BMC Infectious Diseases

BackgroundFamily-based HIV index case testing identifies family members with unknown HIV status and links them to care. Data are limited in southern Ethiopia. MethodsA facility-based cross-sectional study was conducted among 377 adults on antiretroviral therapy (ART) in Wolaita Zone, Southern Ethiopia, from November 2022 to May 2023. Participants were selected using systematic random sampling. Data were collected via interviewer-administered semi-structured questionnaire. Multivariable logistic regression identified factors associated with index case family testing. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated, and statistical significance was declared at p < 0.05. ResultsThe proportion of index case family testing for HIV was 84.9% (95% CI: 81.2- 88.6). In multivariable analysis, urban residence (AOR = 2.8; 95% CI: 1.16-6.75), duration on ART greater than 12 months (AOR = 13.0; 95% CI: 4.6-36.9), disclosure of HIV status to family members (AOR = 5.6; 95% CI: 1.9-16.5), discussion of HIV status with family members (AOR = 6.6; 95% CI: 1.9-23.2), and being counselled by health professionals to bring families for testing (AOR = 6.3; 95% CI: 2.1-19.0) were significantly associated with index case family testing. ConclusionThe prevalence of family-based HIV index case testing in Wolaita Zone was 84.9%, below the national 95% target. Health professionals should strengthen counselling on ART adherence, status disclosure, family discussion, and active referral to improve testing uptake among family members of people living with HIV.

Objectives: To identifiy risk factors for antimicrobial resistance (AMR) in seven pathogen-antimicrobial combinations in patients with cancer and cancer survivors. Methods: Using data from patients with recent or past cancer diagnostic codes in Oxfordshire, UK, we examined associations between 22 potential risk-factors and AMR in blood culture isolates, collected between 1-April-2015 and 31-March-2025. Results: Among 5,975 bacteraemias in 4,365 adults, we analysed 3,141 (52.6%) due to Enterobacterales and 620 (10.4%) due to Enterococcus faecalis/faecium in 2,752 patients. Fourteen risk-factors for antimicrobial-resistant bacteraemia were identified, varying across pathogen-antimicrobial combinations. Compared with no previous antimicrobial susceptibility test result, prior resistance to the same antibiotic in any culture in the last year was strongly associated with AMR across all pathogen-antimicrobial combinations (all p<=0.001). Prior antibiotic exposure and younger age were also positively associated with AMR in four and five combinations, respectively. Cancer type showed modest effects; lymphoid/haematopoietic malignancies were associated with higher odds (vs colorectal cancer) of trimethoprim-sulfamethoxazole-resistant Enterobacterales (aOR=2.07 95%CI 1.40-3.06) and vancomycin-resistant Enterococcus bacteraemia (aOR=6.68, 1.21-36.91). Conclusions: Previous resistance was the greatest risk factor for bacteraemia with AMR in cancer patients and survivors, with prior antibiotic exposure and age also contributing. Lymphoid/haematopoietic malignancies increased risk of resistance to specific antimicrobials. Keywords: antimicrobial resistance, bacteraemia, cancer, risk factors

BackgroundDelayed tuberculosis (TB) treatment remains a major challenge to TB control and is associated with increased mortality, drug resistance, and onward transmission. Food insecurity may contribute to delayed TB treatment through economic, physical, and psychosocial pathways. Depression and anxiety are also associated with delayed TB treatment and may mediate the relationship between food insecurity and delayed TB treatment. This study examined the association between food insecurity and delayed TB treatment initiation and assessed the mediation roles of depression and anxiety for this relationship among people newly diagnosed with TB. MethodsWe recruited 180 participants newly diagnosed with TB in Gaborone, Botswana. Food insecurity, depression, and anxiety were measured using the Household Food Insecurity Access Scale, PHQ-9, and Zung Self-Rating Anxiety Scale, respectively. Delayed TB treatment was defined as > 2 months since first TB symptoms. Logistic regression was used to examine the association between food insecurity and delayed TB treatment. Causal mediation analysis was conducted to assess the mediating roles of depression and anxiety. ResultsAmong the 180 participants, 45 (25%) experienced delayed TB treatment initiation. Participants with delayed TB treatment had slightly higher median scores for food insecurity (2 vs. 1, p = 0.11), depression (9 vs. 6, p = 0.001), and anxiety (37 vs. 34, p = 0.05). There was insufficient evidence of an overall association between food insecurity and delayed TB treatment initiation (OR = 1.04, 95% CI 0.98-1.11, p = 0.20). Mediation analysis found insufficient evidence of total and direct effects through depression and anxiety. However, there was evidence of significant indirect effect through depression (OR = 1.04, 95% CI 1.01-1.08, p < 0.001) and a borderline indirect effect through anxiety (OR = 1.02, 95% CI 1.00-1.04, p = 0.05). ConclusionMediation analysis revealed associations between food insecurity and delayed TB treatment initiation mediated by depression and anxiety which were not evident in total effects analysis. These findings highlight the importance of considering both socioeconomic and psychological factors in addressing delayed TB treatment. Further studies are needed to confirm these pathways.

