Bjørn Blomberg

Infections with bacteria which have evolved multi-drug resistance (MDR) cause millions of deaths worldwide. Large-scale efforts are gathering genotypic and phenotypic data on MDR bacteria, but methods for learning the structure, diversity, and predictors of evolutionary pathways to MDR have yet to take full advantage of these data. Here, we use evolutionary accumulation modelling (EvAM), an emerging class of machine learning methods with roots in cancer progression, to infer these evolutionary pathways across ESKAPEE pathogens (seven bacterial species that dominate health burdens), using a database of over 635k genotyped phenotypic observations from around the world. We identify global patterns in MDR evolutionary pathways, remarkably shared across multiple ESKAPEE species. Species-specific deviations from these stereotypical pathways are connected with geographical and demographic covariates, facilitating predictions of future MDR evolution. We verify these predictions with several hundred new phenotypes from ESKAPEE samples spanning decades of clinical infections in sub-Saharan Africa, demonstrating the capacity to forecast future MDR evolution from these inferred shared pathways.

On November 14th, 2025, the Ethiopian Ministry of Health confirmed the country’s first Marburg virus outbreak, representing another in a series of recent outbreaks across Africa in only 3 years. Marburg virus disease (MVD) is a highly lethal zoonotic haemorrhagic fever caused by the Marburg virus. This review synthesises the current evidence on MVD, covering epidemiology, pathogenesis, diagnostics, and emerging countermeasures, such as investigational antivirals and vaccines. Despite the severity of the disease outcome, no licensed treatment or vaccine exists. Recent outbreaks, including Rwanda (2024), Tanzania and Ethiopia (2025), have accelerated evaluation of investigational therapeutics such as remdesivir and monoclonal antibody MBP091 under expanded access and early‑phase studies; no randomised human efficacy data are currently available for MVD, alongside novel platforms including mRNA and adenovirus-vectored vaccines. Advances in molecular virology have helped to elucidate mechanisms of immune evasion and viral persistence, informing strategies for targeted interventions. Diagnostic capacity and therapeutic deployment remain constrained in resource-limited settings. Strengthening global preparedness will require integrated surveillance, rapid clinical trial frameworks, and equitable access to vaccines and antivirals.

Background: Identifying and addressing long-term health and societal challenges after COVID-19 is a research priority. Objectives: To create an international, multidisciplinary COVID-19 database, and synthesise long-term outcomes, predictors and costs. Design: Systematic identification of COVID-19 data sets and meta-analysis of individual participant data on long-term outcomes after COVID-19. Setting: Contributed data were collected in clinical, community and research settings. Interventions: Interventions from original studies were included as covariates in models. Data sources: MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, PsycInfo ^® (American Psychological Association, Washington, DC, USA), Cumulative Index to Nursing and Allied Health Literature, World Health Organization Global Index Medicus, Epistemonikos, LitCOVID; World Health Organization International Clinical Trials Registry Platform; ClinicalTrials.gov and supplementary searches for studies (November 2019–November 2021) were searched for studies on > 10 people from cohort, case-control, survey or randomised controlled trial studies, across any setting, describing validated assessment instruments, symptoms, hospitalisation, discharge destination or mortality beyond 28-days after COVID-19 onset. Data were extracted by two independent reviewers. Methods: Principal investigators contributed fully anonymised individual participant data. Demography, equity and symptoms were described. Assessment instruments were mapped to the International Classification of Functioning, Disability and Health. Factors associated with outcomes at 3–6 months, 9–12 months and beyond 12 months of index infection, for n > 500 individual participant data and > 1 data set were described using ratio of difference, point estimates, odds ratio and 95% confidence interval, as appropriate. The Mixed Methods Appraisal Tool described study quality; models were appraised using a Grading of Recommendations Assessment, Development and Evaluation-informed approach; heterogeneity was described using I ² . Outcome measures: Included overall perception of health, multidomain cognitive function, anxiety, depression, stress, post-traumatic stress disorder, fatigue, strength, walking ability, mobility, coping with daily life, breathlessness, mortality, later hospitalisation and health-related quality of life. Results: PRECIOUS collated 116 data sets from 40 countries (individual participant data = 62,849), comprising 20 randomised controlled trials, 13 case-control, 60 cohort 2 longitudinal, 1 survey and 20 other study types. Participants’ median age was 58 years interquartile range (45–68); 34,185 (54.4%) were female; 158 unique symptoms and 137 unique assessment instruments were captured, predominantly describing International Classification of Function, Disability and Health-body functions. Women had poorer outcomes across 30/37 models, compared with men. In 15/37 models, pre-existing lung disease and increasing age were associated with poorer outcomes; hospitalisation, diabetes and chronic kidney disease were each associated with poorer outcomes in 8/37 models. Initial hospitalisation resulted in lower health-related quality of life that did not recover for up to 2 years after initial infection. Heterogeneity was low in 34/37 models; 22/37 models were of moderate and 11/37 were of low quality. Limitations: Use of secondary data limits available covariates, outcomes and time points to those included in primary data sets; evidence was primarily based on high-income countries. There was a lack of data on longer-term healthcare resource use to estimate the costs to the healthcare system. Conclusions: PRECIOUS contributes to the overall picture of long-term COVID-19 outcomes beyond the long-COVID condition and highlights poorer long-term outcomes in women and people with pre-existing comorbidities. Future work: Evidence gaps included healthcare resource use, isolation, loneliness, societal participation and return to work outcomes. Data are needed on the role of health inequity on long-term outcomes. Study registration: This study is registered as PROSPERO (CRD42020224323, IRAS ID: 293578). Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR132895) and is published in full in Health and Social Care Delivery Research ; Vol. 14, No. 29. See the NIHR Funding and Awards website for further award information.

