Gerald Mboowa

The past 2 years, during which waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants swept the globe, have starkly highlighted health disparities across nations. Tegally et al. show how the coordinated efforts of talented African scientists have in a short time made great contributions to pandemic surveillance and data gathering. Their efforts and initiatives have provided early warning that has likely benefited wealthier countries more than their own. Genomic surveillance identified the emergence of the highly transmissible Beta and Omicron variants and now the appearance of Omicron sublineages in Africa. However, it is imperative that technology transfer for diagnostics and vaccines, as well the logistic wherewithal to produce and deploy them, match the data-gathering effort.

Five years before the 2022 multi-country mpox outbreak, Nigeria and Cameroon reported their first cases in over three decades.1,2 While Nigeria’s outbreak is recognized as an ongoing human epidemic, the drivers of Cameroon’s resurgence remain unclear.3,4 The rate of zoonoses remains uncertain in both countries, and gaps in genomic data obscure the timing, zoonotic and geographic origin of mpox virus (MPXV) emergence in humans. To address these uncertainties, we generated 118 MPXV genomes from Nigeria and Cameroon from 2018-2023. Our findings show that, in contrast to Nigeria, cases in Cameroon are the result of repeated zoonoses, with two distinct zoonotic lineages circulating across the Nigeria-Cameroon border. Our findings suggest that shared animal populations in the cross-border forest ecosystems drive virus emergence and spread. Accordingly, we identify the closest zoonotic outgroup to the Nigerian human epidemic lineage (hMPXV-1) in a southern Nigerian border state. We estimate that the shared ancestor of the zoonotic outgroup and hMPXV-1 circulated in animals in southern Nigeria in late 2013. We estimate that hMPXV-1 emerged in humans in August 2014 in the southern Rivers State and circulated undetected for three years. Rivers State acted as the main source of viral spread across the human epidemic. Our study sheds light on MPXV’s recent establishment in the human population and highlights the risk of persistent zoonotic emergence of MPXV in the complex border regions of Cameroon and Nigeria.

High-income countries have a wealth of genomics expertise that can be rapidly activated to deal with disease threats. African countries should invest in a federated data-management system for genomics epidemiology to deal with such threats better.

Rapid expansion of pathogen sequencing capacity in Africa has led to a paradigm shift from relying on others to locally generating genomic data and sharing it with the global community. However, several barriers remain to be unlocked for timely processing, analysis, dissemination, and effective use of pathogen sequence data for pandemic prevention, preparedness, and response.

The haemoglobinopathies transfusion-dependent β-thalassemia (TDT) and sickle-cell disease (SCD) are two globally prevalent and severe monogenic blood disorders. These conditions impose substantial morbidity and mortality, and their burden falls disproportionately on populations in sub-Saharan Africa, the Middle East and parts of Asia, underscoring the global health significance of any curative approach. In 2021, a study by Frangoul et al. marked a defining moment for genomic medicine and global health. Published in The New England Journal of Medicine, the authors reported the clinical application of CRISPR–Cas9 genome editing to treat two patients with TDT or SCD.

Antimicrobial resistance (AMR) remains a significant global health threat particularly impacting low- and middle-income countries (LMICs). These regions often grapple with limited healthcare resources and access to advanced diagnostic tools. Consequently, there is a pressing need for innovative approaches that can enhance AMR surveillance and management. Machine learning (ML) though underutilized in these settings, presents a promising avenue. This study leverages ML models trained on whole-genome sequencing data from England, where such data is more readily available, to predict AMR in E. coli, targeting key antibiotics such as ciprofloxacin, ampicillin, and cefotaxime. A crucial part of our work involved the validation of these models using an independent dataset from Africa, specifically from Uganda, Nigeria, and Tanzania, to ascertain their applicability and effectiveness in LMICs.

Polygenic risk scores (PRS) show promise but have accuracy disparities across ancestries due to underrepresentation in the existing genomic databases. Here, we outline the initiative of All of Us Research Program in refining PRS and advancing genomic medicine for all.

We propose a novel, non-discriminatory classification of monkeypox virus diversity. Together with the World Health Organization, we named three clades (I, IIa and IIb) in order of detection. Within IIb, the cause of the current global outbreak, we identified multiple lineages (A.1, A.2, A.1.1 and B.1) to support real-time genomic surveillance.

