Prevalence, antimicrobial resistance and genomic comparison of non-typhoidal salmonella isolated from pig farms with different levels of intensification in Yangon Region, Myanmar.

In Myanmar, where backyard, semi-intensive, and intensive pig (Sus scrofa domesticus) farming coexist, there is limited understanding of the zoonotic risks and antimicrobial resistance (AMR) associated with these farming practices. This study was conducted to investigate the prevalence, AMR and genomic features of Salmonella in pig farms in the Yangon region and the impact of farm intensification to provide evidence to support risk-based future management approaches. Twenty-three farms with different production scales were sampled for two periods with three sampling-visit each. Antimicrobial susceptibility tests and whole-genome sequencing were performed on the isolates. The prevalence of Salmonella was 44.5% in samples collected from backyard farms, followed by intensive (39.5%) and semi-intensive farms (19.5%). The prevalence of multi-drug resistant isolates from intensive farms (45/84, 53.6%) was higher than those from backyard (32/171, 18.7%) and semi-intensive farms (25/161, 15.5%). Among 28 different serovars identified, S. Weltevreden (40; 14.5%), S. Kentucky (38; 13.8%), S. Stanley (35, 12.7%), S. Typhimurium (22; 8.0%) and S. Brancaster (20; 7.3%) were the most prevalent serovars and accounted for 56.3% of the genome sequenced strains. The diversity of Salmonella serovars was highest in semi-intensive and backyard farms (21 and 19 different serovars, respectively). The high prevalence of globally emerging S. Kentucky ST198 was detected on backyard farms. The invasive-infection linked typhoid-toxin gene (cdtB) was found in the backyard farm isolated S. Typhimurium, relatively enriched in virulence and AMR genes, presented an important target for future surveillance. While intensification, in terms of semi-intensive versus backyard production, maybe a mitigator for zoonotic risk through a lower prevalence of Salmonella, intensive production appears to enhance AMR-associated risks. Therefore, it remains crucial to closely monitor the AMR and virulence potential of this pathogen at all scales of production. The results underscored the complex relationship between intensification of animal production and the prevalence, diversity and AMR of Salmonella from pig farms in Myanmar.

Rifampicin tolerance and growth fitness among isoniazid-resistant clinical Mycobacterium tuberculosis isolates from a longitudinal study.

Antibiotic tolerance in Mycobacterium tuberculosis reduces bacterial killing, worsens treatment outcomes, and contributes to resistance. We studied rifampicin tolerance in isolates with or without isoniazid resistance (IR). Using a minimum duration of killing assay, we measured rifampicin survival in isoniazid-susceptible (IS, n=119) and resistant (IR, n=84) isolates, correlating tolerance with bacterial growth, rifampicin minimum inhibitory concentrations (MICs), and isoniazid-resistant mutations. Longitudinal IR isolates were analyzed for changes in rifampicin tolerance and genetic variant emergence. The median time for rifampicin to reduce the bacterial population by 90% (MDK90) increased from 1.23 days (IS) and 1.31 days (IR) to 2.55 days (IS) and 1.98 days (IR) over 15-60 days of incubation, indicating fast and slow-growing tolerant sub-populations. A 6 log10-fold survival fraction classified tolerance as low, medium, or high, showing that IR is linked to increased tolerance and faster growth (OR = 2.68 for low vs. medium, OR = 4.42 for low vs. high, p-trend = 0.0003). High tolerance in IR isolates was associated with rifampicin treatment in patients and genetic microvariants. These findings suggest that IR tuberculosis should be assessed for high rifampicin tolerance to optimize treatment and prevent the development of multi-drug-resistant tuberculosis.

Correction: The effect of M. tuberculosis lineage on clinical phenotype.

[This corrects the article DOI: 10.1371/journal.pgph.0001788.].

Immunogenicity of Abdala COVID-19 vaccine in Vietnamese people after primary and booster vaccinations: A prospective observational study in Vietnam.

