BMC Infectious Diseases

Background: Refractory and macrolide-resistant Mycoplasma pneumoniae pneumonia (MPP) has emerged as a major challenge in pediatric respiratory medicine, amplified by the post-2023 resurgence. However, a systematic overview of the research landscape specific to treatment-refractory and drugresistant disease in children remains lacking. Methods: Research articles and reviews on pediatric refractory or macrolide-resistant MPP published between 2000 and 2025 were retrieved from OpenAlex using Boolean searches. After screening, 2,286 records were quantitatively analyzed for annual output, contributing countries/institutions, thematic clusters, and citation-burst dynamics using Python. Results: Annual publications grew exponentially, with a pronounced surge after 2023 (n=378 in 2025). China produced the highest volume (45.1%) but recorded fewer citations per publication than the US, Japan, and Canada. The literature resolved into four clusters: macrolide resistance/molecular basis, epidemiology, etiology/co-infection, and refractory disease management. Burst analysis showed an evolution from earlier fronts like 23S rRNA mutations and azithromycin to recent emerging trends like pandemic-related co-circulation, genotype surveillance, and co-infection. Conclusions: Research on pediatric refractory and resistant MPP is expanding rapidly, shifting in emphasis from etiologic descriptions toward resistance mechanisms and clinical management. Standardizing the treatment of macrolide-unresponsive disease and post-pandemic epidemiological surveillance represent the principal directions for future work. Keywords: Mycoplasma pneumoniae; children; macrolide resistance; refractory pneumonia; bibliometric analysis; research trends

Abstract To identify countries with potential weaknesses in respiratory public health protection, we characterised shared hotspot patterns across three major respiratory infectious diseases and assessed whether the resulting shared hotspot scores were associated with worse COVID-19 outcomes. A Bayesian multivariate shared-component spatiotemporal model was fitted to data from 204 countries over 1990-2023 using Global Burden of Disease 2023 estimates to derive a shared hotspot score for each country. Generalized estimating equation negative binomial models were then used to examine associations between the shared hotspot score and COVID-19 incidence and mortality over 2020-2023. The shared hotspot score showed substantial cross-country heterogeneity, with the highest values concentrated in sub-Saharan Africa, South Asia, and Southeast Asia. Tuberculosis showed the strongest contribution to the shared spatial component (lambda = 1.657, 95% highest density interval: 0.883-2.506). Higher shared hotspot scores were significantly associated with both higher COVID-19 incidence (incidence rate ratio = 1.6783, 95% confidence interval: 1.4564-1.9340; p = 8.308 x 10^-13) and mortality (incidence rate ratio = 1.7436, 95% confidence interval: 1.5061-2.0186; p = 9.912 x 10^-14). Countries with persistently high co-occurrence of common respiratory infectious diseases also experienced worse COVID-19 outcomes, suggesting that the shared hotspot score may inform preparedness-oriented surveillance and resource allocation for future large-scale respiratory epidemics or pandemics.

Background Severe acute respiratory infections (SARI) strain healthcare systems. Sentinel surveillance remains central to SARI monitoring, but routinely collected hospital discharge data offer a scalable, population-wide complement. In Finland, national registers now enable register-based surveillance, yet SARI case definitions remain unevaluated. Aim To evaluate whether routinely collected electronic health records can support register-based SARI surveillance and establish a national case definition. Methods We conducted a retrospective register-based study linking inpatient discharge data from the Finnish Care Register for Health Care (Hilmo) and laboratory-confirmed pathogen notifications from the National Infectious Diseases Register (NIDR). Admissions were aggregated into hospitalisation episodes using generic and pathogen-specific respiratory ICD-10 codes and linked to laboratory-confirmed respiratory pathogens within an admission-centred window. We assessed the impact of diagnostic coding position, laboratory linkage windows and alternative case definitions on age distribution, seasonality and epidemic trend detection. Results We included 145,435 respiratory hospitalisation episodes. Laboratory confirmations clustered around admission, and a -7-to-+3-day window was selected; 51,498 (35.4%) had a linked laboratory confirmation. Specific primary-position diagnoses preserved clear seasonality and age distributions consistent with SARI epidemiology, whereas secondary-position diagnoses showed attenuated seasonality. A combined case definition incorporating specific primary diagnoses and laboratory-supported syndromic episodes produced stable epidemic curves while improving sensitivity over laboratory confirmation alone. Conclusion National discharge and laboratory registers can support robust SARI surveillance in Finland when case definitions are carefully designed. A combined register-based definition balances specificity, sensitivity and feasibility, complementing sentinel surveillance and integrated respiratory monitoring. Keywords Severe acute respiratory infection (SARI); surveillance; electronic health records; ICD-10; case definition; Finland

