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Journal articleSilva L, Gogoi M, Lal Z, et al., 2026,
Antibiotic knowledge among ethnic minority groups in high-income countries: A mixed-methods systematic review.
, Public Health Pract (Oxf), Vol: 11OBJECTIVES: Antimicrobial resistance (AMR) is a major global public health concern. Although low-income countries are disproportionately affected by AMR, certain underserved groups in high-income countries (HICs), such as migrants and ethnic minorities, disproportionately bear the burden of AMR. This may be driven by socio-cultural factors including differences in health literacy. This review aimed to investigate the level of antibiotic knowledge amongst different ethnic minority groups in HICs. STUDY DESIGN: This was a mixed-methods systematic literature review. METHODS: We searched four databases (MEDLINE, EMBASE, the Cochrane library, CINAHL) to May 5, 2023, for primary studies on knowledge of antibiotics in different ethnic groups in HICs. We included studies in English using qualitative, quantitative and/or mixed-methods approaches and reporting on antibiotic knowledge by ethnicity. We used the convergent integrated approach for data synthesis and the Mixed-Methods Appraisal tool for quality assessment. RESULTS: 3935 articles were screened and 24 studies (17 quantitative, 5 qualitative, and 2 mixed-methods) were included, comprising 52778 participants from 8 countries (USA, UK, Australia, New Zealand, Netherlands, Greece, Sweden, Germany). Overall, participants from ethnic minority groups were able to identify common names of antibiotics and were aware of risks of antibiotics and side effects. However, participants thought antibiotics would treat viral-type illnesses. Ethnic minority groups generally had lower levels of knowledge compared to ethnic majority groups. CONCLUSIONS: Although ethnic minority communities possessed good levels of knowledge on certain aspects of antibiotics (e.g. being able to identify names of antibiotics), there were gaps in other areas (e.g. misperception that antibiotics are used for viral infections). The lower level of knowledge in ethnic minority groups compared to majority groups may be a contributing factor to health inequaliti
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Journal articleStevens O, Anderson RL, Sabin K, et al., 2026,
HIV prevalence in transgender women and cisgender men who have sex with men in sub-Saharan Africa.
, AIDS, Vol: 40, Pages: 510-516INTRODUCTION: The Global AIDS Strategy 2021-2026 calls for equitable access to HIV services for all populations. Transgender people have been marginalized and experience disproportionate risk of HIV infection in sub-Saharan Africa (SSA) and data to guide HIV programmes are severely limited. Surveillance data among cisgender men who have sex with men (cis-MSM) are comparatively abundant. We assessed whether HIV prevalence among cis-MSM was correlated with HIV prevalence among transgender women. METHODS: Data from key population surveys conducted in SSA between 2010 and 2022 were identified from existing databases and survey reports. Studies that collected HIV prevalence data among both transgender women and cis-MSM populations were analysed with random effect meta-analysis to estimate the ratio of HIV prevalence among cis-MSM:transgender women. RESULTS: Twenty-one studies were identified encompassing 8476 transgender women and 24 102 cis-MSM. Median HIV prevalence among transgender women was 23.5% [interquartile range (IQR) 11.5-39.8%] and 16.2% (IQR 8.1-26.8%) among cis-MSM. HIV prevalence among transgender women was 50% higher than in cis-MSM [prevalence ratio 1.48, 95% confidence interval (CI) 1.25-1.76]. HIV prevalence among transgender women was highly correlated with year/province-matched HIV prevalence among cis-MSM ( R2 = 0.60), but poorly correlated with year/province-matched total population HIV prevalence ( R2 = 0.01). CONCLUSION: Transgender women experience a significantly greater HIV burden than cis-MSM in SSA, underscoring the need for HIV services addressing the disproportionate vulnerability experienced by transgender women. Further bio-behavioural surveys focused on determinants of HIV infection, treatment uptake, and risk behaviours among transgender people, distinct from cis-MSM, will improve understanding of HIV risk and vulnerabilities.
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Journal articleKhurana MP, Brünnich Sloth MM, Scheidwasser N, et al., 2026,
SARS-CoV-2 reinfections and subsequent risk of hospital-diagnosed post-acute sequelae in Denmark (2020-2022): a nationwide cohort study.
