eLife: latest articles by subject

Understanding pain in women with polyendocrine metabolic ovarian syndrome: health risks and treatment effectiveness

shefali.setiaverma@pennmedicine.upenn.edu (Katherine Sherif) — Fri, 28 Aug 2026 00:00:00 +0000

Heterogeneity of use, access, and retention of insecticide-treated nets: Implications for subnational tailoring to maximise malaria control

a.glover18@imperial.ac.uk (Andrew C Glover) — Thu, 20 Aug 2026 00:00:00 +0000

Using mathematical models to optimise mosquito net distribution

prete@unicamp.br (Carlos A Prete Jr) — Fri, 07 Aug 2026 00:00:00 +0000

Tailoring malaria control interventions to regional transmission dynamics and behavioural characteristics can optimise them in resource-limited settings.

Repurposed small molecule toxin inhibitors neutralise a diversity of venoms from the Neotropical viperid snake genus Bothrops

rachel.clare@edgehill.ac.uk (Adam Westhorpe) — Fri, 31 Jul 2026 00:00:00 +0000

Snakebite globally claims more than 100,000 lives per year and results in morbidity for 400,000 survivors. Current treatment uses antibody-based antivenoms which are constrained by their efficacy, safety, and cost. In this study we evaluated the efficacy of previously described repurposed drugs against viperid snakes of the medically important Bothrops genus. Despite variable toxin representation and bioactivity across this central and south American genus, we found that the lead inhibitors targeting metalloproteinases (marimastat and DMPS) and phospholipases (varespladib) demonstrated pan-species neutralisation in enzymatic assays, whilst nafamostat (serine protease inhibitor) had variable activity. The metalloproteinase inhibitors protected against the procoagulant and haemorrhagic effects of several venoms in phenotypic assays. Collectively these findings demonstrate that repurposed drugs may be of great value as early interventions for the treatment of bothropic envenoming in the Neotropics and thus provide a strong rationale for their progression into future preclinical and clinical evaluation for snakebite indication.

A natural experiment in Kenya reveals durable immunosuppressive effects of early childhood malaria: a longitudinal cohort study

csande@kemri-wellcome.org (Charles J Sande) — Tue, 14 Jul 2026 00:00:00 +0000

Inferring variant-specific effective reproduction numbers from combined case and sequencing data

marlinfiggins@gmail.com (Marlin D Figgins) — Thu, 09 Jul 2026 00:00:00 +0000

Accurately estimating relative transmission rates of SARS-CoV-2 variants remains a scientific and public health priority. Recent studies have used the sample proportions of different variants from genetic sequence data to describe variant frequency dynamics and relative transmission rates, but frequencies alone cannot capture the rich epidemiological behavior of SARS-CoV-2. Here, we extend methods for inferring the effective reproduction number of an epidemic using confirmed case data to jointly estimate variant-specific effective reproduction numbers and frequencies of co-circulating variants using cases and sequences across states in the United States from January 2021 to March 2022. Our method can be used to infer structured relationships between effective reproduction numbers across time series, allowing us to estimate fixed variant-specific growth advantages. We use this model to estimate the effective reproduction number of SARS-CoV-2 variants of concern and variants of interest in the United States, and to estimate consistent growth advantages of particular variants across different locations.

Estimating probabilities of malaria importation in southern Mozambique through modelling P. falciparum genomics and mobility patterns

arnau.pujol@isglobal.org (Alfredo Mayor) — Fri, 26 Jun 2026 00:00:00 +0000

Imported malaria is a critical obstacle to achieving elimination in low transmission settings, but importation classification tools combining human mobility and parasite genomics are lacking. A Bayesian model combining epidemiological, human mobility, and parasite genetic data was developed to estimate malaria importation and geographic origins of Plasmodium falciparum cases. Using microhaplotype-based genetic relatedness from 1605 samples across nine Mozambican provinces in 2022, the study focused on two low-transmission districts in the south: Magude and Matutuine. Parasites from southern Mozambique showed lower genetic relatedness to those from northern/central regions (0.021) than the national average (0.034, p<0.001), indicating limited connectivity. Overall, 42% (88/207) of infections in these districts were classified as imported, mainly originating from Inhambane province (63% [55/88]). Imported cases showed higher parasite complexity than local ones (odds ratios [OR] = 1.3). Importation rates differed markedly between districts – Matutuine (48.60%, 87/179) was far more affected than Magude (10.71%, 3/28) – highlighting the need for localised rather than uniform elimination strategies. In Matutuine, importation appears to be actively sustaining transmission, suggesting that reducing malaria burden in source regions (particularly Inhambane) and targeting travellers from central and northern Mozambique would have the greatest elimination impact.

