International Journal of Infectious Diseases

Background Tuberculosis (TB) remains a critical public health challenge, with two-thirds of the global TB burden in ten Asian countries. Social vulnerabilities, comorbidities, health inequity, multi-dimensional poverty, malnutrition, and barriers to healthcare access continue to fuel TB epidemic. Inability to detect asymptomatic and sub-clinical TB, combined with passive approach in service delivery and overreliance on smear microscopy, leads to delayed diagnosis, a substantial burden of undetected cases, and continuing TB transmission in the communities. In such a context, the introduction and scale-up of active case-finding approaches - including community-based TB screening using highly sensitive screening tools and novel rapid diagnostics - becomes a strategic priority to interrupt transmission. The growing availability of multiple screening and diagnostic options makes evidence-based decision-making increasingly complex. Methods To estimate the potential epidemiological impact and cost implications of scaling up TB diagnostics and community-based screening in ten high-burden Asian countries, we constructed a mathematical model and evaluated multiple intervention scenarios. We then assessed and compared four service delivery models: 1) digital ultraportable chest x-ray (UPCXR) & Xpert/Truenat in community, 2) digital UPCXR in community and Xpert/Truenat at health facilities, 3) digital UPCXR in community and near point of care (nPOC) at health facilities, 4) nPOC in community & Xpert/Truenat at health facilities - for total investment required and projected health benefits for their cost-effectiveness. Results and conclusions The modelling study indicated that strengthening health facility capacity (with enhanced TB screening, expanded molecular diagnostics, reduced loss to follow-up, private sector standard of care, leading to increased treatment coverage & quality of active disease treatment and reduced post-treatment relapse, scale-up of TB preventive treatment (TPT), and provision of nutritional support to 80% of TB patients and their household contacts) can significantly reduce TB incidence and mortality; however, community-wide mass screening remains essential to achieving TB elimination targets . Targeted screening of vulnerable populations demonstrated greater cost-effectiveness than untargeted screening approaches. Achieving the End TB goals will ultimately require an effective TB vaccine with high population-level coverage. AI-enabled digital UPCXR-based screening combined with Xpert/Truenat testing at the community level demonstrated maximum epidemiological impact potential, while the most cost-efficient model is Digital UPCXR in the community combined with nPOC testing at health facilities. An investment of USD 12.7 billion over the next five years in community-level implementation of digital UPCXR and molecular diagnostics could avert an additional 9.8 million TB cases and 1.9 million deaths across ten Asian countries over a ten-year horizon.

BackgroundTuberculosis (TB) and human immunodeficiency virus (HIV) are leading causes of infectious disease deaths, with disproportionate impact in low- and middle-income countries (LMICs). Despite well-established biological relationships between these diseases, there is limited information on how TB prevalence differs between people living with and without HIV. MethodsWe conducted a systematic review and meta-analysis of TB prevalence surveys conducted in LMICs and published during January 1st 1993-October 13th 2025 (PROSPERO CRD42024503853). We extracted bacteriologically-confirmed TB prevalence estimates stratified by participant HIV status. Surveys that offered HIV testing to all, sputum-collection-eligible, or TB-positive participants were included in the primary analysis. We applied Bayesian meta-regression to estimate pooled risk ratios (RR) of bacteriologically-confirmed TB prevalence among participants living with versus without HIV. Additionally, we estimated country-level and overall TB notification-to-prevalence (N:P) ratios by HIV status. FindingsOf 10,211 potentially relevant publications, 12 TB prevalence surveys--representing 264,530 participants within nine countries in Southern and Eastern Africa--were used in the primary analysis. Reported TB prevalence was higher among participants living with versus without HIV in 11/12 surveys, with an overall pooled RR of 3{middle dot}86 (95% credible interval: 2{middle dot}41-5{middle dot}53). N:P ratios were higher among participants living with HIV in all examined countries. The overall pooled N:P ratios were 1{middle dot}74 (0{middle dot}59-4{middle dot}56) and 0{middle dot}48 (0{middle dot}17-1{middle dot}20) among participants living with versus without HIV, respectively. InterpretationIn Southern and Eastern Africa, bacteriologically-confirmed TB prevalence is three- to six-times higher among people living with HIV. Comparison of prevalence and notification data suggest higher rates of TB diagnosis for people living with versus without HIV, but also indicates substantial delays in the detection of untreated TB cases for both populations. FundingWellcome Trust, UK National Institute for Health and Care Research, UK Foreign, Commonwealth and Development Office, NIH. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThere is limited systematic evidence on how the prevalence of TB disease differs between people living with HIV and without HIV. Multiple observational cohorts have described substantially elevated TB incidence among populations with HIV, but disease prevalence will also be affected by differences in mortality and treatment uptake rates. We searched PubMed from inception through January 21, 2026 using the search string ((HIV AND TB) OR HIV/TB) AND (prevalence AND (systematic review OR meta-analysis)) without any restrictions on language. We also reviewed investigators personal libraries. This search yielded 506 publications; however few of these included prevalence data. An analysis conducted in 2020 synthesized HIV status-stratified data from seven national TB prevalence surveys in Africa and found that HIV prevalence was lower among prevalent TB cases than among notified cases. This study did not include subnational surveys and did not distinguish between survey participants with self-reported or test-confirmed HIV status. Added value of this studyThis study synthesized TB prevalence data, stratified by participant HIV status, from national and subnational surveys conducted in LMICs and published between January 1st 1993 and October 13th, 2025. Collated data represented 681,402 survey participants across ten countries. All but one study were conducted in Southern and Eastern Africa. We limited our primary analysis to surveys that systematically tested participants for HIV and bacteriologically-confirmed TB. The prevalence of bacteriologically-confirmed TB was estimated to be three to six times higher than among people living with versus without HIV. Ratios of TB notifications to TB prevalence were higher for people living with HIV compared to people without HIV, suggesting higher rates of TB case detection (and likely shorter duration of disease) for people living with HIV and untreated TB than those without HIV. Implications of all available evidenceFew estimates of community-representative TB prevalence stratified by participant HIV status exist. These surveys have been concentrated in Southern and Eastern Africa, despite TB-HIV burden being distributed globally. Our findings highlight the elevated burden of TB among people living with HIV in these settings, as well as the limited data on the intersection of TB and HIV epidemiology in other world regions. Furthermore, our comparison of notification and prevalence data demonstrate substantial shortfalls in TB case detection, regardless of an individuals HIV status.