Background Human T-cell lymphotropic virus - 1 (HTLV-1) is the causative agent of Adult T-cell Leukaemia/Lymphoma (ATLL), a malignancy of CD4+ cells, and HTLV-1-associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP), a demyelinating disease. Globally, 10-20 million people are infected, though most remain asymptomatic and about 5% progress to severe disease. Transmission occurs mainly through breastfeeding, sexual contact, contaminated needles, and blood transfusion. In Ghana, evidence on the role of HTLV-1 in haematological malignancies remains scarce. Methods This was a cross-sectional study involving 200 patients with haematological malignancies (Acute Lymphoblastic Leukaemia - 4, Acute Myeloid Leukaemia - 6, Chronic Lymphocytic Leukaemia - 27, Chronic Myeloid Leukaemia - 63, Hodgkin Lymphoma - 21, Multiple Myeloma - 31, Myelodysplasia - 6, Myeloproliferative Neoplasm - 11) at the Haematology Day Care of the Korle-Bu Teaching Hospital. After informed consent was obtained, sera from study participants were tested for anti-HTLV-1 using MP Diagnostics GmbH ELISA immunoassay. Data were analysed using R software version 4.0.2 and SPSS version 31.0.0. Results The study population had a mean age of 49.1{+/-}17.7 years, with majority being females (n=109, 54.5%). Of the 200 samples, 16 (8.0%) were seropositive for HTLV-1, and these were detected in 4 males and 12 females. No statistically significant association was found between HTLV-1 infection and haematological malignancy (exact p = 0.061), sex (p=0.061), and history of blood transfusion (exact p= 1.000). Conclusion The findings show the seroprevalence of HTLV-1 of 8.0% among patients with haematological malignancies. Although there was no probable association between HTLV-1 and haematological malignancies, screening for HTLV-1 in patients with haematological malignancies may help to unravel the exact contribution in these conditions.

Background Malaria risk is influenced by climatic conditions, and children under five are particularly vulnerable due to their limited acquired immunity. We investigate the association between climatic factors and malaria risk in 350,000 children aged 5-59 months in sub-Saharan Africa over 18 years. Methods We included children aged 5-59 months with malaria tests from Demographic and Health Surveys (DHS) in 26 sub-Saharan African countries between 2006 and 2023. We linked these data to high-resolution climate exposures: temperature, precipitation, soil moisture, actual evapotranspiration and specific humidity. We fitted a mixed-effect logistic regression model incorporating Distributed Lag Non-linear Models (DLNM) over 1-6 month lag window for each exposure, controlling for seasonality and long-term trends. We examined effect modification by maternal education, household wealth, residential type, water source, sanitation facility, child age and sex, use of insecticide-treated bed nets (ITNs), and the age of the household head. Results Malaria prevalence was 19.5%. Malaria risk was highest at 24 degrees (OR: 1.45, 95% CI: [1.36, 1.54]), followed by a decline at higher temperatures. This elevated risk was mainly driven by short-term exposures (1-2 months). Precipitation increased risk up to 59 ~ 120 mm (1.10, [1.07, 1.12]), after which heavier rainfall reduced risk, particularly at short- to medium-term lags (1-4 months). Soil moisture was associated with increasing risk up to ~80 mm (1.11, [1.08, 1.14]), with a plateau at higher levels. Evapotranspiration showed a strong, near-linear positive association with malaria risk. Higher specific humidity levels (>14 g/kg) presented a lower risk, reaching a 45% reduction at 17 g/kg (0.55, [0.49, 0.61]), with the strongest protective effects at short-term lags (1-2 months). Elevated malaria risk at low and moderate average temperatures was particularly evident among children who did not sleep under an ITN net. Conclusion Malaria risk in children under five is strongly shaped by climatic factors, with complex and delayed associations. The findings provide evidence to guide targeted interventions and early-warning strategies for vulnerable populations.