From multiplicity of infection to force of infection in sparsely sampled high-transmission Plasmodium falciparum populations

qz1111@stanford.edu (Karen P Day) — Tue, 23 Jun 2026 00:00:00 +0000

High multiplicity of infection (MOI), the number of genetically distinct parasite strains co-infecting a host, characterizes falciparum malaria and other infectious diseases under high transmission. High MOI in Plasmodium falciparum accompanies high prevalence of asymptomatic infection despite high exposure, creating a large transmission reservoir that challenges intervention. This pattern is enabled by parasite immune evasion through extensive antigenic diversity. The force of infection (FOI), the number of new infections acquired by an individual host over a given time interval, is the dynamic counterpart of MOI and a key epidemiological parameter for monitoring antimalarial interventions. FOI is difficult and costly to measure, especially in high-transmission regions, requiring cohort studies or model-based inference from repeated cross-sectional surveys. Here, we apply queuing theory to estimate FOI from MOI with two approaches: a two-moment approximation and Little’s Law. We illustrate these methods using MOI estimates obtained under sparse sampling schemes with the ‘varcoding’ approach. Both methods rely on infection duration data from naive malaria therapy patients and are therefore suitable for subpopulations with limited immunity, such as toddlers. We evaluate their performance using output from a stochastic agent-based model and apply the methods to an interrupted time-series study in northern Ghana, before and immediately after a three-round transient indoor residual spraying intervention. By accounting for sampling limitations with a Bayesian framework and bootstrap imputation, both methods yield good and replicable FOI estimates across various simulated scenarios. Their application to the surveys of 1- to 5-year-old children in Ghana indicates a larger than 70% reduction in annual FOI immediately after intervention.

Rift Valley fever virus dynamics in a transhumant cattle system in The Gambia

jarraessa@yahoo.com (Daniel T Haydon) — Fri, 27 Feb 2026 00:00:00 +0000

Rift Valley fever (RVF) is a zoonotic disease of global concern, driven by environmental conditions, vector activity, and livestock mobility. Although RVF has been reported in The Gambia, its epidemiology remains poorly understood. This study developed a compartmental model to study RVF dynamics in the cattle population of the country. The model incorporated seasonally dynamic transmission parameters reflecting transhumant movement and ecological differences between two distinct ecoclimatic regions: the Sahelian area and the Gambia river. Parameterised using serological data linked to household survey data, the model predicted endemic RVF virus (RVFV) circulation within The Gambia and captured temporal infection trends that closely match empirical data. Weak decay rates of seropositivity were required to match predicted and observed age-seroprevalence. Results indicated sustained RVFV transmission during the dry season in the Gambia river eco-region, with a high risk of seasonal virus introductions to the Sahelian eco-region at the start of the wet season via the returning transhumant cattle. Our study highlighted the role of livestock mobility in RVFV epidemiology in The Gambia and the need for targeted control strategies that might include, for example, targeted cattle vaccination or application of topical insecticide treatments for transhumant herds.

Prediction of SARS-CoV-2 transmission dynamics based on population-level cycle threshold values: An epidemic transmission and machine learning modeling study

catherine.hogan@bccdc.ca (Aamir Bharmal) — Mon, 16 Feb 2026 00:00:00 +0000

Polymerase chain reaction (PCR) cycle threshold (Ct) values can be used to estimate the viral burden of Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) and predict population-level epidemic trends. We investigated the use of epidemic transmission modeling and machine learning (ML) based on Ct value distribution for SARS-CoV-2 incidence prediction in British Columbia, Canada, during an Omicron subvariant BA.1-predominant period from November 2021 to January 2022. Using real-world data, we developed an epidemic transmission model that was first validated on outbreak data and subsequently fitted to province-level data to predict incidence. Using simulated data, we developed a ML pipeline including five models to predict the reproductive number as a measure of transmission potential based on Ct value distribution and validated it on out-of-sample province-level data. The epidemic transmission model demonstrated accurate prediction with the real incidence falling within the 95% credible interval of the predicted MCMC chains for both the long-term care facility outbreak and province-level data. The ML models demonstrated good performance with a mean squared error (MSE) lower than 0.17 across all models and improved performance with increasing sample size. The variability of the Ct distribution around the mean was the strongest predictor of the reproductive number. These modeling approaches demonstrated utility for incidence and reproductive number prediction and have potential to complement traditional surveillance in real time to guide public health interventions.