The A(H1N1)pdm09 virus remains a major global health threat. This study examined the burden of ICU admission, mortality, and associated predictors among patients with A(H1N1)pdm09 pneumonia in a leading center for infectious diseases in Vietnam. Information on demographic, clinical, and laboratory characteristics, and outcomes was retrieved from medical records of adults admitted with influenza A(H1N1)pdm09 during 2009-2019. Among 729 cases, 21.7% (158/729) developed pneumonia. Among 158 pneumonia cases, 36.7% (58/158) developed moderate-to-severe acute respiratory distress syndrome (ARDS), and 15.2% (24/158) received invasive ventilation. ICU admission and mortality rates were 48.7% (77/158, 95%CI 41.1-56.5%) and 8.2% (13/158, 95%CI 4.9-13.6%), respectively. Predictors of ICU admission included being >60 years old (adjusted OR [AOR] 13.864, 95%CI 2.185-87.956, P=0.005), comorbidities (AOR 6.527, 95%CI 1.710-24.915, P=0.006), AST (AOR 1.013, 95%CI 1.001-1.025, P=0.029), and moderate-to-severe ARDS (AOR 14.027, 95%CI 4.220-46.627, P<0.001). Predictors of mortality were invasive ventilation (AOR 55.355, 95%CI 1.486-2062.375, P=0.030) and double-dose oseltamivir or combination therapy (AOR 32.625, 95%CI 1.594-667.661, P=0.024). In conclusion, mortality is not rare in A(H1N1)pdm09 infection. Monitoring of older patients and those with comorbidities, liver enzyme elevation, or moderate-to-severe ARDS is essential for the timely detection of complications requiring intensive care.

Globally, respiratory tract infections (RTI) are the main cause of morbidity, and in Low-middle-income countries (LMICs) RTI including pneumonia are a leading cause of morbidity and mortality in children <5 years. Diarrheal illness increases RTI risk in young children through micronutrient depletion, and immune stress, yet data on post-diarrhea RTI burden in LMICs are limited. We determined the prevalence and risk factors of RTI within three months following medically-attended diarrhea (MAD) in children aged 6-35 months enrolled in seven EFGH country sites in Asia, Africa and South America. The EFGH study prospectively enrolled children aged 6-35 months with MAD in selected health facilities during a 24-month period from 2022 to 2024 and followed them for three months. RTI was defined as cough or difficulty breathing and the presence of one of the following symptoms at any scheduled or unscheduled visit during follow-up: stridor; fast-breathing; oxygen saturation <90%; or chest indrawing. The period prevalence and 95% confidence intervals of RTI were calculated, and correlates of RTI were assessed using modified-Poisson regression. From June 2022 to August 2024, 9,476 children aged 6-35 months presenting with MAD in the EFGH study sites were screened: 9,116 (96.2%) included in the current study. Nearly half were female (46.7%), and median age was 15 months. Overall, 48.5% received all age-appropriate vaccines, and 87.6% received the pneumococcal vaccine, with significant variation across countries. Nearly one-quarter of children were stunted, 17.2% wasted, and 21.9% underweight. RTI occurred in 3.8% of children during the three-month follow-up, mostly within the first month. Higher prevalence of RTI occurred among children aged 12-23 months (8.7%), those undernourished (16.1%), unvaccinated (4.0%) or living in poor sanitation settings (4.1%). While children who received all age-appropriate or pneumococcal vaccinations had a lower crude prevalence of RTI, these associations were not statistically significant after adjusting for age, sex and study site. RTI was infrequently observed in the three months following MAD presentation, with significant variability by site and with the highest prevalence in Malawi. RTI risk was highest in 12-23-month-olds and among children with undernutrition, and those living in poor sanitation conditions.

