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Journal articleHicks J, Munsey A, Mousa A, et al., 2026,
Disentangling patterns of community malaria transmission and burden using malaria prevalence among pregnant women attending antenatal care: a modelling study
, The Lancet Microbe, ISSN: 2666-5247BackgroundMalaria prevalence measured among pregnant women at the first antenatal care (ANC1) visit provides longitudinal estimates of malaria burden in pregnancy and correlates well with cross-sectional community prevalence, but additional analysis is required to estimate community incidence. We aimed to test whether ANC1-based malaria prevalence can, via an open-source, mechanistic, model-based framework, recover seasonal patterns of clinical incidence suitable for subnational programmatic decision making.MethodsWe conducted a modelling study using monthly ANC1 malaria prevalence data from six previously published studies of malaria in pregnancy in six sub-Saharan African countries between May, 2010, and August, 2014. An extended, validated, age-structured malaria transmission model was fitted to monthly ANC1 malaria prevalence using particle Markov chain Monte Carlo (pMCMC) to infer monthly clinical incidence and seasonality metrics. Agreement between model-derived incidence and independently observed time series was assessed using the Markham Seasonality Index (MSI) and peak timing with concordance correlation coefficients (CCCs) and 95% CIs.FindingsAcross the six intermittent screening and treatment in pregnancy (ISTp) datasets, total ANC1 sample sizes and positivity were Ghana, 622 (47·9%) of 1298; Burkina Faso, 592 (41·9%) of 1413; Mali, 284 (21·7%) of 1308; The Gambia, 105 (8·8%) of 1194; Kenya, 323 (21·1%) of 1528; and Malawi, 291 (15·9%) of 1825. Strong agreement was observed between model-derived incidence and independent cohort data for MSI (CCC 0·82 [95% CI 0·31–0·97]) and for peak timing (CCC 0·98 [95% CI 0·87–1·00]).InterpretationA mechanistic pMCMC framework applied to routine ANC1 data can recover clinically relevant seasonality in incidence for the broader community, enabling subnational timing of seasonal interventions (such as seasonal malaria chemopre
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Journal articleNaidoo T, Morgenstern C, Doohan P, et al., 2026,
A systematic review of Nipah virus disease epidemiological parameters, outbreaks and mathematical models
, The Lancet Infectious Diseases, ISSN: 1473-3099We conducted a systematic review, following PRISMA guidelines (PROSPERO CRD42023393345), characterising the epidemiology, outbreaks and mathematical models of Nipah virus (NiV), an important public health threat in South and Southeast Asia. We searched PubMed and Web of Science from database inception through to 14 March 2025, and extracted 243 parameters, 89 risk factors, 39 models and 23 distinct outbreaks from 119 papers. IgG seroprevalence estimates in the general population ranged from 0% to 12.5%. NiV causes severe disease, with pooled case-fatality ratio estimates ranging widely from 9.1% (95%CI: 0.2%-41.3%) in Singapore to 81.9% (95%CI: 71.9%-88.9%) in Bangladesh. NiV's infection timeline and clinical course remain poorly characterised; we estimated a median incubation period of 8.77 days (n=165, 95%CI: 7.53-10.02) from 8 estimates in 7 articles with sufficient information. Transmission parameter estimates were scarce, and all but one of five central estimates of the basic reproduction number were below 1. NiV mathematical models (n=39) were rarely fitted to data (n=8). All extracted information is accessible via our R package, epireview.
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Journal articleDennis TPW, Sulieman JE, Nouredayem M, et al., 2026,
The origin, history, and resistance architecture of an invasive urban malaria mosquito in Africa.
, Science, Vol: 393The invasive urban malaria vector Anopheles stephensi threatens 126 million city dwellers in Africa. Controlling An. stephensi requires greater understanding of its origin, invasion dynamics, and insecticide resistance mechanisms. Analysis of 645 whole genomes sampled across Africa, the Middle East, and Asia supports an invasion scenario in which an initial South Asian introduction established a bridgehead population in Djibouti, which seeded distinct invasion fronts in Sudan, Ethiopia/Kenya, and Yemen. These incursions show contrasting rates and routes of spread shaped by landscape topology. Insecticide resistance is predominantly mediated by metabolic detoxification genes, with resistance haplotypes and copy-number amplifications introduced from South Asia. These findings, alongside a companion genomic resource, enable genomic surveillance of An. stephensi spread and resistance to aid control strategies.
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Journal articleSteyn N, Mills C, Shirvaikar V, et al., 2026,
A decision-theoretic framework for uncertainty quantification in epidemiological modelling.