, Lancet Reg Health Eur, Vol: 63BACKGROUND: Post-acute sequelae of COVID-19 (PASC), or long COVID, are a public health concern. While most recover from SARS-CoV-2 infections within weeks, some experience persistent symptoms. Here, we quantified the association between repeated SARS-CoV-2 infections and the risk of hospital-diagnosed PASC. METHODS: We conducted a nationwide register-based cohort study of all adults in Denmark (≥18 years) with at least one SARS-CoV-2 PCR or antigen test between April 1, 2020, and December 31, 2022. Participants were followed from first test until long COVID diagnosis (ICD-10: B948A), death, emigration, three SARS-CoV-2 infections, or end of study. Risk of long COVID diagnosis was estimated at three timepoints after study entry (180 days, 1 year, 2 years) and the outcomes were assessed during the 180 days after each timepoint. Cause-specific Cox models treated death as a competing risk, with number of infections and vaccination status as time-varying covariates. Absolute risks and differences were estimated using G-computation. Analyses were stratified by sex, income, and vaccination status. Secondary analyses assessed fatigue and headache (ICD-10), excluding individuals with prior diagnoses. FINDINGS: Of 4,418,544 individuals, 6942 (0.16%) were diagnosed with long COVID. The absolute risk of a diagnosis increased following reinfection (0.73% [95% CI 0.69-0.77] after one infection vs. 1.16% [1.05-1.30] after two infections at 180 days), but differences were small and decreased over time. Risks following reinfection were similar across sex and income strata. Absolute risk decreased with prior vaccinations. Secondary analyses showed no increased risk of fatigue or headache after primary infection. A small increase in fatigue risk was observed after reinfection at 1 year (RD 0.03% [0.01-0.05]), but not for headache. INTERPRETATION: Reinfection increases long COVID risk; however, the absolute increase after reinfection is smaller than that observed after a primary inf
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Journal articlePatel A, Jofre Bonet M, Hauck K, et al., 2026,
Corrigendum to 'Broadening the lens: a commentary on Sheard and Cauana-Finkel's account of women's progress in UK academic health economics' [Soc. Sci. Med. 382, October 2025, 118411].
, Soc Sci Med, Vol: 394 -
Journal articleWei Q, Zhang T, Schmit N, 2026,
Post-acute sequelae after Lassa fever: a systematic review and meta-analysis
, Journal of Infection, ISSN: 0163-4453 -
Journal articleZhang T, Wei Q, Schmit N, 2026,
Post-acute sequelae after Nipah virus infection: a systematic review and meta-analysis
, EClinicalMedicine, ISSN: 2589-5370Background Nipah virus was first detected in the 1998-1999 Malaysia outbreak and remains a significant public health concern due to its high epidemic potential and recurrent outbreaks in South Asia. Incidence patterns of post-acute sequelae, characterised by persistence or delayed onset after the acute phase of an infection, are not well documented after infectious disease outbreaks. We aimed to address this knowledge gap. Methods We conducted a systematic review and meta-analysis on the prevalence, incidence, duration, and characteristics of post-acute sequelae in survivors of Nipah virus infection. We searched PubMed and Web of Science for studies published in English between database inception and Nov 17, 2025. Articles were eligible for inclusion if they were peer-reviewed and reported primary data on post-acute sequelae in survivors of Nipah virus infection. Risk of bias was assessed using Joanna Briggs Institute critical appraisal tools. We conducted random-effects meta-analysis for all outcomes reported in at least two studies, and assessed heterogeneity qualitatively and using the I2 statistic. This review was registered with PROSPERO CRD42024616198. Findings Our search identified 1,091 articles after deduplication, of which eight were eligible for inclusion in the systematic review and six in the meta-analysis. Study populations included hospitalised Nipah encephalitis survivors and total survivors of Nipah virus infection in three and five articles, respectively. Only one study included a healthy control group. Three articles were of high, four of moderate and one of low quality. We extracted prevalence for potential neurological, psychiatric or non-specific post-acute sequelae. The pooled prevalence of total residual neurological deficits was 24% (95% CI 9-49; I2=0%) among total survivors of Nipah infection (3 studies; 80 participants), and 45% (95% CI 11-85; I2=64%) among the subset of survivors with acute Nipah encephalitis (3 studies; 87 participants).
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Journal articleGray E, Cooper L, Ramirez Gonzalez A, et al., 2026,
Estimating population immunity against serotype-two poliomyelitis from the inactivated polio vaccine in routine immunization across 112 countries: a modelling study
, PLoS Medicine, ISSN: 1549-1277Background: To mitigate the risk of outbreaks of serotype 2 poliomyelitis after withdrawal of this sero- type from oral poliovirus vaccine (OPV) in 2016, inactivated poliovirus vaccine (IPV) was introduced into the routine immunization (RI) programmes of all countries using OPV. Since 2022, WHO has recommended a 2-dose schedule, with a first dose at 14 weeks of age followed by a second dose at least 4 months later (e.g. 14-39 week schedule), although an earlier schedule may be adopted, despite lower immunogenicity, if vaccine coverage is low at older ages. Methods and Findings: We combined published data on type-2 IPV seroconversion with age, national RI coverage estimates, dose introduction dates, and country-specific schedules using a cohort model of population immunity to estimate IPV-induced immunity from 2024-2031 for 112 countries using either one or two doses of IPV. We projected immunity for current, 6-14, and 14-39 week schedules to find the optimal schedule and estimate the impact of interventions such as schedule changes and catch-ups. Under current schedules, estimated median serotype 2 population immunity in 2025 among children under five years of age is at 61% (IQR: 52%, 72%), rising to 71% (IQR: 57%, 80%) in 2031. The later 14-39 week schedule was optimal in all countries, with potential for the median immunity to rise to 78% (IQR: 66%, 85%) by 2031 if adopted by all countries in 2026. Eight countries would still have < 50% immunity, rising to 65%-72% if catch-up campaigns with 80% coverage were implemented in 2030. The work is limited by the fact that IPV provides only a partial picture of total immunity where there has been emergency type-two OPV use. Furthermore, national estimates may mask subnational coverage differences and pockets of extremely low immunity. Conclusions: Under these estimates, IPV schedules and coverage are suboptimal in many countries. Those with a single dose should introduce a second on the 14-39 week schedule; those on e
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Journal articleMichalow J, Cori A, Kimani J, et al., 2026,
Optimal deployment of gonorrhoea point-of-care tests: modelling the potential impact of diagnostic confirmation testing and screening strategies across five priority populations in Kenya.