Heterogeneous associations of polygenic indices of 35 traits with mortality: a register-linked population-based follow-up study

hannu.lahtinen@helsinki.fi (Andrea Ganna) — Wed, 11 Feb 2026 00:00:00 +0000

Global risk mapping of highly pathogenic avian influenza H5N1 and H5Nx in the light of epidemic episodes occurring from 2020 onwards

dupas.mc@gmail.com (Cedric Marsboom) — Wed, 28 Jan 2026 00:00:00 +0000

Avian influenza (AI) is a highly contagious viral disease affecting poultry and wild water birds, posing significant global challenges due to its high mortality rates and economic impacts. Highly pathogenic avian influenza (HPAI) outbreaks, particularly those caused by H5N1 and its variants, have surged since 1959. The HPAI H5N1 clade 2.3.4.4b viruses have notably expanded their geographical reach, affecting numerous countries, diverse avian species, and now mammals. Using an ecological niche modelling approach, this study aims to elucidate the environmental factors associated with increased HPAI H5 cases since 2020, investigate potential shifts in ecological niches, and predict new areas suitable for viral circulation. We developed ecological niche models for HPAI cases in wild and domestic birds across two distinct periods: 2015–2020 and 2020–2022. Key environmental predictors include chicken and duck population density, human density, distance to water bodies, and land cover variables. Post-2020, we observe increased relative influence of predictors such as intensive chicken population density and cultivated vegetation. Risk maps reveal notable ecological suitability for HPAI H5 circulation in Europe, Asia, and the Americas, with significant expansions of at-risk areas post-2020. Wild bird H5 occurrences appear primarily correlated with urban areas and open water regions. Our analyses also highlight a potential shift in affected wild bird species diversity, with more avian species, particularly sea birds, impacted post-2020. Overall, these results further contribute to the understanding of HPAI epidemiology and identify regions where surveillance and control measures should be prioritised.

Timely vaccine strain selection and genomic surveillance improve evolutionary forecast accuracy of seasonal influenza A/H3N2

jhuddles@fredhutch.org (John Huddleston) — Thu, 04 Dec 2025 00:00:00 +0000

Evolutionary forecasting models inform seasonal influenza vaccine design by predicting which current genetic variants will dominate in the influenza season 12 months later. Forecasting models depend on hemagglutinin sequences from global public health networks to identify current genetic variants (clades) and estimate clade fitnesses. The lag between collection of a clinical sample and public availability of its sequence averages ∼3 months, complicating the 12-month forecasting problem by reducing our understanding of current clade frequencies. Despite continued methodological improvements to forecasting models, these constraints of a 12-month forecast horizon and 3-month submission lags impose an upper bound on any model’s accuracy. The SARS-CoV-2 pandemic revealed that modern vaccine technology reduces forecast horizons to 6 months and expanded sequencing support reduces submission lags to 1 month on average. We quantified the potential effects of these public health policy changes on forecast accuracy for A/H3N2 populations. Reducing forecast horizons to 6 months reduced average absolute forecasting errors to 25% of the 12-month average, while reducing submission lags decreased uncertainty in current clade frequencies by 50%. These results show the potential to improve the accuracy of existing forecasting models through realistic changes to public health policy.

Using step selection functions to analyse human mobility using telemetry data in infectious disease epidemiology: a case study of leptospirosis

p.ruizcuenca@lancaster.ac.uk (Ariane Goncalves da Silva) — Mon, 01 Dec 2025 00:00:00 +0000