Background: Paediatric sepsis remains a significant global health issue, with the highest burden in low- and middle-income countries. Widespread antimicrobial resistance makes standard first-line empiric treatment regimens ineffective. To explore potential alternatives, we compared antimicrobial resistance patterns in blood culture isolates from two previous cohort studies on children admitted to hospital with fever in Tanzania, with focus on resistance to the semisynthetic aminoglycosides amikacin and plazomicin. Methods: Antimicrobial susceptibility testing was conducted using minimum inhibitory concentration (MIC) strips, with results interpreted according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) clinical breakpoints. Resistance rates to current recommended empiric sepsis treatments and potential new regimens with ampicillin combined with amikacin or plazomicin were assessed. Whole genome sequencing was performed on Klebsiella , Escherichia , and Salmonella isolates. Results: Antimicrobial susceptibility testing was conducted on 449 blood culture isolates from 427 patients, and whole genome sequencing was performed on 216 isolates. Overall resistance rates to gentamicin-ampicillin and ceftriaxone were 46% and 50%, respectively, while resistance to amikacin-ampicillin and plazomicin-ampicillin was 9%. We estimate that by using amikacin-ampicillin instead of gentamicin-ampicillin, we can reduce the risk of ineffective antibiotic treatment by 37 percentage points (95% confidence interval: 32%-42%). Correspondingly, using amikacin-ampicillin instead of ceftriaxone would reduce the risk by 41 percentage points (95% confidence interval: 35%-46%). In Klebsiella pneumoniae and Escherichia coli ceftriaxone resistance primarily resulted from the bla _CTX-M-15 gene, while resistance to gentamicin was mainly due to the aac(3)-II gene. The aac(6′)-Ib-cr gene was found in 33 Klebsiella and E. coli isolates, although only three exhibited amikacin MICs above the clinical breakpoint. Conclusion: This in vitro analysis suggest that amikacin-ampicillin is a promising option as first-line empiric treatment of suspected sepsis in children in Tanzania. The clinical efficacy and safety need to be evaluated in clinical trials.

The rapid expansion of antimicrobial resistance (AMR) among Gram-negative pathogens presents a major clinical challenge, particularly in vulnerable populations such as infants. The dissemination of resistance is often mediated by mobile genetic elements (MGEs) that can mobilise antimicrobial resistance genes (ARGs) both within and between genomes. The insertion sequence (IS) IS 26 , is a MGE with the ability to replicate itself and associated ARGs, create translocatable units (TU), and produce tandem arrays of ARGs. Here we present the 18-week in vivo evolution of a community-acquired multi-drug resistant (MDR) Escherichia coli colonising an infant gut, characterised by a de-amplification of an IS 26 -mediated tandem array of ARGs. The hybrid-assembled ancestral and descendant strain genomes show an evolutionary rate of 10.22 SNPs per genome per year. Independent analysis of the hybrid genome assembly, and of Oxford Nanopore Technologies (ONT) and Illumina read-mapping support the existence of at least five copies of a TU (Tn 3 -like( tnpA )- tetR-tetA-yedA- ΔTn 1721 ( tnpA ) - IS 26 - aac(6’)-Ib-cr-bla _OXA-1 - Δ catB3 -IS 26 ) in the ancestor and only one in the descendant. Despite de-amplification, no change in fitness (p = 0.275) and piperacillin-tazobactam susceptibility (TZP) was observed. In contrast, gentamicin susceptibility increased, in the absence of known associated mutations. This study provides insight into IS 26 -mobility dynamics in vivo and their implications for AMR, within the rapidly changing environment of the neonatal gut.