Background: Seasonal influenza, commonly known as flu, is an acute respiratory, highly contagious illness caused by influenza viruses. A clear understanding of influenza seasonality is crucial for guiding prevention and treatment strategies, including decisions on vaccination timing to prevent outbreaks. While well documented in temperate regions, data on influenza epidemiology in tropical areas, particularly sub-Saharan Africa, remain limited. We described the types, subtypes and positivity rate of seasonal influenza in Uganda during 2019-2023. Methods: We abstracted data from the National Influenza database on positive seasonal influenza cases confirmed by Polymerase Chain Reaction. The cases were disaggregated by age group, sex, region, month and year of reporting. Using Microsoft excel, we calculated the influenza positivity rate and disaggregated it by strain, sex, age, region and time. Test positivity rate was computed as the number of positive cases as a percentage of the total samples tested. Results: Among 17,957 individuals tested, the overall positivity rate for seasonal influenza was 5% (936 cases). Positivity was higher among males compared to females (7% vs. 4%), with children aged 5-9 years having the highest positivity rate (16%), while individuals aged 50-54 years had the lowest (1%). The median positivity rate was 4%, with a range of 1-16%. Regionally, the central region reported a positivity rate of 5%, with rates across all regions ranging from 5% to 8%. Over time, there was a gradual decline in positivity rates, decreasing from 16.5% in 2019 to 5.3% in 2023. Seasonal influenza exhibited bimodal peaks, with the primary peak occurring between March and May and a secondary peak from October to December. Influenza A was the predominant strain, accounting for 70% of seasonal influenza cases (669/936). Among the Influenza A subtypes, H3N2 was most common, representing 63% of cases (425/669). Conclusions: The declining seasonal influenza positivity rates from 2019 to 2023 and the predominance of Influenza A and H3N2 highlight the need for sustained surveillance in Uganda. Given Influenza A's high genetic variability and potential for novel strain emergence, monitoring circulating strains, informing vaccine development, and implementing targeted interventions for high-risk groups and regions are critical to controlling and preventing outbreaks.

Seasonal influenza remains a major cause of morbidity and mortality worldwide. Although neuraminidase inhibitors improve outcomes, influenza-related deaths persist. We evaluated the impact of early aspirin (ASA) and non-aspirin nonsteroidal anti-inflammatory drug (NSAID) use on outcomes in adults hospitalized with influenza. This retrospective study included adults admitted to the University of Minnesota Medical Center from 2016 to 2018. Continuous variables were summarized as medians with interquartile ranges (IQRs) and categorical variables as counts and percentages. Group comparisons used Wilcoxon rank-sum, Chi-square, or Fishers exact tests. Analyses included case-control comparisons, assessments by vaccination status, and subgroup analyses by early ASA or NSAID use. Among 2,816 patients, 320 had laboratory-confirmed influenza, with vaccination less common among cases. Unvaccinated patients had higher rates of intensive care unit (ICU) admission (23.6% vs. 11.1%; P = 0.003) and ventilatory support (15.0% vs. 6.1%; P = 0.009). In vaccinated patients, early ASA use was associated with older age and higher in-hospital mortality, whereas early NSAID use was associated with no in-hospital deaths, better one- and three-year survival (P < 0.001), and fewer, though not statistically significant, cardiovascular complications. In unvaccinated patients, ASA use was associated with lower three-year survival (59.1% vs. 79.2%; P = 0.013), while NSAID use was associated with fewer ICU admissions and no cardiovascular or renal complications. In both vaccinated and unvaccinated adults hospitalized with influenza, early NSAID use was associated with improved survival and fewer complications, whereas ASA use was associated with worse outcomes.

Background Rising antimicrobial resistance (AMR) in the African region contributes to high morbidity and mortality. Continuous national AMR surveillance is critical in understanding the spread of AMR and informing policies on containment. We present results of national AMR surveillance in Kenya Methods Passive surveillance was prospectively conducted in 20 sites in Kenya between 2021 and 2025. Sites included national and sub-national level tertiary public and private hospital laboratories. Non-duplicate isolates of WHO priority Gram-negative and Gram-positive pathogens were included in this analysis. Bacterial isolates were identified using either conventional identification methods, Analytical Profile Index or automated systems while antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method or automated systems and interpreted using the Clinical and Laboratory Standards Institute guidelines. The primary outcomes were the proportions of various priority bacteria isolated and the proportions resistant to commonly used antibiotics. Results Between 2021 and 2025, there were 15,124 priority pathogens isolated with 7,592 (50.2%) from urine, 5,430 (35.9%) from blood (35.9%), and 1,784 (11.8%) from respiratory specimens. Escherichia coli and Klebsiella pneumoniae accounted for 76.3% of the priority pathogens. Resistance to 3rd generation cephalosporins was 63.2% for Escherichia coli and 79.1% for Klebsiella pneumoniae for the period 2021 to 2025 while carbapenem-resistance was 30.4% for Klebsiella pneumoniae and 7.2% for Escherichia coli. Resistance to carbapenems by Klebsiella pneumoniae increased from 17.9% in 2021 to 35.9% in 2025 while Methicillin resistance in Staphylococcus aureus increased from 36.5% in 2021 to 56.4% in 2025. Conclusion Resistance to critical antibiotics is a significant problem in Kenya, with alarming rates of Methicillin Resistant Staphylococcus aureus and carbapenem resistant Klebsiella pneumoniae. Ugent and sustained infection prevention and control measures and appropriate antimicrobial stewardship activities should be instituted across all health facilities in the country. There is need for improved access to antibiotics with activity against these resistant pathogens.