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

karen.day@unimelb.edu.au (Abraham R Oduro) — Tue, 28 Oct 2025 00:00:00 +0000

Here, we introduce a new endpoint ‘census population size’ to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (MOI_var), based on the hyper-diversity of the var multigene family. We present a Bayesian approach to estimate MOI_var from sequencing and counting the number of unique DBLα tags (or DBLα types) of var genes, and derive from it census population size by summation of MOI_var in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high, seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by >90% and decreased parasite prevalence by ~40–50%, significant reductions in var diversity, MOI_var, and population size were observed in ~2000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short-lived and 32 months after IRS was discontinued and SMC was introduced, var diversity and population size rebounded in all age groups except for the younger children (1–5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the var population genetic characteristics of a high-transmission system (high var diversity; low var repertoire similarity), demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Forecasting the spatial spread of an Ebola epidemic in real time: Comparing predictions of mathematical models and experts

james.munday@swisstph.ch (Alicia Rosello) — Fri, 10 Oct 2025 00:00:00 +0000

Reassessing the link between adiposity and head and neck cancer: a Mendelian randomization study

dy20206@bristol.ac.uk (Caroline L Relton) — Thu, 09 Oct 2025 00:00:00 +0000

Understanding the global rise of artemisinin resistance: Insights from over 100,000 Plasmodium falciparum samples

cristina.ariani@gmail.com (Andrew J Balmer) — Thu, 02 Oct 2025 00:00:00 +0000

Artemisinin partial resistance (ART-R) in Plasmodium falciparum is a major challenge to malaria control globally. Over the last two decades, ART-R has spread widely across Southeast Asia, undermining public health strategies and hindering elimination. As of 2024, ART-R has now emerged in East Africa, with the potential to dramatically impact current efforts to control malaria in the region. Mitigating its spread requires detailed genomic surveillance of point mutations in the kelch13 gene, the primary known determinant of artemisinin resistance. Although extensive surveillance data on these markers is available, it is distributed across many literature studies and open databases. In this review, we aggregate spatiotemporal data for 112,933 P. falciparum samples collected between 1980 and 2023 into a single resource, providing the most comprehensive overview of kelch13 markers to date. We outline the history and current status of these mutations globally, with particular focus on their emergence in Southeast Asia and East/Northeast Africa. Concerningly, we find the recent increases in ART-R in Africa mirror patterns observed in Southeast Asia 10–15 years ago. We examine factors that may influence its spread, including fitness costs, treatment strategies, and local epidemiological dynamics, before discussing potential scenarios for how resistance may spread in Africa in coming years. This review provides a comprehensive account of how the situation of ART-R has unfolded globally so far, highlighting insights for researchers and public health bodies which aim to reduce its negative effects.

Improving SARS-CoV-2 variants monitoring in the absence of genomic surveillance capabilities: a serological study in Bolivian blood donors in October 2021 and June 2022

lucia-paola.inchauste-jordan@univ-amu.fr (Elif Nurtop) — Fri, 18 Jul 2025 00:00:00 +0000

A sex-specific Mendelian randomization-phenome-wide association study of body mass index

mary.schooling@sph.cuny.edu (C Mary Schooling) — Wed, 11 Jun 2025 00:00:00 +0000

Assessing healthy vaccinee effect in COVID-19 vaccine effectiveness studies: a national cohort study in Qatar

hsc2001@qatar-med.cornell.edu (Abdullatif Al-Khal) — Mon, 09 Jun 2025 00:00:00 +0000

Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort

claudia.barth@medisin.uio.no (Ann-Marie G de Lange) — Thu, 29 May 2025 00:00:00 +0000

Lifestyles and their relative contribution to biological aging across multiple-organ systems: Change analysis from the China Multi-Ethnic Cohort study

yinjianzhong2005@sina.com (Dan Tang) — Fri, 07 Mar 2025 00:00:00 +0000

Protection afforded by post-infection SARS-CoV-2 vaccine doses: A cohort study in Shanghai

yyao@fudan.edu.cn (Bo Zheng) — Mon, 17 Feb 2025 00:00:00 +0000

Persistent cross-species transmission systems dominate Shiga toxin-producing Escherichia coli O157:H7 epidemiology in a high incidence region: A genomic epidemiology study