, Am J EpidemiolEstimating, understanding, and communicating uncertainty is fundamental to statistical epidemiology, where model-based estimates regularly inform real-world decisions. However, sources of uncertainty are rarely formalised, and existing classifications are often inconsistent. This lack of structure hampers interpretation, model comparison, and targeted data collection. Connecting ideas from machine learning, information theory, experimental design, and health economics, we present a first-principles decision-theoretic framework that defines uncertainty as the expected loss incurred by making an estimate using incomplete information, arguing that this is a practically relevant definition for epidemiology. We show how reasoning about future data leads to a notion of expected uncertainty reduction, which induces formal definitions of reducible and irreducible uncertainty. We illustrate our approach with a simple worked example and a case study of SARS-CoV-2 wastewater surveillance in Aotearoa New Zealand, estimating the uncertainty reduction if wastewater surveillance were expanded to the full population. We then connect our framework to relevant literature from adjacent fields, showing how it unifies and extends many of these ideas. Our article serves as a gateway for applying a wide range of approaches to epidemiological models. Altogether, our framework provides a foundation for more reliable, consistent, and policy-relevant uncertainty quantification in infectious disease epidemiology.
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Journal articleYoung NW, Meier-Scherling CPG, Cuomo-Dannenburg G, et al., 2026,
Mapping the prevalence of molecular markers of Plasmodium falciparum artemisinin partial resistance in Africa: a systematic review and spatiotemporal modelling study.
, Lancet Infect DisBACKGROUND: Plasmodium falciparum kelch13(k13) mutations in Africa signal emerging artemisinin partial resistance (ART-R), endangering malaria control by undermining artemisinin-based combination therapies (ACTs). Sparse surveillance obscures whether rising k13 ART-R prevalence reflects local emergence or geographical expansion. We aimed to model and infer high-resolution spatiotemporal prevalence of k13 ART-R mutations, as well as mdr1 and crt mutations (markers of reduced susceptibility to ACT partner drugs), to inform public health policy. METHODS: For this systematic review and modelling analysis, we searched PubMed, Ovid MEDLINE, and Web of Science databases for English-language primary studies reporting malaria resistance, conducted in Africa, reporting pretreatment P falciparum samples with genotyping of k13 (all codons), mdr1 N86Y, or crt K76T, and that provided sufficient survey time and location metadata and complete, primary data, published between Sept 25, 2014, and July 9, 2025, with data extracted from full-text reports. Studies identified during the systematic review were added to 11 privately held datasets that met the same eligibility criteria but were unpublished at the time of review to give the augmented systematic review. Studies from the augmented systematic review were added to existing data from the Worldwide Antimalarial Resistance Network molecular surveyor (WWARN), MalariaGEN Pf8, and the WHO malaria threats map (WHO MTM), with any duplicates removed. The integrated dataset was harmonised by use of a standardised data schema. We estimated the continuous prevalence of each mutation using a spatiotemporal Gaussian process model and summarised with median and 95% credible intervals over posterior draws. The study was registered with PROSPERO (CRD42024593923). FINDINGS: We identified 1119 articles during the database search, with 120 studies included in the final analysis. These were augmented with 11 privately held datasets. In total, the aug
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Journal articleSheppard R, Charles GD, Ciavarella C, et al., 2026,
Integrating parallel Plasmodium falciparum and Plasmodium vivax malaria models in a unified framework to capture co-endemic prevalence patterns
, Communications Health, Vol: 1, ISSN: 3091-4841Background Plasmodium falciparum and Plasmodium vivax cause most malaria cases worldwide and are co-endemic in many countries, yet differ substantially in biology and in their responses to common interventions. As programmes drive down P. falciparum, P. vivax is a growing challenge for elimination, but most modelling tools assess the species separately, limiting coordinated policy. We aimed to build a unified malaria transmission modelling framework for co-endemic settings and assess how well it reflects global prevalence.Methods We integrated an established P. vivax model into a flexible P. falciparum modelling platform, enabling parallel simulation of both species within a shared biological, demographic, and intervention environment. Modelled equilibrium prevalences, matched by mosquito density, were compared with 19,225 yearly co-prevalence estimates from the Malaria Atlas Project (769 sub-national regions, 33 co-endemic countries, 2000–2024); uncertainty was represented by 95% quantile-based regions from 50 parameter draws. We assessed how this fit was modified by biological factors and simulated interventions.Results Here we show that the framework captures 51% of co-prevalence estimates within its uncertainty regions, rising to 65.5% when country-specific P. vivax relapse rates and human Duffy negativity are included. P. falciparum predominates where mosquito densities are high, whereas P. vivax is relatively more prevalent at lower densities. Simulated interventions produce larger relative reductions in P. falciparum prevalence, while P. vivax shows greater rebounds after intervention withdrawal, particularly at low mosquito densities.Conclusions This unified framework provides a quantitative tool to support coordinated, species-specific intervention strategies in co-endemic settings, a step toward sustainable malaria elimination.