OBJECTIVES: We studied the immunogenicity after primary and booster vaccinations of the Abdala COVID-19 vaccine, a receptor-binding domain protein subunit vaccine, in Vietnamese people by determining the level of neutralization and cross-neutralization activities against the ancestral SARS-CoV-2 and its variants and SARS-CoV-1. METHODS: We performed a prospective observational study, enrolling adults aged 19-59 years in Dong Thap province, southern Vietnam, and collected blood samples from baseline until 4 weeks after the booster dose. We measured anti-nucleocapsid, anti-spike, and neutralizing antibodies against SARS-CoV-2 and assessed the cross-neutralization against 14 SARS-CoV-2 variants and SARS-CoV-1. Complementary antibody data came from Vietnamese health care workers fully vaccinated with ChAdOx1-S. RESULTS: After primary vaccination, anti-spike antibody and neutralizing antibodies were detectable in 98.4% and 87% of 251 study participants, respectively, with neutralizing antibody titers similar to that induced by ChAdOx1-S vaccine. Antibody responses after a homologous (Abdala COVID-19) or heterologous (messenger RNA BNT162b2) booster could neutralize 14 SARS-CoV-2 variants (including Omicron) and SARS-CoV-1. CONCLUSIONS: Abdala COVID-19 vaccine is immunogenic in Vietnamese people. Enhanced antibody response after a booster dose could cross-neutralize 14 SARS-CoV-2 variants and SARS-CoV-1. Our results have added to the growing body of knowledge about the contribution of protein subunit vaccine platforms to pandemic control.

A Season at the Himalayan Rescue Association Aid Post in Manang.

The Himalayan Rescue Association (HRA) has operated high altitude clinics in Nepal for 50 years, with rising visitor numbers, especially from India, China, and Nepal. New roads have eased access and increased the speed of ascent in some areas. Our aim was to provide a description of the activities, clinical problems, and lecture attendees of the HRA aid post in Manang over one season. We also highlight the evolving challenges of providing healthcare and education in the high Himalayan region. We describe the clinical and educational activities of the HRA aid post in Manang from September 24 to December 1, 2023. Prospective clinical data collection included anonymized patient demographics and diagnoses. Lecture data were taken from the attendee register and by daily manual counts of lecture attendees. We saw 376 patients, 62% of whom were Nepalis. Infectious diseases (42%) and altitude illness (16%) were the most common problems. A total of 846 people from 47 countries attended the daily altitude lectures. Only 5% of attendees were Nepali. Electrical supply interruptions and limitations in medical evacuation options were among the challenges of providing care at a high altitude clinic and preventing altitude illness using educational lectures. Altitude illness remains a common and potentially life-threatening problem, with risks increased by rapid ascent enabled by new road access and by ignorance of risks of altitude among travelers, especially Nepalis. Language barriers in educational outreach call for novel approaches and interventions that will ensure the effectiveness of altitude education.

Diagnostic Prediction Model for Tuberculous Meningitis: An Individual Participant Data Meta-Analysis.

No accurate and rapid diagnostic test exists for tuberculous meningitis (TBM), leading to delayed diagnosis. We leveraged data from multiple studies to improve the predictive performance of diagnostic models across different populations, settings, and subgroups to develop a new predictive tool for TBM diagnosis. We conducted a systematic review to analyze eligible datasets with individual-level participant data (IPD). We imputed missing data and explored three approaches: stepwise logistic regression, classification and regression tree (CART), and random forest regression. We evaluated performance using calibration plots and C-statistics via internal-external cross-validation. We included 3,761 individual participants from 14 studies and nine countries. A total of 1,240 (33%) participants had "definite" (30%) or "probable" (3%) TBM by case definition. Important predictive variables included cerebrospinal fluid (CSF) glucose, blood glucose, CSF white cell count, CSF differential, cryptococcal antigen, HIV status, and fever presence. Internal validation showed that performance varied considerably between IPD datasets with C-statistic values between 0.60 and 0.89. In external validation, CART performed the worst (C = 0.82), and logistic regression and random forest had the same accuracy (C = 0.91). We developed a mobile app for TBM clinical prediction that accounted for heterogeneity and improved diagnostic performance (https://tbmcalc.github.io/tbmcalc). Further external validation is needed.