Introduction Improved diagnostics are needed for people at risk of tuberculosis, especially adolescents. Tongue swab (TS) molecular testing has emerged as a promising strategy for tuberculosis diagnosis. We evaluated diagnostic accuracy and acceptability of Xpert MTB/RIF Ultra (Xpert) using TS samples for tuberculosis detection among adolescents. Methods We conducted a cross-sectional diagnostic accuracy study with consecutive recruitment in Vietnam. Adolescents aged 10-19 who were recommended to undergo investigation for tuberculosis and had not received tuberculosis treatment in the past years were eligible. Participants provided TS and sputum samples and completed a structured survey regarding sampling experiences. TS was tested on Xpert, with sputum tested on Xpert and liquid culture. We utilised a composite reference standard of a positive result on sputum Xpert or sputum culture to define disease status. Sensitivity, specificity, and diagnostic yield were calculated for TS Xpert. Results From July to December 2025, we enrolled 225 adolescents from Can Tho and An Giang provinces in southern Vietnam. Fewer than half (96/225, 43%) the participants exhibited a tuberculosis -like symptom, and the majority (157/225, 70%) were close contacts of a person recently diagnosed with tuberculosis. TS were collected from all adolescents, while 116 (52%) could provide mucopurulent sputum. Tuberculosis prevalence was relatively low (12/225, 5.3%). TS Xpert sensitivity (90% CI) and specificity (90% CI) were 58.3% (35.6, 78.0) and 99.5% (97.9, 99.9), respectively. Diagnostic yield among all diagnosed was 58.3% (7/12). TS sampling was highly acceptable to adolescents; the short time and simplicity of collecting TS were considered favourably. Conclusions The sensitivity and diagnostic yield of TS Xpert was relatively low among adolescents recommended for tuberculosis investigation, which includes asymptomatic individuals who may not provide high quality sputum. Specificity was excellent, and everyone could provide a TS. TS high acceptability indicates it remains a promising sample for diagnostic algorithms.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continuously evolved since its emergence in the human population in 2019. As of 1st August 2025, more than 1,700 Omicron subvariants have been designated by the Pango nomenclature system. The Pango nomenclature system designates a new lineage based on genetic and epidemiological information of SARS-CoV-2 strains. However, there is a possibility that strains that have similar genetic backgrounds and the same phenotype are given different Pango lineage names. In this paper, we propose a new algorithm, called FindPart-w, which can identify groups of viral lineages that share the same relative effective reproduction numbers. We introduced a new lineage replacement model, called the constrained RelRe model, which constrains groups of lineages to have the same relative effective reproduction numbers. The FindPart-w algorithm searches the equality constraints that minimise the Akaike Information Criterion of constrained RelRe models. Using hypothetical observation count data created by simulation, we found that the FindPart-w algorithm can identify groups of lineages having the same relative effective reproduction number in a practical computational time. Applying FindPart-w to actual real-world data of time-stamped lineage counts from the United States, we found that the Pango lineage nomenclature system may have given different lineage names to SARS-CoV-2 strains even if they have the same relative effective reproduction number and similar genetic backgrounds. In conclusion, this study showed that viruses that had the same relative effective reproduction number were identifiable from temporal count data of viral sequences. These findings will contribute to the future development of lineage designation systems that consider both genetic backgrounds and transmissibilities of lineages.

Background. Targeted Universal Tuberculosis Testing (TUTT) may increase tuberculosis (TB) case detection by including people who are not actively seeking TB care but are at high risk of the disease. Non-invasive tongue swab (TS) testing may facilitate TUTT. We evaluated two TS testing protocols in people with HIV (PWH) tested irrespective of TB symptoms. Methods. Study staff collected Copan FLOQSwab and Medline foam swab specimens, alongside urine and sputa, from PWH, most of whom were presenting for antiretroviral therapy initiation at primary healthcare clinics in KwaZulu-Natal, South Africa. FLOQSwabs were tested by sequence-specific magnetic capture (SSMaC) with qPCR (FLOQSwab-SSMaC). Foam swabs were tested by centrifuge-sedimentation and high-volume qPCR (foam-sedimentation). Urine lipoarabinomannan was detected using LF-LAM. The extended microbiological reference standard (eMRS) comprised any positive result on Xpert Ultra and/or liquid culture of sputum. Results. We enrolled 251 participants (median age 34 years, 56% female, 67% with self-reported TB symptoms). Participants had a median CD4 count of 347 cells/ul, and 16% (40/251) had prior TB. FLOQSwab-SSMaC was 43% sensitive (13/30) and 100% specific (131/131) relative to eMRS. Foam-sedimentation was 47% (9/29) sensitive and 100% (176/176) specific. Sensitivity increased to 52% (FLOQSwab-SSMaC) and 50% (foam-sedimentation) when sputum Xpert Ultra Trace positive results were excluded from eMRS. TS was more sensitive than urine LAM, and both sample types were more sensitive when CD4 counts were below 200. Discussion. TS testing detected about half of PWH with TB and outperformed urine LAM within this population, including among PWH with low CD4 counts.