Introduction: Antibiotic misuse is a major driver of antimicrobial resistance (AMR), contributing to an estimated 1.27 million deaths globally. In Kenya, inappropriate antibiotic use is shaped by health-seeking behaviors and sociodemographic factors. However, little is known about how adults with productive coughs seek and use antibiotics, or how sociodemographic factors underpin these practices. This study explored antibiotic-seeking pathways, usage patterns, and the sociodemographic factors influencing these practices among adults with productive coughs attending selected chest and tuberculosis clinics in Nairobi County, Kenya. Methodology: A facility-based cross-sectional study was conducted among 400 adults ([&ge;]18 years) with productive coughs. Data were collected using a structured questionnaire on sociodemographic characteristics, antibiotic-seeking pathways, and use patterns. Results: Most participants were male (65.0%) and employed (67.0%), with 68.3% earning below Ksh 10,000 (approximately USD 80) monthly and 35.8% having basic education. A history of smoking (37.3%), tuberculosis (32.0%), or other comorbidities (29.8%) was common. Among 347 (86.7%) antibiotic users, 46.4% obtained antibiotics through general practitioners (GP) only, 31.4% via both GP and over-the-counter (OTC) sources, 15.3% from OTC only, and 6.9% through self-medication. Females were more likely to self-medicate (13.3% vs. 3.2%) and had higher odds of antibiotic use (cOR: 2.00; 95% CI: 1.04-4.10). Tuberculosis history was linked to greater GP reliance (61.7% vs. 37.4%). Low-income participants mainly used GP-only sources, while higher-income earners favored GP plus OTC routes (RRR: 2.67; 95% CI: 1.41-5.05). Empirical use was common (71.1%), dominated by Amoxicillin (90.8%), with multiple antibiotic use reported by 67.2% of the participants. Conclusion: Antibiotic use among adults with productive coughs in Nairobi was widespread and largely empirical, dominated by Amoxicillin and Amoxicillin/Clavulanic acid. Self-medication, unregulated antibiotic access, and inappropriate use highlight the urgent need for stricter prescription enforcement and strengthened stewardship programs to promote rational antibiotic use and curb AMR.