Background: Drug-resistant tuberculosis (DR-TB) remains a major challenge to tuberculosis control in sub-Saharan Africa. Cameroon faces substantial challenges in managing DR-TB; however, national evidence on treatment outcomes remains unsynthesized. This systematic review and meta-analysis aimed to estimate pooled treatment outcomes, adverse drug events (ADEs), and predictors of unfavorable outcomes among patients with DR-TB in Cameroon. Methods: This systematic review and meta-analysis followed the PRISMA 2020 guidelines. PubMed, Scopus, Embase, Web of Science, the Cochrane Library, African Journals Online. Google Scholar and reference lists were also searched. Studies reporting World Health Organization-defined treatment outcomes among patients with DR-TB were included. Random-effects meta-analyses using generalized linear mixed models with logit transformation were performed. Heterogeneity was assessed using the I2 statistic, and publication bias and sensitivity analyses were conducted. Results: Fifteen studies conducted between 1998 and 2022 were included. The pooled mortality rate was 6.8% (95% CI: 4.7-9.7; 14 reports; n = 2,351 participants), loss to follow-up was 4.1% (95% CI: 2.8-6.1; 12 studies; n = 2,244 participants), and treatment failure was 5.0% (95% CI: 1.1-19.8; 12 studies; n = 2,050 participants). The pooled treatment success rate was 74.2% (95% CI: 60.4-84.4; 13 reports; n = 2,146 participants). Treatment success improved over time and was higher with modified regimens (87.2%; 95% CI: 83.8-89.9; 3 studies; n = 460 participants) than with standard regimens (68.8%; 95% CI: 52.2-81.6; 10 studies; n = 1,686 participants). Among patients with multidrug-resistant-TB, the pooled prevalence of adverse drug events was 70.8% (95% CI: 40.2-89.7; 3 studies; n = 251 participants), with ototoxicity (41.9%; 95% CI: 23.7-62.6; 3 studies; n = 251 participants) and gastrointestinal disorders (40.9%; 95% CI: 25.5-58.2; 2 studies; n = 172 participants) being the most common events. HIV co-infection was significantly associated with unfavorable treatment outcomes (pooled OR = 2.76; 95% CI: 1.95-3.93; 6 studies), and male gender was also associated with increased odds of unfavorable outcomes (OR = 1.73; 95% CI: 1.25-2.40; 5 studies). Conclusions: Approximately three-quarters of patients with DR-TB in Cameroon achieved successful treatment, although mortality, treatment failure, and adverse drug events remain important concerns. Strengthening pharmacovigilance, integrated TB/HIV care, and the implementation of effective all-oral regimens are essential to improve treatment outcomes. Systematic review registration number: CRD420261404490.

Legionnaires disease is a severe respiratory illness caused by Legionella bacteria, with most cases occurring sporadically and environmental sources often unidentified. Effective outbreak detection requires understanding the spatiotemporal dynamics of sporadic cases and their environmental drivers. We developed a mechanistically informed spatiotemporal model integrating fine-scale spatial heterogeneity, multi-week meteorological influences, and extended temporal lags. The framework combines a negative binomial generalised additive model (GAM), a Besag-York-Mollie (BYM2) spatial component, and distributed lag nonlinear models (DLNMs) to capture nonlinear, delayed effects of temperature, dewpoint depression, precipitation, and cloud cover. These outputs generate a national daily index of weather-driven vulnerability, which is combined with hierarchical clustering to identify potential outbreaks. Across 2000-2019, our model improved outbreak detection in 15 of 20 years compared with the baseline UKHSA approach; in the remaining years performance was either equivalent (two years) or only slightly worse (three years, 0.98% reduction). Mean relative improvements were 6.0%, with a maximum of 14.4% in 2013. Improvements were consistent across months, and coarser 0.25-degree grid evaluations likely underestimate the models advantage at finer spatial scales. The analysis also clarified dual-stage Legionnaires disease dynamics, distinguishing environmental bacterial growth from the shorter infection window, and demonstrated the necessity of extended lags for accurate risk prediction. This framework provides a robust platform for targeted surveillance and predictive modelling, supporting evidence-based interventions and enhancing preparedness for sporadic Legionnaires disease under observed climatic conditions.