Background: Sub-Saharan Africa (SSA) still experiences a high burden of micronutrient deficiencies. For monitoring of micronutrient status among young children in SSA, non-invasive alternatives to blood-based biomarkers are desirable. Handheld Raman spectrophotometry appears to offer this alternative to quantify intracellular stores of micronutrients. In rural Burkina Faso and Kenya, we validated the Cell-/SO-Check device (ZellCheck(R)) against conventional laboratory-based methods. Methods: For this validation study, we recruited children aged [&ge;]24 months attending routine clinics within the Health and Demographic Surveillance Systems (HDSS) in Siaya and Nouna. Anthropometric measurements and venous blood samples were taken. Plasma ferritin, soluble transferrin receptor (sTfR) and C-reactive protein (CRP) were measured by ELISA, and plasma zinc by atom absorption. The spectrometer was used to quantify zinc and iron. For continuous outcomes, we generated Bland Altman plots and calculated bias and limits of agreement (LoA). For binary outcomes, we produced Receiver Operator Characteristic (ROC) areas under the curve (AUC), and estimated sensitivity, specificity and predictive values. Results: We analysed data of 48 children from Burkina Faso and 54 children from Kenya (male: 53%; age range: 24-66 months). According to spectrophotometry, the proportions of iron deficiency and zinc deficiency were 16.7% and 25.5%, respectively. The median concentrations were for ferritin 24.0 {micro}g/L (range: 2.0-330.0), for sTfR 5.7 mg/L (2.8-51.0), and for zinc 9.9 {micro}mol/L (5.2-25.0). The corresponding bias for iron levels by spectrophotometry was 42.4 with LoA: -18.7, 103.6. The bias for zinc levels was 7.5 with LoA: -49.3, 64.2. For the classification of deficiency, the ROC-AUC, sensitivity, and specificity for spectrophotometry vs. biomarker-based diagnosis were for iron deficiency 0.62, 68% and 55%, respectively, and for zinc deficiency 0.55, 33% and 91%, respectively. Conclusions: The Cell-/SO-Check device may be used to rank children in population-based studies in SSA according to their zinc status, but not iron status. The method should not replace the standard laboratory measurements for clinical diagnoses of zinc and iron deficiencies.

Introduction: Modeling when influenza epidemics typically occur can help countries optimize surveillance, time clinical and public health interventions, and reduce the burden of influenza. Methods: We used influenza virus detections reported during 2011-2024 by 180 countries to the Global Influenza Surveillance and Response System, excluding COVID-19 pandemic impacted years (2020-2023). We analyzed data by calendar year (week 1-52) or shifted year (week 30-29) time windows, based on when most influenza detections occurred in each country. For countries with sufficient data, we computed generalized additive models (GAMs) of each country's weekly influenza-positive tests to smooth and impute time series distributions. From these GAMs, we calculated each country's normalized weekly influenza burden. Country-specific normalized time series were grouped using hierarchical k-means clustering reducing the Euclidean distance between time series within clusters. We calculated cluster-specific GAMs to estimate average seasonal timing. Countries without sufficient data were assigned to a cluster based on population-weighted latitudinal distance to a cluster's mean latitude. Results: We identified five clusters, or epidemic zones, from 111 countries with sufficient data. The influenza burden in epidemic zones A and B was consistent with a northern hemisphere pattern, with most influenza detections occurring during October-April (A) and September-March (B), while epidemic zones D and E were characterized by southern hemisphere-like seasonal timing, with most influenza burden occurring during May-November. Epidemic zone C had most influenza burden occurring during September-March; most countries assigned to this cluster were in the tropics. Conclusion: Epidemic zones may serve as a useful tool to strengthen and optimize influenza surveillance for global health decision-making (e.g., during vaccine strain composition discussions) and to guide country preparedness efforts for seasonal influenza epidemics, including the timing of enhanced surveillance, as well as the procurement and delivery of vaccines and antivirals.

Tuberculosis (TB) is prevalent in Uganda and overlaps with a high rate of HIV/TB coinfection. While nearly all hospital-based TB cases in Kampala, the capital of Uganda, show clear TB symptoms, 30% or more of undiagnosed TB cases found through active screening are asymptomatic. Additionally, the host risk factors for TB in Kampala cannot be distinguished from environmental risk factors. These TB-specific challenges are just part of the complexity, especially in areas with high HIV/AIDS burden. Data science techniques, especially Artificial Intelligence (AI) and Machine Learning (ML) algorithms, could help untangle this complexity by identifying factors related to the host, pathogen, and environment, which are difficult to explain or predict with traditional/conventional methods. In this project, we will use health data science approaches (AI/ML) to identify factors driving TB transmission within households and reasons for anti-TB treatment failure. We will utilize the computational resources at Makerere University and available demographic, clinical, and laboratory data from TB patients and their contacts to develop AI and ML algorithms. These will aim to: (1) identify patients at baseline (month 0) unlikely to convert their sputum or culture results by months 2 and 5, thus at risk of failing TB treatment; (2) identify household contacts of TB cases who are at risk of developing TB disease, as well as contacts who may resist TB infection despite repeated exposure to M. tuberculosis. Achieving these objectives will provide evidence that data science methods are effective for early detection of potential TB cases and high-risk patients, thereby helping to reduce TB transmission in the community. The study protocol received approval from the School of Biomedical Sciences IRB, protocol number SBS-2023-495.