Southeast Asia initiative to combat SARS-CoV-2 variants (SEACOVARIANTS) consortium.

A strong and effective COVID-19 and future pandemic responses rely on global efforts to carry out surveillance of infections and emerging SARS-CoV-2 variants and to act accordingly in real time. Many countries in Southeast Asia lack capacity to determine the potential threat of new variants, or other emerging infections. Funded by Wellcome, the Southeast Asia initiative to combat SARS-CoV-2 variants (SEACOVARIANTS) consortium aims to develop and apply a multidisciplinary research platform in Southeast Asia (SEA) for rapid assessment of the biological significance of SARS-CoV-2 variants, thereby informing coordinated local, regional and global responses to the COVID-19 pandemic. Our proposal is delivered by the Vietnam and Thailand Wellcome Africa Asia Programmes, bringing together a multidisciplinary team in Indonesia, Thailand and Vietnam with partners in Singapore, the UK and the USA. Herein we outline five work packages to deliver strengthened regional scientific capacity that can be rapidly deployed for future outbreak responses.

Our project strengthens local scientific capacity in South East Asia (SEA) and therefore enables the rapid assessment of SARS-CoV-2 variants as they emerge within the region. While COVID-19 remains a global pandemic, future emerging infections caused by a novel virus is an inevitable event, with SEA being a global hot-spot for pathogen emergence. Consequently, the research capacity built, the scientists trained and the research network formed as part of this project will lay the foundation for future locally-led outbreak responses. Our project will demonstrate that novel research platforms can be set up in other low and middle income countries to address the unprecedented challenges presented by emerging infections.

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal study of 216 adults with TBM; 73 (34%) were HIV-positive, a factor highly correlated with mortality. We implemented an end-to-end framework to model clinical and imaging features to predict disease progression. Our model used state-of-the-art machine learning models for automatic imaging feature encoding, and time-series models for forecasting, to predict TBM progression. The proposed approach is designed to be robust to missing data via a novel tailored model optimisation framework. Our model achieved a 60% balanced accuracy in predicting the prognosis of TBM patients over the six different classes. HIV status did not alter the performance of the models. Furthermore, our approach identified brain morphological lesions caused by TBM in both HIV and non-HIV-infected, associating lesions to the disease staging with an overall accuracy of 96%. These results suggest that the lesions caused by TBM are analogous in both populations, regardless of the severity of the disease. Lastly, our models correctly identified changes in disease symptomatology and severity in 80% of the cases. Our approach is the first attempt at predicting the prognosis of TBM by combining imaging and clinical data, via a machine learning model. The approach has the potential to accurately predict disease progression and enable timely clinical intervention.

Clinical sub-phenotypes of Staphylococcus aureus bacteraemia.

BACKGROUND: Staphylococcus aureus bacteraemia (SAB) is a clinically heterogeneous disease. The ability to identify sub-groups of patients with shared traits (sub-phenotypes) is an unmet need that could allow patient stratification for clinical management and research. We aimed to test the hypothesis that clinically-relevant sub-phenotypes can be reproducibly identified amongst patients with SAB. METHODS: We studied three cohorts of hospitalised adults with monomicrobial SAB: a UK retrospective observational study (Edinburgh cohort, n=458), the UK ARREST randomised trial (n=758), and the Spanish SAFO randomised trial (n=214). Latent class analysis was used to identify sub-phenotypes using routinely-collected clinical data, without considering outcomes. Mortality and microbiologic outcomes were then compared between sub-phenotypes. RESULTS: Included patients had predominantly methicillin-susceptible SAB (1366/1430,95.5%). We identified five distinct, reproducible clinical sub-phenotypes: (A) SAB associated with older age and comorbidity, (B) nosocomial intravenous catheter-associated SAB in younger people without comorbidity, (C) community-acquired metastatic SAB, (D) SAB associated with chronic kidney disease, and (E) SAB associated with injection drug use. Survival and microbiologic outcomes differed between the sub-phenotypes. 84-day mortality was highest in sub-phenotype A, and lowest in B and E. Microbiologic outcomes were worse in sub-phenotype C. In a secondary analysis of the ARREST trial, adjunctive rifampicin was associated with increased 84-day mortality in sub-phenotype B and improved microbiologic outcomes in sub-phenotype C. CONCLUSIONS: We have identified reproducible and clinically-relevant sub-phenotypes within SAB, and provide proof-of-principle of differential treatment effects. Through clinical trial enrichment and patient stratification, these sub-phenotypes could contribute to a personalised medicine approach to SAB.