Background: The global burden of dengue infection has rising, yet limited data exists on its impact in the Caribbean. We describe the incidence and associates of acute kidney injury in adults and children with dengue at a teaching hospital in Jamaica. Methods: A single-centre retrospective cohort study of admissions with laboratory confirmed dengue infection at University Hospital of the West Indies, Mona Jamaica between January 2023 to November 2024. AKI was defined using Kidney Disease Improving Global Outcomes definitions. Patients were included if aged >1year and had at least 2 creatinine values. Clinical, demographic and laboratory data were abstracted by chart review. Summary statistics were used to describe continuous and categorical data, and logistic regression to determine AKI associations. Stratified analysis was performed by age-group (adults-aged [&ge;] 16, and paediatric-aged <16 years). Results: Analyses included 167 persons, 62% (103) were male, mean age was 26.1{+/-}19.5 years. AKI occurred in 25.8%, 65.1% were KDIGO stage 1. AKI incidence was 30.2% and 18.0% among adults and children respectively. There were 3 in-hospital deaths. People with AKI were older 32{+/-}21.4 vs 24 {+/-}18.4 (p=0.021), and had longer duration of stay [6 vs 4 days (p <0.001)]. Male sex [OR 2.09 (95% CI:0.96-4.59), p=0.064], age per year [OR 1.02 (95% CI:1.01-1.04), p=0.015] symptom duration [OR1.11 (CI 0.99-1.24), p = 0.058], admission bilirubin [OR 1.02 (CI: 1.00-1.04), p = 0.022], NLR [OR 1.09 (CI 1.00-1.18), p = 0.037] were associated with AKI. In adults admission potassium was inversely associated with AKI [OR 0.46 (95% CI 0.21-1.01), p 0.056], while in children admission potassium [OR 3.00 (95% CI 0.88-10.6), p 0.088] was associated with AKI. Conclusion: AKI in dengue hospitalizations is higher than most reports at 25.8%. Targeted public health policy on vector control and early symptom recognition may be needed to improve outcomes.

BackgroundTo date, accessible diagnostic tools to identify whether a patients pneumonia is a bacterial, or viral infection, are not accurate or timely enough to prevent preemptive antibiotic administration. Relying on single biomarkers or clinical presentations has been insufficient. We aimed to incorporate a wide range of novel biomarkers and clinical presentations in a multivariable model and validate its capacity to differentiate cases of bacterial and viral pneumonia. MethodsData from 457 children aged 2-59 months, admitted to Kilifi County Referral Hospital, Kenya, with bacterial (n = 229) and viral (n = 228) infections, were used to develop and validate a predictive multivariable Poisson regression model to differentiate pneumonia etiology. The Receiver Operating Characteristic curve was used to assess biomarker performance and validate the model internally. ResultsSixty-three percent (63%) of the children presented with severe pneumonia. 72% with viral pneumonia had severe pneumonia, compared to 54% with bacterial pneumonia who had severe pneumonia. In crude analyses, chest-wall indrawing, cough, convulsions, crackles, angiotensinogen, and Serpin Family A Member 1 were significantly associated with pneumonia etiology, controlling for age. However, only chest-wall indrawing remained significant in multivariable analyses after controlling for age. The model demonstrated fair, but inadequate, discrimination, with an Area Under the Curve of 0.61. ConclusionAmong the children admitted to hospital with WHO defined pneumonia, a wide range of biomarkers and clinical presentations still failed to distinguish bacterial from viral pneumonia.

Justification: Accidental lab-acquired infections (LAIs) with potential pandemic pathogens (PPPs) in high-biosafety research facilities risk causing a pandemic. Routine testing of lab workers for LAIs coupled with isolation of infected workers could reduce the risk, but the impact of such an intervention may depend on pathogens' epidemiological characteristics. Objective: This study aims to understand how the epidemiological characteristics of PPPs moderate the efficacy of a routine testing and isolation intervention in preventing larger outbreaks after an LAI. Methods: We employed a discrete-time stochastic network infectious disease model to run 625,000 epidemic simulations encompassing 625 unique combinations of five parameters of interest: test frequency, pathogen transmissibility, the self-isolation rate for symptomatic cases, the percentage of cases that are asymptomatic, and the percentage of infectious time that is spent in the pre-symptomatic state among those who show symptoms. To summarize the Monte Carlo simulations, we paired visual analysis with logistic regression for formal hypothesis testing, with an emphasis on the interaction terms that capture the moderating effect of epidemiological parameters on the impact of test frequency. Main Results: There were four main findings. First, the relative reductions in risk of outbreak that were caused by increased test frequency were inversely correlated with pathogen transmissibility. Second, the effect of test frequency was magnified at higher asymptomatic shares when the symptomatic self-isolation rate was high, but minimally when the self-isolation rate is low. Third, the direction of how the symptomatic self-isolation rate moderated the effect of increased test frequency depended on the asymptomatic share. Fourth, as the pre-symptomatic share of infectious time increased, the effect of test frequency on the probability of an outbreak was strongly magnified largely independent of symptomatic self-isolation rates. Conclusions: Routine testing and isolation could significantly mitigate the risk of catastrophic PPP escapes, with the intervention's success varying based on pathogen characteristics. High shares of asymptomatic and pre-symptomatic transmission notably increased the relative risk reductions achieved by the intervention. These findings suggest prioritizing testing interventions for pathogens with high asymptomatic and pre-symptomatic transmission and highlight the symptomatic self-isolation rate as a policy intervention target.