BackgroundThere is a close correlation between neuroendocrine regulation and pulpitis progression. This study aims to identify key neuroendocrine regulation-related genes in pulpitis, providing insights for its treatment. MethodsGSE77459 and GSE92681 datasets were used to validate experimental findings. Key neuroendocrine regulation-related genes were identified via Cytoscape plugin cytoHubba and expression validation. Gene set enrichment analysis, RNA-binding protein regulatory networks, post-translational modifications, molecular regulatory networks, and drug prediction were performed. Key gene expression was experimentally verified in clinical samples. ResultsTop 10 genes were obtained via cytoHubba; 4 (IL6R, OSM, IL1RN, CCL4) with significant differences between pulpitis and control samples and consistent trends in both datasets were identified as key genes. Gene set enrichment analysis showed key genes participate in pathways like cytokine-cytokine receptor interaction. Related RNA-binding proteins were ELAVL1 and HNRNPA1, with phosphorylation as the main post-translational modification. Core regulatory microRNAs included miR-519, miR-765, miR-23, and regulatory factors included FOXC1, PRRX2. Targeted drugs (e.g., sarilumab, haloperidol decanoate, cyclosporine) were predicted, and clinical sample verification confirmed consistent expression trends. Conclusion4 key neuroendocrine regulation-related genes were identified, which may have clinical significance for the diagnosis and treatment of pulpitis.

ObjectiveThis study aimed to assess the effectiveness of SMS and voice message reminders in reducing the dropout rate in Lome-Togo, in 2026. MethodsWe conducted a cross-sectional study between October 2025 and March 2026 in the Grand Lome region. The intervention consisted of an integrated digital system used by health facilities to send automated SMS. Categorical variables were described in terms of frequency and proportion; Fishers exact test was used to compare proportions. Quantitative variables were described by their means accompanied by their standard deviation; the Wilcoxon rank-sum test was used to compare means. The significance level for statistical tests was set at 5%. ResultsA total of 30 health facilities were included. Seventy percent (70.0%) of the health facilities used messages associated with calls. Ninety percent (90.0%) of participants found the reminders useful, and 60.0% reported an improvement in Expanded Program on Immunization services related to their use. Among participants who received a reminder, 51.0% kept their vaccination appointments. The Penta 1/3 dropout rate decreased from 3.2% before the intervention to 1.3% (p < 0.001). Among the 323 parents of children included, only 20.74% reported receiving a reminder by phone. Sixty-point-five percent (60.5%) preferred to receive both text messages and voice calls. ConclusionThis study demonstrates the operational feasibility of an SMS/call-based reminder system in reducing dropout rate for childhood vaccination in Togo.

BackgroundTuberculosis (TB) remains a leading cause of infectious disease mortality worldwide, and treatment failure contributes to ongoing transmission, drug resistance, and poor clinical outcomes. Artificial intelligence and machine learning approaches have attracted growing interest for predicting tuberculosis treatment outcomes, but the literature is heterogeneous and lacks a comprehensive synthesis. MethodsWe conducted a systematic review and meta-analysis of studies that developed or validated machine learning models to predict TB treatment failure. We searched PubMed/MEDLINE and Embase from January 2000 to October 2025. Studies were eligible if they developed, validated, or implemented an artificial intelligence or machine learning model for the prediction of TB treatment failure or a closely related poor outcome in patients receiving anti-TB treatment. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool. Random-effects meta-analysis was performed to pool area under the curve values, with subgroup analyses and meta-regression to explore heterogeneity. ResultsThirty-four studies were included in the systematic review, of which 19 reported area under the curve values suitable for meta-analysis (total participants, 100,790). Studies were published between 2014 and 2025, with 91% published from 2019 onward. Tree-based methods were the most common algorithm family (52.9%), and multimodal models integrating three or more data types were used in 41.2% of studies. The pooled area under the curve was 0.836 (95% confidence interval 0.799-0.868), with substantial heterogeneity (I{superscript 2} = 97.9%). In subgroup analyses, studies including HIV-positive participants showed lower discrimination (pooled area under the curve 0.748) compared to those excluding them (0.924). Only eight studies (23.5%) performed external validation, and only one study (2.9%) was rated as low risk of bias overall, primarily due to methodological concerns in the analysis domain. Eggers test suggested publication bias (p = 0.024). Major evidence gaps included underrepresentation of high-burden countries, HIV-affected populations, social determinants, pediatric TB, and extrapulmonary disease. ConclusionsMachine learning models for predicting TB treatment failure show promising discrimination but are not yet ready for routine clinical implementation. Performance varies substantially across populations and settings, and methodological limitations, including inadequate validation, poor calibration assessment, and high risk of bias, limit confidence in current estimates. Future research should prioritize rigorous external validation, calibration assessment, and development in underrepresented populations, particularly HIV-affected and high-burden settings. Author SummaryTB kills over a million people annually. While curable, treatment failure remains common and drives ongoing transmission and drug resistance. Researchers increasingly use artificial intelligence and machine learning to predict which patients will fail treatment, but it is unclear if these models are ready for clinical use. We reviewed 34 studies including nearly 1.1 million participants from 22 countries. On average, models correctly distinguished patients who would fail treatment from those who would not 84% of the time, a performance generally considered good. However, this average hid enormous variation. Models developed in populations including HIV-positive people performed substantially worse, suggesting prediction is harder with HIV co-infection. Worryingly, only one study used high-quality methods; 97% had serious flaws in handling missing data, checking calibration, or testing in new populations. Only eight studies validated their models in different settings. To conclude, we found that machine learning is promising in predicting TB treatment failure, but it is not ready for clinical use. Researchers should prioritize validation in high-burden settings, include social determinants, and improve methodological rigor before these tools can help patients.