Rationale: Airborne transmission of Mycobacterium tuberculosis results from incompletely characterized host, bacterial, and environmental factors. Sputum smear microscopy is associated with considerable variability in transmission. Objectives: To evaluate the use of cough-generated aerosols of M. tuberculosis to predict recent transmission. Methods: Patients with pulmonary tuberculosis (TB) underwent a standard evaluation and collection of cough aerosol cultures of M. tuberculosis. We assessed household contacts for new M. tuberculosis infection. We used multivariable logistic regression analysis with cluster adjustment to analyze predictors of new infection. Measurements and main results: From May 2009 to January 2011, we enrolled 96 sputum culture-positive index TB cases and their 442 contacts. Only 43 (45%) patients with TB yielded M. tuberculosis in aerosols. Contacts of patients with TB who produced high aerosols (≥10 CFU) were more likely to have a new infection compared with contacts from low-aerosol (1-9 CFU) and aerosol-negative cases (69%, 25%, and 30%, respectively; P = 0.009). A high-aerosol patient with TB was the only predictor of new M. tuberculosis infection in unadjusted (odds ratio, 5.18; 95% confidence interval, 1.52-17.61) and adjusted analyses (odds ratio, 4.81; 95% confidence interval, 1.20-19.23). Contacts of patients with TB with no aerosols versus low and high aerosols had differential tuberculin skin test and interferon-γ release assay responses. Conclusions: Cough aerosols of M. tuberculosis are produced by a minority of patients with TB but predict transmission better than sputum smear microscopy or culture. Cough aerosols may help identify the most infectious patients with TB and thus improve the cost-effectiveness of TB control programs.

The recent re-emergence of multidrug-resistant pathogens has exacerbated their threat to worldwide public health. The evolution of the genomics era has led to the generation of huge volumes of sequencing data at an unprecedented rate due to the ever-reducing costs of whole-genome sequencing (WGS). We have developed the Rapid Microbial Analysis Pipeline (rMAP), a user-friendly pipeline capable of profiling the resistomes of ESKAPE pathogens ( Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumoniae , Acinetobacter baumannii , Pseudomonas aeruginosa and Enterobacter species) using WGS data generated from Illumina’s sequencing platforms. rMAP is designed for individuals with little bioinformatics expertise, and automates the steps required for WGS analysis directly from the raw genomic sequence data, including adapter and low-quality sequence read trimming, de novo genome assembly, genome annotation, single-nucleotide polymorphism (SNP) variant calling, phylogenetic inference by maximum likelihood, antimicrobial resistance (AMR) profiling, plasmid profiling, virulence factor determination, multi-locus sequence typing (MLST), pangenome analysis and insertion sequence characterization (IS). Once the analysis is finished, rMAP generates an interactive web-like html report. rMAP installation is very simple, it can be run using very simple commands. It represents a rapid and easy way to perform comprehensive bacterial WGS analysis using a personal laptop in low-income settings where high-performance computing infrastructure is limited.

Your Editorial on efforts to agree a global pandemic treaty (Nature 629, 727; 2024) emphasizes that genomic surveillance and pathogen and data sharing are key to effective infection control and development of therapies. With investment spurred by COVID-19, more than 70% of African Union (AU) member states have developed local capacity to sequence pathogen genomes (M. Makoni Lancet Microbe 1, e318; 2020), and more than 170,000 genomes of the virus SARS-CoV-2 have been sequenced and shared. In collaboration with AU member states, the Africa Centres for Disease Control and Prevention (CDC) is creating a biobanking network across the continent to address pathogen sharing. Led by the AU and the Africa CDC, a Common African Position on Pandemic Prevention, Preparedness, and Response was adopted in February 2024. Agreement on a pathogen-access and benefit-sharing system — which will allow rapid exchange of sequence data and equitable and timely access to countermeasures for pandemic preparedness and response — will be the most crucial outcome of the pandemic treaty. Sharing of pathogen data, reciprocated with multilateral benefits, can provide a guarantee of safety and equity for people all over the world, whether in higher- or lower-income countries.