, J Infect DisBACKGROUND: Gonorrhoea treatment in sub-Saharan Africa relies on syndromic management, which has poor diagnostic performance and misses asymptomatic infections. Point-of-care tests (POCTs) could address these limitations, but anticipated supply constraints necessitate strategic allocation to maximise impact. METHODS: We developed a deterministic compartmental model of gonorrhoea transmission in Kenya to evaluate allocating POCTs for diagnostic confirmation of symptomatic care attendees versus screening of routine healthcare service attendees across five priority populations: female sex workers (FSW), their male clients (CFSW), pregnant women, adolescent girls and young women, or total population men. We modelled constrained and unrestricted POCT availability during 2025-2030, and estimated infections averted relative to baseline syndromic management. Quality-adjusted life years (QALYs) gained were quantified using probability tree models. RESULTS: At baseline, incidence was highest among FSW (11.9 [UI:5.7-18.6] per 100 per year) and CFSW (13.1 [6.9-24.8]), while most QALY losses (80.6% [76.1-83.8%]) were among pregnant women and their infants. With constrained POCTs (sufficient to test 0.1% of adults annually), diagnostic confirmation averted the most transmission when among symptomatic FSW (2.1% [0.6-5.6%] of infections) or CFSW (2.2% [0.8-5.3%]), and the most morbidity when among symptomatic pregnant women (3.5% [1.8-7.2%] of QALY losses). Screening averted <1% of infections or QALY losses across populations. With unrestricted POCTs, screening had larger absolute impacts but lower per-test efficiency than diagnostic confirmation. CONCLUSIONS: Our modelling supports prioritising diagnostic confirmation over screening, consistent with WHO guidance to strengthen aetiologic diagnosis within syndromic care. Diagnostic testing among symptomatic pregnant women had the largest impact on mitigating gonorrhoea-related morbidity.
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OtherJahn S, Fraser K, Gaythorpe KAM, et al., 2026,
Developing and Applying a Unified Weather and Climate Database to Assess Climate Change Impacts on Tropical Infectious Disease Transmission and Burden
<jats:p>Research at the intersection of climate, weather, and health is rapidly expanding and inherently interdisciplinary, requiring integration of information across multiple disciplines. This includes comprehensive, accessible, reliable, and harmonized datasets that combine high-quality observational data with bias-corrected and downscaled climate projections from Global Climate Models (GCMs), such as from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). However, despite the availability of numerous gridded observational datasets and pre-processed projections, individual products vary in strengths, limitations, and representations of fine-scale spatiotemporal patterns, which can substantially affect downstream modelling and projection of current and future health outcomes. Moreover, the operational scale of epidemiological analysis is typically defined by administrative units, rather than by regular grids, and therefore often relies on the inclusion of area-level estimates that are additionally weighted by indicators such as human population. Hence, spatially resolved weather and climate data, typically provided in specialized formats (e.g., NetCDF), generally require substantial preprocessing before they can be used for respective analysis.To address these challenges, we developed a tailored, quasi-global weather and climate dataset designed to support high-resolution infectious disease transmission modelling in tropical settings. Our dataset comprises (1) high-resolution (0.1°) daily climate projections between 60°N and 60°S, and (2) corresponding spatially averaged (population-weighted) area-level estimates at administrative unit levels 0-2 for over 100 countries. We therefore selected and evaluated multiple global observational datasets, including model- and satellite-based products such as ERA5 and CHIRPS, across heterogeneous, disease-relevant tropical study domains. The observational datasets showing the highest perfo
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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: 2666-5247Background Malaria prevalence measured among pregnant women at first antenatal care (ANC1) 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 sub-regional programmatic decision-making. Methods We 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 Markham Seasonality Index (MSI) and peak timing with concordance correlation coefficients (CCC) and 95% confidence intervals (CI). Findings Across the six ISTp datasets, total ANC1 sample sizes and positivity were: Ghana 622/1298 (47.9%); Burkina Faso 592/1413 (41.9%); Mali, 284/1308 (21.7%); The Gambia 105/1194 (8.8%); Kenya 323/1528 (21.1%); and Malawi 291/1825 (15.9%). 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 0.87–0.997). Interpretation A mechanistic pMCMC framework applied to routine ANC1 data can recover clinically relevant seasonality in incidence for the broader community, enabling sub-regional timing of seasonal interventions (like seasonal malaria chemoprevention). These capabilities are especially valuable where high-quality case surveillance is limited, and household surveys are under-funded. Our
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