Genomic insights unveil the plasmid transfer mechanism and epidemiology of hypervirulent Klebsiella pneumoniae in Vietnam.

Hypervirulent Klebsiella pneumoniae (hvKp) is a significant cause of severe invasive infections in Vietnam, yet data on its epidemiology, population structure and dynamics are scarce. We screened hvKp isolates from patients with bloodstream infections (BSIs) at a tertiary infectious diseases hospital in Vietnam and healthy individuals, followed by whole genome sequencing and plasmid analysis. Among 700 BSI-causing Kp strains, 100 (14.3%) were hvKp. Thirteen hvKp isolates were identified from 350 rectal swabs of healthy adults; none from 500 rectal swabs of healthy children. The hvKp isolates were genetically diverse, encompassing 17 sequence types (STs), predominantly ST23, ST86 and ST65. Among the 113 hvKp isolates, 14 (12.6%) carried at least one antimicrobial resistance (AMR) gene, largely mediated by IncFII, IncR, and IncA/C plasmids. Notably, the acquisition of AMR conjugative plasmids facilitated horizontal transfer of the non-conjugative virulence plasmid between K. pneumoniae strains. Phylogenetic analysis demonstrated hvKp isolates from BSIs and human carriage clustered together, suggesting a significant role of intestinal carriage in hvKp transmission. Enhanced surveillance is crucial to understand the factors driving intestinal carriage and hvKp transmission dynamics for informing preventive measures. Furthermore, we advocate the clinical use of our molecular assay for diagnosing hvKp infections to guide effective management.

The impact of antibiotics on the gut microbiota of children recovering from watery diarrhoea.

Infectious diarrhoeal diseases remain a substantial health burden in young children in low- and middle-income countries. The disease and its variable treatment options significantly alter the gut microbiome, which may affect clinical outcomes and overall gut health. Antibiotics are often prescribed, but their impact on the gut microbiome during recovery is unclear. Here, we used 16S rRNA sequencing to investigate changes in the gut microbiota in Vietnamese children with acute watery diarrhoea, and highlight the impact of antibiotic treatment on these changes. Our analyses identified that, regardless of treatment, recovery was characterised by reductions in Streptococcus and Rothia species and expansion of Bacteroides/Phocaeicola, Lachnospiraceae and Ruminococcacae taxa. Antibiotic treatment significantly delayed the temporal increases in alpha- and beta-diversity within patients, resulting in distinctive patterns of taxonomic change. These changes included a pronounced, transient overabundance of Enterococcus species and depletion of Bifidobacterium pseudocatenulatum. Our findings demonstrate that antibiotic treatment slows gut microbiota recovery in children following watery diarrhoea.

Validating the ratio of insulin like growth factor binding protein 4 to sex hormone binding globulin as a prognostic predictor of preterm birth in Viet Nam: a case-cohort study.