BackgroundScrub typhus is a major yet neglected vector-borne disease in Thailand, where it has been nationally notifiable for over two decades. However, long-term changes in its epidemiology, including reporting rates, transmission intensity, disease severity, and seasonal patterns, have not been comprehensively characterised at the national level. MethodologyWe analysed 22 years of national surveillance data for scrub typhus in Thailand (2003-2024) using a latent process model that jointly fits reported cases with published nationwide seroprevalence data and antibody kinetics to estimate reporting rates and underlying transmission dynamics across all 77 provinces of Thailand. FindingsOver the 22-year study period, 143096 cases and 119 deaths were reported nationally. Estimated reporting proportion broadly mirrored transmission intensity, being higher in high-burden regions and lower elsewhere. A synchronous decline in detection was observed across all regions during the COVID-19 pandemic, followed by rapid rebound by 2024. After accounting for these reporting dynamics, the force of infection was highest in the northern provinces but also substantial in the northeast and south, with upward trends in some provinces. Susceptibility among older adults aged 65 and above increased progressively over the study period, reversing the pattern observed two decades earlier. Case-fatality in the 25-35-year reference group was low and declined from 0.14% (95% Credible Interval [CrI]: 0.06-0.29%) to 0.06% (95% CrI: 0.02-0.12%), but relative case-fatality remained consistently highest among adults above 65 across all periods. Three geographically distinct seasonal patterns were identified, all stable over time. ConclusionOver two decades, scrub typhus transmission in Thailand has been shown to extend well beyond its traditionally recognised northern focus, with substantial burden in previously underappreciated regions, while the demographic profile of those most affected has shifted progressively toward older adults. These findings support the need for regionally tailored surveillance, age-targeted clinical preparedness, and sustained investment in understanding the ecological drivers of transmission. Key messagesScrub typhus is a common but neglected cause of fever in Thailand, where it has been reported through the national surveillance system for over two decades. However, trends in reported cases can be misleading because they reflect not only true changes in transmission but also variation in diagnosis and reporting over time and across regions. We developed a model that combines surveillance data with seroprevalence surveys and antibody kinetics to separate true changes in transmission from variation in reporting, allowing us to estimate how transmission intensity, disease severity, and seasonal patterns have evolved from 2003 to 2024 across all 77 provinces. We found that substantial transmission occurs not only in the well-studied northern provinces but also in the northeast and south, where the disease has received less attention. Susceptibility has progressively shifted toward older adults, who also face the highest case-fatality, while three distinct seasonal patterns vary by region but have remained stable over time. These findings suggest that scrub typhus control in Thailand requires a shift from a predominantly northern focus toward regionally tailored strategies that account for local transmission timing, an ageing at-risk population, and the ecological drivers that sustain transmission in each setting.

Abstract Background Timely diagnosis of tuberculosis and drug resistance remains a cornerstone of effective disease control. Multiplex open molecular platforms capable of simultaneously detecting Mycobacterium tuberculosis complex (MTBc), non-tuberculous mycobacteria (NTM), and resistance to first-line anti-tuberculosis drugs could streamline diagnostic pathways. Methods We conducted a laboratory-based evaluation of two multiplex real-time PCR assays (MTBc/NTM R-Gene and MTB-RIF/INH R-Gene) using 300 well-characterized samples, including 150 MTBc-positive culture isolates (including rifampicin-resistant, isoniazid-resistant, and drug-susceptible strains) and 150 MTBc-negative samples (50 NTM isolates and 100 mycobacteria-negative specimens). Composite reference standards included culture, MPT64 antigen testing, and line probe assay corroborated by phenotypic drug susceptibility testing for resistance profiling, with NTM speciation performed using a dedicated line probe assay. DNA extraction was performed using the QIAamp DNA Mini Kit (QIAGEN, Germany), followed by amplification on a real-time PCR platform according to manufacturer instructions. The diagnostic performance was assessed against composite reference standards. Results The analytical performance for detecting MTBc demonstrated 100% sensitivity and specificity (150/150). NTM detection showed 70.0% sensitivity (35/50) and a specificity of 100%, highlighting limitations in coverage of NTM species. Rifampicin resistance was detected with a sensitivity of 96.0% (48/50) and specificity of 100%, whereas isoniazid resistance detection was 100% sensitive and specific (50/50). Agreement with established reference standards was high ({kappa}=0.76-1.00) within this analytical context. Interpretation This analytical validation demonstrates that multiplex open real-time PCR assays can accurately and simultaneously detect MTBc, NTM, and rifampicin and isoniazid resistance using culture isolates. While these platforms offer potential advantages in flexibility and expanded resistance profiling, additional studies on clinical diagnostic accuracy, cost-effectiveness analyses, and operational feasibility are required to determine their practical utility and programmatic impact in high-burden settings