Objectives: To evaluate whether on-site molecular point-of-care testing (POCT) for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) is associated with reduced antibiotic overtreatment for presumed sexually transmitted infections (STIs) among adults living with HIV in rural Uganda. Methods: We conducted a single-site quasi-experimental pre-post intervention study at Kumi Hospital, comparing syndromic management (April-August 2024) with CT/NG POCT-guided management (September 2024-January 2025). Adults living with HIV presenting with symptoms suggestive of an STI were included. Overtreatment in the pre-intervention phase was estimated by comparing antibiotic prescribing with the expected number of CT/NG infections based on positivity observed during the intervention phase. Results: A total of 404 participants were included (203 pre-intervention, 201 intervention). During the intervention phase, CT and/or NG were detected in 14 individuals (7.0%). Median test turnaround time was 95 minutes, enabling same-day treatment in 93% of positive cases. Antibiotic prescribing decreased from 99.0% to 11.4% following POCT implementation (P < 0.001), corresponding to an absolute reduction of 87.6 percentage points. Estimated overtreatment declined from 30.0% to 5.0% for NG and from 74.9% to 6.0% for CT (both P < 0.001). Conclusions: Implementation of CT/NG POCT in routine HIV care was associated with a marked reduction in antibiotic prescribing and estimated overtreatment for presumed STIs. These findings support the potential of POCT-guided, aetiology-based STI management to reduce unnecessary antimicrobial exposure in settings where syndromic management remains standard practice.

Introduction: Following a large chikungunya outbreak during 2006 to 2008, Sri Lanka did not report any outbreaks for a 16 year period until end of 2008, possibly due to population immunity. Therefore, understanding baseline immunity prior to outbreaks is crucial to inform implementation of vaccine strategies. Methods: We assessed the age stratified seroprevalence for chikungunya in an urban (n=816) and a semi urban (n=380) community in Colombo, Sri Lanka, from September to November 2024, prior to the commencement of the large chikungunya outbreak, in December 2024. Sociodemographic, socioeconomic and clinical data were collected and chikungunya specific IgG measured in serum samples. Results: Of 1196 participants, 410 (34.3%) were chikungunya IgG seropositive. Seroprevalence was significantly higher in urban populations compared with semi urban populations (39.6% vs 22.9%; p<0.001) and increased significantly with age in urban areas but not in semi-urban areas. Living in an urban area was the strongest independent risk factor of chikungunya seropositivity (aOR 7.48, 95% CI 4.05 to 13.81; p<0.001), consistent with the higher population density, poor housing conditions and overcrowding observed in that setting. The use of mosquito nets was independently associated with reduced risk of seropositivity (aOR 0.50, 95% CI 0.27 to 0.93; p=0.029). Almost no individuals aged <16 years had evidence of prior infection (0.55%), indicating minimal transmission in the preceding 16 years. In the urban cohort, seropositivity was significantly associated with diabetes, central obesity, overweight, and hypertension. Conclusions: There appears to have been minimal chikungunya transmission in the 16 years preceding the 2024 outbreak, with a large population susceptible to chikungunya. Higher seroprevalence in urban populations highlights the role of population density, overcrowding, and housing conditions as key drivers of transmission.