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Journal articleSimmonds O, Maddren R, Collyer B, et al., 2026,
Predisposition to Ascaris lumbricoides reinfection in the Geshiyaro project in southern Ethiopia.
, Trans R Soc Trop Med HygOBJECTIVES: Predisposition to reinfection is characterized by certain individuals repeatedly acquiring infection at higher rates than others in the population despite treatment. As endemic regions approach low prevalence levels, such individuals will act as reservoirs of infection and contribute to sustaining transmission cycles in communities. This study investigated evidence for individual-level predisposition to Ascaris lumbricoides infections using longitudinal data from the Geshiyaro project in southern Ethiopia. METHODS: Longitudinal parasitological data collected over 7 years were analysed. Kendall's tau (τ) correlation coefficient was used to assess temporal persistence of infection between successive survey rounds, and Kendall's coefficient of concordance (W) was used to evaluate long-term stability in individuals' relative infection risk over many years of survey rounds. RESULTS: Positive correlations in infection status between survey rounds were observed (τ = 0.10-0.30, P < .001). Moderate concordance in infection ranking across the study period was also detected (W = 0.43, 95% CI: 0.42-0.45; P < .001), indicating persistent individual-level predisposition over many years of treatment and reinfection. CONCLUSION: These findings demonstrate sustained heterogeneity in infection risk within endemic communities. As transmission declines, identifying individuals predisposed to reinfection may help inform targeted or complementary 'test-and-treat' strategies to support interruption of A. lumbricoides transmission.
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Journal articleMcCabe R, Ebbarnezh L, Okware S, et al., 2026,
Estimation of the Ebola outbreak size in the Democratic Republic of the Congo
, The Lancet Infectious Diseases, Vol: 26, Pages: e279-e280, ISSN: 1473-3099 -
Journal articleLadhani SN, Trotter C, Borrow R, et al., 2026,
Meningococcal disease, meningococcal vaccines, and the recent meningococcal outbreak in Kent, UK.
, Lancet Infect Dis, Vol: 26, Pages: 653-655 -
Journal articleJamieson L, Johnson LF, Imai-Eaton JW, et al., 2026,
Optimising scale-up of injectable lenacapavir for HIV pre-exposure prophylaxis in South Africa: A modelling study and economic evaluation.
, PLoS Med, Vol: 23BACKGROUND: South Africa accounts for 20% of global HIV infections. Six-monthly injectable lenacapavir (LEN) for HIV pre-exposure prophylaxis (PrEP) has superior efficacy to oral tenofovir disoproxil fumarate/emtricitabine (TDF/FTC), and similar efficacy to 2-monthly injectable cabotegravir (CAB). With LEN's regulatory approval, South Africa faces critical implementation decisions amid constrained domestic resources and reduced international funding. We evaluated the epidemiological impact, cost-effectiveness, and optimal populations for LEN roll-out in South Africa. METHODS AND FINDINGS: Using Thembisa v4.8, a deterministic compartmental HIV transmission model, we simulated the impact of LEN scale-up, expanded oral TDF/FTC, and CAB scale-up, compared to a baseline of current TDF/FTC provision over 20 years (2026-2045) in South Africa. We modelled PrEP among women, including adolescent girls and young women (AGYW), female sex workers (FSW), pregnant and breastfeeding women (PBFW), men who have sex with men (MSM), and heterosexual men. For TDF/FTC scale-up, we doubled baseline initiation rates. For LEN and CAB, conservative and optimistic scenarios assumed initiation rates similar to or double those under TDF/FTC scale-up, respectively. Duration of use varied by subpopulation under TDF/FTC (3-6 months), conservative (LEN: 6-12 months, CAB: 4-8 months), and optimistic (LEN: 12-24 months, CAB: 8-16 months) scenarios. We modelled strategies to maximise impact of ~500,000 LEN doses allocated for 2026-2027, and national roll-out by subpopulations. We compared LEN cost-effectiveness to other HIV interventions, including antiretroviral treatment (ART). Costs are presented from the South African government's perspective in undiscounted 2025 United States Dollars (USD). Providing LEN to 1.7-2.9 million South Africans annually averted 19%-31% of infections and saved 3%-5% of life years lost to HIV, reaching incidence <0.1% in 2039-2043, 10-14 years earlier than baseline. TD
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