Background Nepal has set a goal to eliminate lymphatic filariasis (LF) by 2030. As of 2024, Nepal has stopped the mass drug administration (MDA) in 56 of the 64 endemic districts and completed two rounds of MDA in six districts with persistent LF ([&ge;]2% antigen prevalence) using the three-drug regimen of Ivermectin, Diethylcarbamazine, and Albendazole (IDA), exceeding 65% coverage. We subsequently conducted an Epidemiological Monitoring Survey (EMS) to assess the impact of the MDA in reduction of LF infection prevalence below the transmission threshold and examine the factors associated with it. Methods We conducted a cross-sectional EMS nine months after MDA in 12 evaluation units (EUs) across six districts, with two sites per EU. We recruited a total of 7,343 individuals aged [&ge;]20 years, sampled using multi-stage sampling, ensuring at least 300 blood samples collected per site. We collected data on demographics and MDA participation. We performed the LF antigen testing for all participants, followed by night blood microfilariae testing in antigen-positive individuals. Statistical analyses included non-parametric tests, Chi-square and Fishers Exact tests, and multivariable logistic regression to assess outcomes after adjusting for potential confounders. Results Nine of 12 evaluation units (EUs) recorded <1% microfilaremia, meeting the WHO threshold for passing EMS, while three EUs failed with [&ge;]1% prevalence in at least one site. Antigen and MF prevalence were 4.47% and 0.34%, respectively (ratio 13:1). Both Antigen and MF prevalences were significantly associated with female sex (AOR= 0.564, 95% CI: 0.441-0.721 and AOR = 0.326, 95% CI: 0.129-0.826 respectively) and participation in the most recent MDA round (AOR = 0.477; 95% CI: 0.385-0.591 and AOR = 0.089; 95% CI: 0.017-0.464 respectively). MDA uptake was influenced by age (<40 years, AOR = 0.72; 95% CI: 0.653-0.793), sex (female, AOR = 1.438; 95% CI: 1.29-1.603), cross-border residence (AOR = 0.616; 95% CI: 0.558-0.681), and occupation (agriculture and housewife, AOR = 1.144; 95% CI: 1.008-1.298). MF prevalence was also associated with younger age (<40 years, AOR = 0.211; 95% CI: 0.071-0.626). Conclusion The survey indicates progress toward LF elimination, with nine of twelve EUs achieving WHOs <1% microfilaremia threshold after two rounds of IDA-MDA. However, transmission persists in three sites, likely linked to poor MDA participation among specific subgroups--particularly males, younger adults, and cross-border populations. Strengthening MDA coverage and compliance across all demographic and occupational groups, with special focus on border areas, is essential to achieve LF elimination in Nepal.

The majority of emerging infectious diseases are zoonotic, having their origin in wildlife before spilling over into the human population. While small mammals are recognized as critical reservoirs for these viruses, their viral diversity remains largely uncharacterized across many African countries. We conducted molecular surveillance of synanthropic rodents and shrews in the Kibera informal settlement in Nairobi and the rural Taita Hills region of Kenya to detect and characterize potential zoonotic viruses. Tissue samples from 228 rodents and shrews were screened for six viral families using PCR assays. Rat hepatitis E virus (HEV) (Rocahepevirus ratti), a rodent-associated virus with potential for human spillover, was identified in Mus musculus and Rattus norvegicus from Kibera. NGS was conducted for the HEV positive samples, and we obtained two near-complete HEV genomes from Rattus norvegicus, which clustered within rodent-associated HEV genotypes in the phylogenetic analysis. The two sequences from the Rattus norvegicus cluster together, indicating a close genetic relationship. Paramyxoviruses belonging to the genera Jeilongvirus and Parahenipavirus were detected both from Taita and Kibera in nine different samples from Rattus norvegicus, Mus minutoides, Crocidura sp and Acomys ignitus. One paramyxovirus positive sample (Acomys ignitus) from Taita was selected for further sequencing with NGS, and a complete genome of a new jeilongvirus was assembled. Phylogenetic analysis of the detected viruses confirmed the close relation to previously known rodent-borne jeilongviruses but also revealed potentially novel jeilong- and parahenipavirus species. Our findings highlight the circulation of potentially zoonotic viruses in both urban and rural small mammals in Kenya. It emphasizes the necessity of continued genomic surveillance of zoonotic viruses to mitigate risks of their spillover into human populations. HighlightsO_LISurveillance reveals diverse rodent-borne viruses circulating in Kenya. C_LIO_LIRat-HEV was detected in Rattus norvegicus and Mus musculus from an urban low-income area. C_LIO_LIParamyxoviruses were detected across multiple rodent and shrew species, including novel Acomys ignitus jeilongvirus. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/719784v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@194e81eorg.highwire.dtl.DTLVardef@11342cdorg.highwire.dtl.DTLVardef@186ad97org.highwire.dtl.DTLVardef@eeb516_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundZero-dose children, defined as those who have not received the first dose of a diphtheria-tetanus-pertussis-containing vaccine (DPT1), are a key indicator of inequitable access to immunization services. Nigeria remains one of the largest contributors to the global burden of zero-dose children. This study estimated the prevalence of zero-dose children aged 12-23 months and identified individual-and community-level determinants using the 2024 Nigeria Demographic Health Survey (NDHS). MethodsA secondary analysis of cross-sectional analysis was conducted using data from 4,711 children aged 12-23 months in the 2024 NDHS kids recode dataset. A multilevel mixed-effects logistic regression model was fitted to account for the hierarchical structure of the data. Four models were compared: null, individual-level, community-level, and combined models. Adjusted odds ratios (AORs) with 95% confidence interval (CI) were used to identify significant determinants at p<0.05. ResultsThe weighted prevalence of zero-dose children was 37.3% (95% CI: 35.1-39.6%). Significant factors included birth order, maternal age, maternal occupation, parental education, household wealth, antenatal attendance, postnatal care utilization, place of delivery, religion, distance to health facilities, and geographical region. Children whose mothers had higher educational attainment, attending antenatal care, deliver in the health facilities, and received postnatal care were significantly less likely to be zero-dose status. Conversely, children from poorer households, those facing distance barriers to health facilities, those belongings to Muslim and traditional religion group and those residing in certain geographical regions had higher odds of zero-dose children, with significant regional variations observed. Conclusionzero-dose vaccination remains highly prevalent in Nigeria and is strongly influenced by socioeconomic disadvantage, maternal healthcare utilization, religion, and regional inequities. Strengthening integrated maternal and child health services and improving access in underserved regions are essential to achieving equitable vaccination coverage.