gtarr@umn.edu (Chad R Laing) — Wed, 29 Jan 2025 00:00:00 +0000

Several areas of the world suffer a notably high incidence of Shiga toxin-producing Escherichia coli. To assess the impact of persistent cross-species transmission systems on the epidemiology of E. coli O157:H7 in Alberta, Canada, we sequenced and assembled E. coli O157:H7 isolates originating from collocated cattle and human populations, 2007–2015. We constructed a timed phylogeny using BEAST2 using a structured coalescent model. We then extended the tree with human isolates through 2019 to assess the long-term disease impact of locally persistent lineages. During 2007–2015, we estimated that 88.5% of human lineages arose from cattle lineages. We identified 11 persistent lineages local to Alberta, which were associated with 38.0% (95% CI 29.3%, 47.3%) of human isolates. During the later period, six locally persistent lineages continued to be associated with human illness, including 74.7% (95% CI 68.3%, 80.3%) of reported cases in 2018 and 2019. Our study identified multiple locally evolving lineages transmitted between cattle and humans persistently associated with E. coli O157:H7 illnesses for up to 13 y. Locally persistent lineages may be a principal cause of the high incidence of E. coli O157:H7 in locations such as Alberta and provide opportunities for focused control efforts.

Serum metabolome indicators of early childhood development in the Brazilian National Survey on Child Nutrition (ENANI-2019)

gilberto.kac@gmail.com (Dayana R Farias) — Wed, 15 Jan 2025 00:00:00 +0000

Leveraging mobility data to analyze persistent SARS-CoV-2 mutations and inform targeted genomic surveillance

riccardo.spott@gmail.com (Aurelia Kimmig) — Wed, 15 Jan 2025 00:00:00 +0000

Given the rapid cross-country spread of SARS-CoV-2 and the resulting difficulty in tracking lineage spread, we investigated the potential of combining mobile service data and fine-granular metadata (such as postal codes and genomic data) to advance integrated genomic surveillance of the pandemic in the federal state of Thuringia, Germany. We sequenced over 6500 SARS-CoV-2 Alpha genomes (B.1.1.7) across 7 months within Thuringia while collecting patients’ isolation dates and postal codes. Our dataset is complemented by over 66,000 publicly available German Alpha genomes and mobile service data for Thuringia. We identified the existence and spread of nine persistent mutation variants within the Alpha lineage, seven of which formed separate phylogenetic clusters with different spreading patterns in Thuringia. The remaining two are subclusters. Mobile service data can indicate these clusters’ spread and highlight a potential sampling bias, especially of low-prevalence variants. Thereby, mobile service data can be used either retrospectively to assess surveillance coverage and efficiency from already collected data or to actively guide part of a surveillance sampling process to districts where these variants are expected to emerge. The latter concept was successfully implemented as a proof-of-concept for a mobility-guided sampling strategy in response to the surveillance of Omicron sublineage BQ.1.1. The combination of mobile service data and SARS-CoV-2 surveillance by genome sequencing is a valuable tool for more targeted and responsive surveillance.

Livestock abortion surveillance in Tanzania reveals disease priorities and importance of timely collection of vaginal swab samples for attribution

felix.lankester@wsu.edu (Blandina T Mmbaga) — Mon, 16 Dec 2024 00:00:00 +0000

Lack of data on the aetiology of livestock diseases constrains effective interventions to improve livelihoods, food security and public health. Livestock abortion is an important disease syndrome affecting productivity and public health. Several pathogens are associated with livestock abortions but across Africa surveillance data rarely include information from abortions, little is known about aetiology and impacts, and data are not available to inform interventions. This paper describes outcomes from a surveillance platform established in Tanzania spanning pastoral, agropastoral and smallholder systems to investigate causes and impacts of livestock abortion. Abortion events were reported by farmers to livestock field officers (LFO) and on to investigation teams. Events were included if the research team or LFO could attend within 72 hr. If so, samples and questionnaire data were collected to investigate (a) determinants of attribution; (b) patterns of events, including species and breed, previous abortion history, and seasonality; (c) determinants of reporting, investigation and attribution; (d) cases involving zoonotic pathogens. Between 2017–2019, 215 events in cattle (n=71), sheep (n=44), and goats (n=100) were investigated. Attribution, achieved for 19.5% of cases, was significantly affected by delays in obtaining samples. Histopathology proved less useful than PCR due to rapid deterioration of samples. Vaginal swabs provided practical and sensitive material for pathogen detection. Livestock abortion surveillance, even at a small scale, can generate valuable information on causes of disease outbreaks, reproductive losses and can identify pathogens not easily captured through other forms of livestock disease surveillance. This study demonstrated the feasibility of establishing a surveillance system, achieved through engagement of community-based field officers, establishment of practical sample collection and application of molecular diagnostic platforms.