which 99 were included in the final analysis, comprising 57 randomized controlled trials and 42 non-randomized studies, with a total sample size of 441,252 participants. Our analysis found that asset-building interventions significantly improved HIV testing uptake (three studies, RR: 1.38, 95% CI 1.15-1.65) compared to control conditions. Differentiated service delivery interventions were associated with improved ART retention (five studies, RR: 1.18, 95% CI 1.04-1.36) and virological suppression (seven studies, RR: 1.19, 95% CI 1.06-1.33) compared to control conditions. Financial incentives significantly enhanced ART adherence (two studies, RR: 1.52, 95% CI 1.23-1.89) compared to control conditions. Digital interventions, such as mobile phone applications and telehealth services, significantly increased HIV testing uptake (two studies, RR: 1.79, 95% CI 1.23-2.61) compared to control conditions. Positive impacts were also observed for these interventions on social outcomes. Most studies adopted minimal to moderate adolescent engagement. For HIV testing, a stronger effect was seen in studies with moderate to substantial adolescent engagement, yielding an RR of 2.37 (95% CI: 1.43-3.93; nine studies), compared to a lower RR of 1.23 (95% CI: 1.15-1.31; 13 studies) in studies with minimal engagement. Notably, the strength of evidence is moderate to low due to the considerable heterogeneity across studies and limited included studies. Our data demonstrate several evidence-based interventions that can enhance adolescent HIV outcomes across the care continuum. Our findings are relevant in many HIV high-burden countries and can help to inform national and regional adolescent HIV policy. This study was supported by UNICEF, the Adolescent HIV Prevention and Treatment Implementation Science Alliance (AHISA), and the US NIH (NIAID K24AI143471, NICHD 1UG1HD113156, UM2HD116395).