Background: Cervical cancer remains a major public health challenge among women living with HIV (WLWH) in sub-Saharan Africa, where screening coverage remains suboptimal despite opportunities for integration within HIV care programs. Visual inspection with acetic acid (VIA) has been widely used as a low-cost screening approach in resource-limited settings. Methods: This cross-sectional analysis utilized prospectively collected data from Project CN001 at the Coptic Hope Center for Infectious Diseases in Nairobi, Kenya, a CASCADE Clinical Trials Network site. WLWH aged 25-49 years receiving routine HIV care and undergoing VIA screening between March 11, 2025, and January 16, 2026, were included. Data from the REDCap and Kenya's electronic medical record system (KenyaEMR) captured sociodemographic characteristics, HIV clinical factors, VIA results, and cervical transformation zone (TZ) classification. Results: Among 857 WLWH screened with VIA, the median age was 40 years (interquartile ranges [IQR]: 34-45), and 77.2% reported a prior history of cervical cancer screening. VIA positivity was 7.4% (63/857) and was higher in women with TZ1/TZ2 than in those with TZ3. VIA positivity was also associated with higher HIV viral load, shorter time since HIV diagnosis, no cervical screening history, and younger age at screening. The proportion of women classified as TZ3 increased with age, from 39.5% among women aged 25-29 years to 67.7% among those aged 45-49 years, while the proportion classified as TZ1 decreased with increasing age. Conclusion: Integrated screening at this urban U.S. President's Emergency Plan for AIDS Relief (PEPFAR) and CASCADE-supported HIV clinic demonstrates the feasibility of integrated cervical cancer screening programs for WLWH. Age-related TZ3 predominance and VIA limitations for older women highlight the need for refined screening strategies and continued electronic platform utilization for program monitoring to support cervical cancer elimination targets.

Background Social contact surveys, which measure who-contacts-whom, are widely used to inform infectious disease transmission models and estimate the reproduction number (R), a key metric for assessing epidemic risk. Despite their widespread use, sample size calculations are not routinely performed. Aims To assess the impact of sample size on estimates of R and determine a practical target sample size for social contact surveys used in epidemic modelling. Methods We conducted a review of social contact surveys (2008-2025) to characterise current practice. We characterised the impact of survey size on epidemic metrics using two social contact surveys, the UK Social Contact Survey and POLYMOD (Europe) and two methods. For each dataset and approach, we generated repeated subsamples and calculated the resulting reproduction numbers, characterised their distributions and measured uncertainty. Results We identified 107 unique social contact surveys from 57 studies. Sample sizes ranged from 30 to more than 10,000 participants, with a median of 1,438. One quarter of surveys contained fewer than 1,000 participants. From our simulations, we find that sample sizes below 200 individuals can result in highly variability reproduction numbers. Increasing sample size increases precision, and the most meaningful gains are up to 1,300 individuals. Increasing sample sizes over 3,000 individuals leads to smaller gains. Conclusions A minimum sample size of approximately 1,200-1,300 participants appears sufficient for general-purpose use. These findings support the inclusion of sample size considerations in the design, reporting and interpretation of social contact surveys used for epidemic intelligence and public health decision-making.

BackgroundART effectively suppresses HIV replication and restores CD4+ T cells; however, long-lived HIV latent reservoirs enable viral persistence. Tuberculosis (TB) co-infection further impacts HIV latency and enhances viral replication. Given the high prevalence of latent TB infection (LTBI) in TB-endemic settings, understanding its impact on HIV biology is critical. Our study aims to investigate the influence of TB co-infection on HIV reservoir dynamics, viral diversity, and drug resistance mutations in ART-naive individuals. MethodologySamples from 90 ART-naive HIV-1C individuals, stratified based on IGRA and TB diagnosis, were used in this study. Plasma and PBMCs were isolated for viral RNA and DNA extraction respectively. Total proviral DNA was quantified using gag PCR. Full-length env and pol genes were amplified, purified and sequenced using ONT and Illumina platforms. Pol sequences were subjected to Drug Resistance Mutation (DRM) analysis via Stanford HIVdb with a minimum threshold mutation frequency of [&ge;]10%. Full length env sequences were used for phylogenetic analysis by aligning with Indian Subtype C reference sequence and phylogenetic tree was generated using ggplot2. ResultProviral load analysis showed no significant differences across HIV+LTBI-, HIV+LTBI+, and HIV+TB+ groups, although a trend toward higher levels was observed in HIV+TB+ individuals. Correlation analysis revealed distinct immune associations, with HIV+LTBI+ individuals showing positive correlations with activation and PD-1 expression. Longitudinal analysis of proviral loads demonstrated a modest decline in proviral load post-ART but remained persistent for up to 18-20 months following initiation of ART accompanied by low level ongoing viral replication. DRM analysis revealed a 33% prevalence in ART-naive individuals, with higher occurrence in HIV+LTBI+ group. Of the identified DRMs, 38% (5/13) and 71% (5/7) in sequences obtained from PBMC and plasma respectively were attributed to polymorphic mutations associated with Integrase strand transfer inhibitors (INSTIs). DRMs within plasma and PBMC derived viruses showed high concordance. Phylogenetic analysis of env sequences indicated overlapping viral populations between the 3 groups, with greater diversity in PBMCs compared to plasma. ConclusionThe study highlights that HIV reservoir dynamics, drug resistance, and viral diversity are significantly influenced by TB co-infection. While proviral loads were comparable, LTBI-associated immune activation and granuloma niches may have driven viral diversification and DRM emergence. High concordance between compartments and presence of transmitted resistance underscore the need for baseline screening, multi-compartment analysis, and sustained surveillance.