Typhoid fever remains a significant public health challenge in low- and middle-income countries. In 2018, The World Health Organization recommended a single dose typhoid conjugate vaccine (TCV) for routine immunization in endemic settings; however, evidence guiding booster doses remains limited. Homologous TCV booster doses have demonstrated immune boosting. This study assessed the immunogenicity and safety of a heterologous booster using a Vi capsular polysaccharide-CRM197 TCV (Vi-CRM) administered 5-6 years after primary vaccination with a Vi capsular polysaccharide tetanus toxoid TCV (Vi-TT) in children. Children previously enrolled in a Phase 2 trial were recruited. Participants who had received TCV at 9-11 or 15-23 months were given a Vi-CRM booster at 6-7 years of age (Booster-TCV group), and controls received their first TCV dose at the same age (1st-TCV group). Serum anti-Vi IgG concentrations were measured at baseline and 28 days post-vaccination. Solicited and unsolicited adverse events (AEs) and serious adverse events (SAEs) were recorded. Among 147 children enrolled, 87 received a second and 60 received a first TCV dose. Baseline anti-Vi IgG geometric mean titers (GMT) were higher in the Booster-TCV group (21.5 EU/mL; 95% CI: 17.2-26.8) than in the 1st-TCV group (5.5 EU/mL; 95% CI: 4.5-6.7). At day 28, GMTs rose markedly in both groups: 5140.0 EU/mL (95% CI: 4302.0-6141.3) in the Booster-TCV group and 2084.8 EU/mL (95% CI: 1724.4-2520.5) in the 1st-TCV group. Local reactions and systemic AEs were mild. No SAEs were observed. Vi-TT-induced immunity persisted for at least 5-6 years, and a heterologous booster triggered a strong immune response with universal seroconversion. These findings support heterologous prime-boost strategies to maintain protection in school-age children and inform optimization of TCV schedules in endemic regions.

ObjectiveStudies of nutritional status and host responses during severe and critical illness have focused predominantly on obesity; in contrast, the relationship between undernutrition, host responses, and clinical outcomes in adults hospitalized with severe infection remains poorly defined. We sought to determine whether severe undernutrition is associated with distinct host responses and clinical outcomes in adults hospitalized with severe infection. DesignProspective cohort study. SettingTwo public referral hospitals in Uganda. PatientsNon-pregnant adults ([&ge;]18 yr) hospitalized with severe, undifferentiated infection. InterventionsNone. Measurements and Main ResultsWe analyzed clinical data and serum Olink proteomic data from 432 participants (median age, 45 yr [IQR, 31-57 yr]; 44% male). Overall, 213 participants (49%) met prespecified criteria for undernutrition, including 52 (12%) with severe undernutrition. Clinically, severe undernutrition was associated with HIV coinfection, microbiologically diagnosed tuberculosis, greater physiological instability, and higher mortality. After adjustment for age, sex, illness duration, study site, and HIV, malaria, and tuberculosis coinfection, severe undernutrition was associated with higher expression of proteins involved in pro-inflammatory immune signaling, endothelial and vascular remodeling, hypoxia and oxidative stress responses, and extracellular matrix remodeling, together with lower expression of proteins linked to growth signaling, anticoagulant regulation, and lipid homeostasis. ConclusionsSevere undernutrition is associated with a distinct high-risk clinical phenotype and biologic signature in adults hospitalized with severe infection. These findings suggest that undernutrition may potentiate key domains of sepsis pathobiology, with implications for strengthening nutritional support and informing host-directed treatment strategies in low- and middle-income countries where malnutrition is common. Key PointsO_ST_ABSQuestionC_ST_ABSHow does undernutrition influence immune, metabolic, and endothelial responses to severe infection in adults? FindingsIn this multicenter cohort study of 432 adults hospitalized with severe infection in Uganda, severe undernutrition was associated with greater physiologic instability, higher mortality, and a distinct proteomic host-response profile. Adults with severe undernutrition exhibited a proteomic signature characterized by pro-inflammatory immune signaling, endothelial and extracellular matrix remodeling, and hypoxia and oxidative stress responses, together with lower expression of proteins involved in growth signaling, anticoagulant regulation, and lipid homeostasis. MeaningSevere undernutrition is associated with a distinct high-risk clinical and biologic phenotype during severe infection, with implications for nutritional support, risk stratification, and host-directed therapeutic strategies, particularly in low- and middle-income countries.