Bloodstream infections (BSIs) are a major cause of hospitalisation and death for children under the age of five in sub-Saharan Africa, with Gram-negative bacteria such as Klebsiella pneumoniae and Escherichia coli among the most common causative agents. These bacteria usually colonise the human gastrointestinal (GI) tract, which has been identified as a reservoir for invasive infections into extra-intestinal environments such as the urinary tract and bloodstream. In this study we used comparative genomics to compare hybrid genome assemblies of blood and faecal bacterial isolates taken from the same patients (all neonates under 19 days old) to determine if the BSI associated isolates and the GI tract associated isolates were related. Multiple pairs of highly related E. coli and K. pneumoniae were found, suggesting that translocation between the GI tract and the bloodstream occurred in multiple cases of BSI. We also highlight key virulence genes and acquired mutations that are indicative of pathogenic strains capable of BSI. These findings expand our understanding of the Gram-negative bacteria involved in BSI pathogenicity and could help guide targeted interventions to prevent future BSI infections in neonates.

Background: The high prevalence of long-term persisting symptoms after COVID-19 (coronavirus disease 2019), termed long COVID or post-COVID-19 condition, even among those with mild initial disease, may have a large public health impact. Apart from avoiding infection, there is no proven prevention or treatment for long COVID. We will perform a randomized placebo-controlled clinical trial to assess whether treatment with the novel antiviral, nirmatrelvir and ritonavir (Paxlovid®) for acute COVID-19 can prevent the development of long COVID. Methods: This is a randomized double-blinded placebo-controlled trial that aims to recruit 2000 nonpregnant persons aged 18 to 64 years with acute COVID-19 with positive PCR and/or antigen test and symptom duration of not more than 5 days. Participants will be randomized 1:1 to a 5-day course of Paxlovid (two tablets 150-mg nirmatrelvir and one tablet 100-mg ritonavir twice daily) or a 5-day course of placebo (similar number of tablets of equal appearance). The primary endpoint will be persistent symptoms compatible with long COVID, assessed as the prevalence of a dichotomous variable corresponding to the presence (1) or absence (0) of one or more of the following symptoms: (i) fatigue, (ii) dyspnea, and (iii) cognitive symptoms (memory and/or concentration problems). The primary outcome will be evaluated at 3-month follow-up and then re-evaluated at 6, 12, and 24 months. Discussion: As more than 750 million people with confirmed COVID-19 have survived globally, the potential burden of long COVID on societies is formidable. If a simple 5-day oral treatment course with nirmatrelvir/ritonavir is shown to prevent long COVID, it would be a highly attractive intervention at an individual level and a mitigation of its public health consequences. Trial registration: ClinicalTrials.gov NCT05852873. Registered on May 2023.

Antimicrobial resistance (AMR) is a substantial and growing global health burden. Understanding, and predicting, its evolution in specific pathogens will help responses across scales from individual patient cases to large-scale policy. Here, we use global data on AMR features, predicted from 47k Klebsiella pneumoniae genomes, with hypercubic transition path sampling to infer the evolutionary pathways by which AMR features in K. pneumoniae (KpAMR) are acquired across 102 countries, territories and areas. We identify “globally consistent” evolutionary behaviours that hold across countries, and “globally divergent” behaviours including carbapenem and fluoroquinolone resistance that vary across countries. We show how these divergent dynamics covary both with public health superregion and drug use policy, and reveal competing evolutionary pathways within and between countries. Using newly-sequenced data across several decades from sub-Saharan Africa, we show that this inferred global roadmap of KpAMR evolution successfully predicts prospective evolutionary dynamics. Together, we hope that the ability to characterize and predict evolutionary dynamics of AMR acquisition, connected to socio-economic and drug policy predictors, will help strengthen our understanding of AMR evolution worldwide. Significance: Antimicrobial resistance (AMR) occurs when microbial pathogens evolve resistance to the drugs we use to treat them. Our understanding of bacterial genomes and how they confer AMR is constantly expanding through beautiful and powerful work establishing large-scale global datasets. Here, we use emerging machine learning approaches with this genomic data to reveal the evolutionary dynamics that have generated AMR characters in a particular pathogen, Klebsiella pneumoniae (Kp), and how these dynamics are influenced by geography and drug use across the globe. This “natural history” of AMR in Kp makes predictions about which characters will evolve next for a given bacterium, and we validate these predictions with newly-sequenced data from clinical isolates from Africa, providing both past and prospective descriptions of AMR in Kp.