OBJECTIVE: To validate a serum biomarker developed in the USA for preterm birth (PTB) risk stratification in Viet Nam. METHODS: Women with singleton pregnancies (n = 5000) were recruited between 19+0-23+6 weeks' gestation at Tu Du Hospital, Ho Chi Minh City. Maternal serum was collected from 19+0-22+6 weeks' gestation and participants followed to neonatal discharge. Relative insulin-like growth factor binding protein 4 (IGFBP4) and sex hormone binding globulin (SHBG) abundances were measured by mass spectrometry and their ratio compared between PTB cases and term controls. Discrimination (area under the receiver operating characteristic curve, AUC) and calibration for PTB <37 and <34 weeks' gestation were tested, with model tuning using clinical factors. Measured outcomes included all PTBs (any birth ≤37 weeks' gestation) and spontaneous PTBs (birth ≤37 weeks' gestation with clinical signs of initiation of parturition). RESULTS: Complete data were available for 4984 (99.7%) individuals. The cohort PTB rate was 6.7% (n = 335). We observed an inverse association between the IGFBP4/SHBG ratio and gestational age at birth (p = 0.017; AUC 0.60 [95% CI, 0.53-0.68]). Including previous PTB (for multiparous women) or prior miscarriage (for primiparous women) improved performance (AUC 0.65 and 0.70, respectively, for PTB <37 and <34 weeks' gestation). Optimal performance (AUC 0.74) was seen within 19-20 weeks' gestation, for BMI >21 kg/m2 and age 20-35 years. CONCLUSION: We have validated a novel serum biomarker for PTB risk stratification in a very different setting to the original study. Further research is required to determine appropriate ratio thresholds based on the prevalence of risk factors and the availability of resources and preventative therapies.

Rifampicin resistant Mycobacterium tuberculosis in Vietnam, 2020-2022.

Objective: We conducted a descriptive analysis of multi-drug resistant tuberculosis (MDR-TB) in Vietnam's two largest cities, Hanoi and Ho Chi Minh city. Methods: All patients with rifampicin resistant tuberculosis were recruited from Hanoi and surrounding provinces between 2020 and 2022. Additional patients were recruited from Ho Chi Minh city over the same time period. Demographic data were recorded from all patients, and samples collected, cultured, whole genome sequenced and analysed for drug resistance mutations. Genomic susceptibility predictions were made on the basis of the World Health Organization's catalogue of mutations in Mycobacterium tuberculosis associated with drug resistance, version 2. Comparisons were made against phenotypic drug susceptibility test results where these were available. Multivariable logistic regression was used to assess risk factors for previous episodes of tuberculosis. Results: 233/265 sequenced isolates were of sufficient quality for analysis, 146 (63 %) from Ho Chi Minh City and 87 (37 %) from Hanoi. 198 (85 %) were lineage 2, 20 (9 %) were lineage 4, and 15 (6 %) were lineage 1. 17/211 (8 %) for whom HIV status was known were infected, and 109/214 (51 %) patients had had a previous episode of tuberculosis. The main risk factor for a previous episode was HIV infection (odds ratio 5.1 (95 % confidence interval 1.3-20.0); p = 0.021). Sensitivity for predicting first-line drug resistance from whole genome sequencing data was over 90 %, with the exception of pyrazinamide (85 %). For moxifloxacin and amikacin it was 50 % or less. Among rifampicin-resistant isolates, prevalence of resistance to each non-first-line drug was < 20 %. Conclusions: Drug resistance among most MDR-TB strains in Vietnam's two largest cities is confined largely to first-line drugs. Living with HIV is the main risk factor among patients with MDR-TB for having had a previous episode of tuberculosis.

Targeted sequencing from cerebrospinal fluid for rapid identification of drug-resistant tuberculous meningitis.