Introduction: Respiratory syncytial virus (RSV) causes significant disease in older and comorbid adults. Current UK vaccination recommendations restrict eligibility to adults [&ge;]75-years, 65-74-years with chronic respiratory disease or immunosuppression, and those in care homes, but evidence on clinical burden in adults <75-years with comorbidities is limited. This study assessed patient characteristics, healthcare resource utilisation (HCRU), and mortality in adults hospitalised with RSV in England. Methods: Population-based retrospective cohort study using linked Clinical Practice Research Datalink Aurum and Hospital Episode Statistics. Adults [&ge;]60-years hospitalised with RSV between October 2014-March 2019 were included. RSV episodes defined as 90-days post diagnosis. Case definitions were created using diagnosis codes related to confirmed RSV (RSV-specific) or acute lower respiratory tract infection where other causative pathogens were excluded (RSV-possible). All-cause HCRU (hospitalisations, critical care admissions, outpatient attendance, primary care consultations, and prescriptions) and case fatality rates were assessed. Results were stratified by age (60-74 and [&ge;]75-years), case definitions (RSV-specific, RSV-possible) and comorbidity profiles (chronic respiratory disease, immunocompromised, cardiovascular disease). Results: A total of 97,712 hospitalised episodes in those aged [&ge;]60-years were included in the analysis, where 785 (0.8%) were RSV-specific cases (n=338 aged 60-74-years, n=447 aged [&ge;]75-years). In RSV-specific cases, median (IQR) cumulative length of stay (LoS) for those [&ge;]75-years was 10.00 (6.00-22.00) days which was equivalent to or lower than each comorbidity sub-group in those aged 60-74-years, with longest LoS in those immunocompromised (11.50 [7.00-26.00] days). Critical care admissions were more often observed across comorbidity stratifications (13.85%-22.34%) compared to those [&ge;]75-years (5.03%). All-cause and RSV-related case fatality rates for RSV-specific cases were highest among those [&ge;]75-years (all-cause: 19.3%; RSV-related: 10.3%). Conclusion: HCRU within RSV episodes in those aged 60-74-years across comorbidity profiles was equal to or greater compared to those aged [&ge;]75-years. These findings highlight the need to prioritise consideration of comorbidity groups that could benefit from RSV vaccination. Key words: Respiratory syncytial virus; vaccine; chronic obstructive pulmonary disease; diabetes mellitus; immunocompromised; asthma; chronic kidney disease; cardiovascular disease; healthcare resource utilisation.

Background: Multidrug-resistant tuberculosis (MDR-TB) remains a significant public health threat in low- and middle-income countries, including Cameroon. This systematic review and meta-analysis aimed to determine the pooled prevalence of MDR-TB and other specific anti-tuberculosis drug resistance patterns, as well as to identify factors associated with drug-resistant tuberculosis in Cameroon. Methods: A comprehensive literature search was conducted in PubMed, Scopus, Web of Science, Embase, Cochrane Library, and African Journals Online. Additional studies were identified through Google Scholar and reference list screening. Observational studies (cross-sectional, cohort, and case-control) reporting drug resistance among bacteriologically confirmed tuberculosis patients in Cameroon were eligible. Joanna Briggs Institute critical appraisal tools were used to critically assessed the study quality. Pooled prevalence estimates were calculated using random-effects meta-analysis. Subgroup analyses and meta-regression explored sources of heterogeneity. A p-value 0.05 was considered statistically significant. Results: Twenty-eight studies conducted between 1995 and 2022 were included. The pooled prevalence of MDR-TB was 5.2% (95% CI: 2.7-9.6; 21 studies; n = 7,515), with significantly higher acquired resistance (11.6%; 95% CI: 6.3-20.3) than initial resistance (2.0%; 95% CI: 1.1-3.5). The highest pooled MDR-TB prevalence was observed in the most recent studies (38.8%; 95% CI: 33.7-44.2), and the lowest in 2015-2019 (2.7%; 95% CI: 0.4-15.2). Any resistance to anti-tuberculosis drugs was 16.0% (95% CI: 10.3-23.9; 28 studies; n = 9,931), and rifampicin resistance was 4.6% (95% CI: 2.4-8.6; 25 studies; n = 8,728). Monoresistance was highest for streptomycin (6.4%; 95% CI: 3.7-10.8) and isoniazid (4.7%; 95% CI: 3.0-7.4). Previous tuberculosis infection was the strongest predictor of drug resistance (OR = 3.9; 95% CI: 1.8-8.4), followed by alcohol consumption (OR = 1.8; 95% CI: 1.2-2.7) and history of incarceration (OR = 1.7; 95% CI: 1.1-2.6). High heterogeneity was observed across most of the pooled estimates. Conclusions: Drug-resistant tuberculosis, particularly MDR-TB, poses a substantial burden in Cameroon, with acquired resistance significantly exceeding initial resistance. Previous tuberculosis infection, alcohol use, and incarceration are key modifiable risk factors. These findings underscore the urgent need to strengthen routine drug susceptibility testing, scale up rapid molecular diagnostics, enhance treatment adherence strategies, and implement targeted interventions for high-risk populations.