Mortality from tuberculous meningitis (TBM) remains around 30%, with most deaths occurring within 2 months of starting treatment. Mortality from drug-resistant strains is higher still, making early detection of drug resistance (DR) essential. Targeted next-generation sequencing (tNGS) produces high read depths, allowing the detection of DR-associated alleles with low frequencies. We applied Deeplex Myc-TB-a tNGS assay-to cerebrospinal fluid (CSF) samples from 72 adults with microbiologically confirmed TBM and compared its genomic drug susceptibility predictions to a composite reference standard of phenotypic susceptibility testing (pDST) and whole genome sequencing, as well as to clinical outcomes. Deeplex detected Mycobacterium tuberculosis complex DNA in 24/72 (33.3%) CSF samples and generated full DR reports for 22/24 (91.7%). The read depth generated by Deeplex correlated with semi-quantitative results from MTB/RIF Xpert. Alleles with <20% frequency were seen at canonical loci associated with first-line DR. Disregarding these low-frequency alleles, Deeplex had 100% concordance with the composite reference standard for all drugs except pyrazinamide and streptomycin. Three patients had positive CSF cultures after 30 days of treatment; reference tests and Deeplex identified isoniazid resistance in two, and Deeplex alone identified low-frequency rifampin resistance alleles in one. Five patients died, of whom one had pDST-identified pyrazinamide resistance. tNGS on CSF can rapidly and accurately detect drug-resistant TBM, but its application is limited to those with higher bacterial loads. In those with lower bacterial burdens, alternative approaches need to be developed for both diagnosis and resistance detection.

Distinctive antibody responses to Mycobacterium tuberculosis in pulmonary and brain infection.

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), remains a global health burden. While M. tuberculosis is primarily a respiratory pathogen, it can spread to other organs, including the brain and meninges, causing TB meningitis (TBM). However, little is known about the immunological mechanisms that lead to differential disease across organs. Attention has focused on differences in T cell responses in the control of M. tuberculosis in the lungs, but emerging data point to a role for antibodies, as both biomarkers of disease control and as antimicrobial molecules. Given an increasing appreciation for compartmentalized antibody responses across the blood-brain barrier, here we characterized the antibody profiles across the blood and brain compartments in TBM and determined whether M. tuberculosis-specific humoral immune responses differed between M. tuberculosis infection of the lung (pulmonary TB) and TBM. Using a high throughput systems serology approach, we deeply profiled the antibody responses against 10 different M. tuberculosis antigens, including lipoarabinomannan (LAM) and purified protein derivative (PPD), in HIV-negative adults with pulmonary TB (n = 10) versus TBM (n = 60). Antibody studies included analysis of immunoglobulin isotypes (IgG, IgM, IgA) and subclass levels (IgG1-4) and the capacity of M. tuberculosis-specific antibodies to bind to Fc receptors or C1q and to activate innate immune effector functions (complement and natural killer cell activation; monocyte or neutrophil phagocytosis). Machine learning methods were applied to characterize serum and CSF responses in TBM, identify prognostic factors associated with disease severity, and define the key antibody features that distinguish TBM from pulmonary TB. In individuals with TBM, we identified CSF-specific antibody profiles that marked a unique and compartmentalized humoral response against M. tuberculosis, characterized by an enrichment of M. tuberculosis-specific antibodies able to robustly activate complement and drive phagocytosis by monocytes and neutrophils, all of which were associated with milder TBM severity at presentation. Moreover, individuals with TBM exhibited M. tuberculosis-specific antibodies in the serum with an increased capacity to activate phagocytosis by monocytes, compared with individuals with pulmonary TB, despite having lower IgG titres and Fcγ receptor-binding capacity. Collectively, these data point to functionally divergent humoral responses depending on the site of infection (i.e. lungs versus brain) and demonstrate a highly compartmentalized M. tuberculosis-specific antibody response within the CSF in TBM. Moreover, our results suggest that phagocytosis- and complement-mediating antibodies may promote attenuated neuropathology and milder TBM disease.

Development and validation of multiplex real-time PCR for simultaneous detection of six bacterial pathogens causing lower respiratory tract infections and antimicrobial resistance genes.