The aim of this paper is to model homeless accommodation settings to investigate how vaccination mitigates the outbreaks, highlighting the importance of vaccination in vulnerable settings. We estimate the daily per capita contact rate with wider community, the internal transmission rate, and the achieved vaccine coverage. We present stochastic simulation of the final size of disease outbreaks given choices of internal and external transmission. We conclude that vaccine that has effect in reducing transmission will mitigate the outbreak in homeless hostels but it will have better results when the household population has large vaccination coverage, which may lead to more cost from the health economic perspective.

Introduction: Control of tuberculosis (TB) in children remains a major challenge globally. There is growing recognition that children with severe acute malnutrition (SAM) are a high-risk population for TB, but the global burden of TB in this group has never been comprehensively quantified. Methods: We conducted a systematic review and meta-analysis to estimate the prevalence of TB among children with SAM. Following PRISMA guidelines, we searched PubMed/MEDLINE, Embase, Scopus, Web of Science, Cochrane Library, and WHO Global Index Medicus from database inception to June 15, 2026. We included studies reporting TB among systematically sampled cohorts of children <15 years with SAM as defined by the World Health Organization. Methodological study quality was assessed with adapted versions of the Newcastle-Ottawa Scale or the Joanna Briggs Institute critical appraisal checklist. Pooled TB prevalence was calculated using a random-effects model with predefined stratification of studies by geographic region, national TB incidence, and study quality. We also conducted subgroup analyses by age, sex, HIV status, SAM type, and TB exposure. Results: We included 73 studies comprising 33,869 children with SAM across 15 countries, predominantly from sub-Saharan Africa and South Asia, and predominantly reporting on hospitalized children. The pooled TB prevalence was 13% (95% CI: 11-16%), but there was substantial heterogeneity (I2=98%). Studies conducted in Southern Africa had the highest pooled TB prevalence (36%, 95% CI: 19-56%) compared to other regions (p<0.01). Pooled TB prevalence was higher in those with history of TB household exposure compared to those without (74% vs. 17%, p=0.01). Conclusions: Approximately one in eight children hospitalized with SAM have TB, greatest among children with history of TB exposure and those in Southern Africa. These findings highlight opportunities for improved early TB diagnosis and routine, integrated TB screening within hospital-based SAM care pathways.

Background: Patients with chronic hepatitis B (CHB) may have an increased risk of severe COVID-19. Tenofovir has been hypothesized to confer protection against severe disease, but evidence is inconclusive. We evaluated the risk of severe COVID-19 among CHB patients treated with tenofovir compared with other nucleos(t)ide analogues (NAs). Methods and findings: In this nationwide, registry-based cohort study, we included all adults with CHB and laboratory-confirmed COVID-19 in Sweden between February 2020 and July 2022. Data from national health and socioeconomic registers were linked using unique personal identification numbers (PINs). Patients with HIV, hepatitis C, or hepatitis D coinfection were excluded. Exposure was defined as tenofovir versus other NA therapy. The primary outcome was severe COVID-19, defined as hospitalization >2 days or death within 30 days of diagnosis. Logistic regression was used to estimate adjusted odds ratios (aOR) with 95% confidence intervals (CI), controlling for age, sex, comorbidities, vaccination, socioeconomic status, and region of birth. Among 5,877 CHB patients with COVID-19, 672 were receiving NA therapy (437 tenofovir, 235 other NAs). Severe COVID-19 occurred in 8.0% of tenofovir-treated patients and 14.5% of those receiving other NAs (unadjusted OR 0.52; 95% CI, 0.31-0.85). After adjustment, the association was attenuated and no longer significant (aOR 0.72; 95% CI, 0.39-1.31). Older age, comorbidities, and unvaccinated status were strongly associated with severe disease. Conclusions: The apparent protective effect of tenofovir against severe COVID-19 in unadjusted analyses was largely explained by confounding factors. The risk of severe disease was primarily driven by age, comorbidities, and vaccination status. Prevention of severe COVID-19 in patients with CHB should instead focus on vaccination and management of comorbidities.

Background: Q fever, caused by Coxiella burnetii, is a zoonosis with significant public health implications. Spain has the highest number of cases in the European Union/European Economic Area, but the clinical and hospitalization burdens remain poorly characterized. This study described the epidemiology, demographic and clinical characteristics, and geographical distribution of hospitalized Q fever patients in Spain from 2016 to 2023. Methods: We conducted a nationwide, retrospective study using the Spanish Minimum Basic Data Set for Hospitalization (MBDS-H). All hospital admissions with an ICD-10-CM code for Q fever (A78) between 2016 and 2023 were included. We analyzed demographic data, comorbidities, complications, length of stay, intensive care unit (ICU) admission, and mortality. We calculated hospitalization rates per 100,000 population. Temporal trends were assessed using Poisson regression. Results: We identified 3,358 hospitalizations for Q fever, representing an overall hospitalization rate of 0.89 per 100,000 population. The median patient age was 56 years (interquartile range [IQR] 42-70), and the cohort was predominantly male (72%). The median hospital length of stay was 9 days (IQR 6-15), and 8.3% required ICU admission. The overall mortality rate was 2.4%. The most common complication was pneumonia (32%). Significant upward trends were observed over the study period for patient age, hypertension, and acute heart failure (p<0.05). Geographical analysis revealed the highest hospitalization rates in the Canary Islands (2.33), La Rioja (2.16), and the Balearic Islands (1.93). Conclusion: This study highlights the hospitalization burden due to Q fever in Spain. The risk of hospitalization increases with age and the presence of predisposing conditions. The marked regional heterogeneity and high frequency of complications such as pneumonia underscore the need for enhanced surveillance and a strengthened One Health approach to control this zoonosis.

Japanese encephalitis virus (JEV) transmission involves complex interactions among Culex mosquitoes, amplifying pig hosts, reservoir wading birds, humans, and environmental conditions, complicating quantitative assessment of transmission dynamics and intervention effectiveness. We developed a deterministic, fourteen-compartment One Health mathematical framework that integrates these interconnected host vector populations and their epidemiological states. The model incorporates temperature-dependent mosquito biting, seasonal transmission, human vaccination, pig biosecurity, environmental barriers, and mosquito-control interventions. Mathematical properties were established through analyses of non-negativity, boundedness, biologically feasible equilibria, local and global stability, and optimal control. District-specific simulations were conducted for Bellary, Udupi, Kolkata, and Purba Bardhaman during the August transmission period. Intervention scenarios were evaluated, and global sensitivity analysis was performed using 500 Latin hypercube samples with partial rank correlation coefficients. Model outputs were also compared with district-level surveillance observations. Vaccination-adjusted basic reproduction numbers were 0.905 in Bellary, 0.965 in Udupi, 1.817 in Kolkata, and 0.885 in Purba Bardhaman, with only Kolkata exceeding the epidemic threshold. Under maximum intervention, total infections decreased by 80.6%, 96.8%, 80.5%, and 72.2%, respectively, while infected mosquito populations declined to zero across all four settings. In Kolkata, vaccinating 3.6 million individuals with dose series II reduced the reproduction number from 1.817 to 0.9846, whereas population-wide dose series I vaccination alone was insufficient to reduce it below unity. Sensitivity analysis identified mosquito recruitment, temperature-dependent biting, carrying capacity, mosquito mortality, density-dependent regulation, and mosquito-to-human transmission as major determinants of peak human infection. Overall, the framework demonstrates heterogeneity in JEV transmission and intervention effectiveness and provides a mathematically grounded One Health approach for comparative evaluation of integrated control strategies.