BACKGROUND: Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Escherichia coli, Streptococcus pneumoniae and Staphylococcus aureus are major bacterial causes of lower respiratory tract infections (LRTIs) globally, leading to substantial morbidity and mortality. The rapid increase of antimicrobial resistance (AMR) in these pathogens poses significant challenges for their effective antibiotic therapy. In low-resourced settings, patients with LRTIs are prescribed antibiotics empirically while awaiting several days for culture results. Rapid pathogen and AMR gene detection could prompt optimal antibiotic use and improve outcomes. METHODS: Here, we developed multiplex quantitative real-time PCR using EvaGreen dye and melting curve analysis to rapidly identify six major pathogens and fourteen AMR genes directly from respiratory samples. The reproducibility, linearity, limit of detection (LOD) of real-time PCR assays for pathogen detection were evaluated using DNA control mixes and spiked tracheal aspirate. The performance of RT-PCR assays was subsequently compared with the gold standard, conventional culture on 50 tracheal aspirate and sputum specimens of ICU patients. RESULTS: The sensitivity of RT-PCR assays was 100% for K. pneumoniae, A. baumannii, P. aeruginosa, E. coli and 63.6% for S. aureus and the specificity ranged from 87.5% to 97.6%. The kappa correlation values of all pathogens between the two methods varied from 0.63 to 0.95. The limit of detection of target bacteria was 1600 CFU/ml. The quantitative results from the PCR assays demonstrated 100% concordance with quantitative culture of tracheal aspirates. Compared to culture, PCR assays exhibited higher sensitivity in detecting mixed infections and S. pneumoniae. There was a high level of concordance between the detection of AMR gene and AMR phenotype in single infections. CONCLUSIONS: Our multiplex quantitative RT-PCR assays are fast and simple, but sensitive and specific in detecting six bacterial pathogens of LRTIs and their antimicrobial resistance genes and should be further evaluated for clinical utility.

A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis.

BACKGROUND: Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known. METHODS: We included 659 individuals aged [Formula: see text] years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl-Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified the reduction in TBM risk after confirmatory tests were negative. We also fitted a simplified model and developed a scoring table for early screening. All models were compared and validated internally. RESULTS: Participants with HIV, miliary TB, long symptom duration, and high cerebrospinal fluid (CSF) lymphocyte count were more likely to have TBM. HIV and higher CSF protein were associated with higher mycobacillary burden. In the simplified model, HIV infection, clinical symptoms with long duration, and clinical or radiological evidence of extra-neural TB were associated with TBM At the cutpoints based on Youden's Index, the sensitivity and specificity in diagnosing TBM for our full and simplified models were 86.0% and 79.0%, and 88.0% and 75.0% respectively. CONCLUSION: Our diagnostic model shows reliable performance and can be developed as a decision assistant for clinicians to detect patients at high risk of TBM. Diagnosis of tuberculous meningitis is hampered by the lack of gold standard. We developed a diagnostic model using latent class analysis, combining confirmatory test results and risk factors. Models were accurate, well-calibrated, and can support both clinical practice and research.

Spatial Analysis of Drug-Susceptible and Multidrug-Resistant Cases of Tuberculosis, Ho Chi Minh City, Vietnam, 2020-2023.

We characterized the spatial distribution of drug-susceptible (DS) and multidrug-resistant (MDR) tuberculosis (TB) cases in Ho Chi Minh City, Vietnam, a major metropolis in southeastern Asia, and explored demographic and socioeconomic factors associated with local TB burden. Hot spots of DS and MDR TB incidence were observed in the central parts of Ho Chi Minh City, and substantial heterogeneity was observed across wards. Positive spatial autocorrelation was observed for both DS TB and MDR TB. Ward-level TB incidence was associated with HIV prevalence and the male proportion of the population. No ward-level demographic and socioeconomic indicators were associated with MDR TB case count relative to total TB case count. Our findings might inform spatially targeted TB control strategies and provide insights for generating hypotheses about the nature of the relationship between DS and MDR TB in Ho Chi Minh City and the wider southeastern region of Asia.

Emerging Enterovirus A71 Subgenogroup B5 Causing Severe Hand, Foot, and Mouth Disease, Vietnam, 2023.

We report on a 2023 outbreak of severe hand, foot, and mouth disease in southern Vietnam caused by an emerging lineage of enterovirus A71 subgenogroup B5. Affected children were significantly older than those reported during previous outbreaks. The virus should be closely monitored to assess its potential for global dispersal.