Mosquito-borne diseases pose a growing public health challenge as climate change reshapes vector population dynamics. West Nile virus (WNV), transmitted between birds and Culex mosquitoes, disproportionately affects Maricopa County, Arizona, one of the nation's highest-burden counties, yet whether models that include weather and avian dynamics improve forecast accuracy remains unclear. Using a 15-year weekly time series of mosquito abundance, mosquito infection prevalence, and human cases, we developed four mechanistic model configurations of varying complexity, from mosquito-human dynamics alone to full models incorporating avian dynamics and weather forcing. We fitted each model to the weekly-observed data, generated probabilistic 1- and 2-week-ahead forecast horizons, and evaluated forecasts against a historical baseline. All configurations fit the data equally regardless of weather or avian dynamics. However, models incorporating both birds and weather created more accurate forecasts of mosquito abundance and mosquito infection prevalence, and all configurations outperformed the baseline for forecasting human cases. Forecast accuracy was highest in summer and fall, and ensemble aggregation sometimes outperformed every individual model, stabilizing predictions across the 15-year record. These findings indicate that avian and weather dynamics are most critical for predicting mosquito-specific data, positioning this framework as a scalable tool for public health planning for WNV surveillance under climate change.

Background. Direct livestock exposure is a risk factor for zoonotic influenza, including H5N1 highly pathogenic avian influenza (HPAI) A virus. But whether living in regions of high poultry and swine production intensity (PPI, SPI) increases risk of exposure to zoonotic influenza viruses independent of occupational livestock contact remains unclear. Objectives. To determine whether livestock workers and community members with no occupational livestock exposure in North Carolina, where poultry and swine production are increasingly co-located, are at higher risk of exposure to zoonotic influenza. Methods. Saliva samples from industrial livestock operation worker (ILO-W), ILO neighbor (ILO-N) and metropolitan area (Metro) households were analyzed for mucosal influenza A (H5N1, H1N1, and H3N2) hemagglutinin (HA) IgA and IgG antibodies to determine associations of PPI, SPI, exposure group, and detection of a swine-specific fecal contamination marker (Pig-2-Bac DNA) with influenza A antibody levels. Results. Residing in the highest PPI and SPI tertile was associated with significantly higher mucosal H5 and H1 HA IgA levels, including among residents without occupational livestock exposure. Households with occupational poultry or swine contact had significantly higher H5 IgA and IgG and H1 IgA levels compared to Metro households. In regression models accounting for clustering at the participant level, log10 anti-H5 HA mucosal IgA increased 0.16 (95% CI: 0.06, 0.27, p<0.005) and 0.10 (95% CI: 0.03, 0.17, p<0.005), per log10 increase in PPI and SPI, respectively, and 0.16 (95% CI: 0.03, 0.19, p<0.02) when Pig-2-Bac DNA was detected on household surfaces. Conclusions. Mucosal H5 HA IgA and IgG and H1 HA IgA were consistently elevated across different metrics of livestock exposure intensity, including residential exposure, occupational contact within a household, and a molecular marker of household swine fecal contamination in a state with intensive poultry and swine production.

Background: Mortality and hospital admissions due to Severe Acute Respiratory Infection (SARI) peaked between January and August 2025 in Brazil. Methods: The Brazilian Ministry of Health data on hospital admissions and deaths caused by SARI were compiled by age group (<5, 5-14, 15-49, 50-64, 65+ years) and quarter between January 2023 and June 2025. SARI causes were aggregated into SARS-Cov-2, Influenza, Respiratory Syncytial Virus (RSV), and other viruses (parainfluenza, adenovirus, rhinovirus, bocavirus, metapneumovirus). Multinomial regression was used to impute likely causes of death when these were not laboratory confirmed. Results: In the second quarter of 2025 (2025/2), RSV mortality rate among children <5 years reached 60 per 100,000, which is a 43% increase compared with 2024/2. Mortality rate for the joint impact of parainfluenza, adenovirus, rhinovirus, bocavirus, and metapneumovirus in the same age group doubled from 20 to 40 on the same scale in 2025/2 compared to 2024/2. Over the same period, influenza mortality tripled among the aged, whereas mortality due to other respiratory viruses increased less dramatically, except for SARS-CoV-2, which decreased among the aged from 150 to 25 per 100,000 between 2023/1 and 2025/2. Other age groups remained relatively stable over the period. The variation in hospital admissions largely followed that of mortality. Conclusions: While deaths and hospital admissions caused by SARS-CoV-2 declined rapidly since 2023, mortality rates of other respiratory viruses, mainly influenza and RSV, increased significantly among children <5 years and the aged in 2025/2. Public health policies that facilitate vaccine uptake against these infections should be given high priority.