Background: HIV/AIDS remains a major public health challenge in Tanzania, where viral load suppression among adults on ART stands at 78% and HVL testing uptake among eligible patients is approximately 22%. Since the introduction of the National HVL Testing Guideline in 2015, little has been done to systematically evaluate its implementation. Objective: To evaluate adherence to the National HVL Testing Guideline across CTC clinics in Dar es Salaam Region, covering ART monitoring, documentation, turnaround time, and factors affecting implementation. Methods: A cross-sectional study was conducted in 2021 across 15 public health facilities with CTC clinics in all five Dar es Salaam districts. A total of 330 PLHIV on ART for more than six months were selected through systematic random sampling with proportional to size allocation, and 45 healthcare providers through convenient sampling. Data were collected via abstraction forms and self-administered questionnaires, and analysed using SPSS Version 23 with descriptive statistics, bivariate analysis, and binary logistic regression. Results: Only 25.1% of patients had their first HVL sample taken at six months as per guideline, with 68.8% delayed beyond six months. Second and third samples were similarly delayed. MoHCDGEC sample tracking forms were absent in 96.7% of facilities and incomplete in 99.1%, and no facility captured specimen acceptance or rejection as site feedback. Turnaround time exceeded the 14-day guideline threshold in 64.5%, 66.7%, and 69.4% of first, second, and third results respectively. Patient negligence (AOR=9.84; 95% CI: 1.83-52.77) and storage (AOR=5.72; 95% CI: 0.94-35.0) were independently associated with guideline adherence. Conclusion: Adherence to the National HVL Testing Guideline in Dar es Salaam is suboptimal across testing timelines, documentation, and turnaround time, with patient negligence and storage capacity as significant determinants. Targeted interventions are needed to strengthen patient education, improve storage infrastructure, enhance documentation systems, and support providers in adhering to guideline-specified timelines.

Background: Metronidazole (MTZ) is a first-line antibiotic for several enteric infections. Its use is common in low-income countries, where most primary-care consultations are conducted by nurses. However, increasing resistance among some enteric pathogens is a growing concern. Using WHO guidelines, we conducted a register-based cross-sectional study to assess MTZ prescribing practices and their determinants in public and private primary healthcare facilities in South Benin. Methods: We performed a register-based cross-sectional study covering the year 2020 in 11 primary healthcare facilities (5 public and 6 private) in Abomey-Calavi, South Benin, following WHO recommendations. In total, 200 visits per facility were selected using systematic random sampling. The primary outcome was the prevalence of MTZ prescription. Determinants of MTZ prescription were identified using multivariable logistic regression analysis. Results: In total, 2,200 medical visits were analyzed. The median age of patients was 19 years, and 57% were female. Antimalarials were prescribed in 52% of visits. Antibacterial agents were prescribed in the majority of visits, with MTZ being the second most frequently prescribed antibiotic (18%), after aminopenicillins (27%). In multivariable analysis, digestive symptoms (adjusted odds ratio [aOR], 8.65; 95% confidence interval [CI], 6.49-11.6), genitourinary symptoms (aOR, 6.84; 95% CI, 3.18-15.0), and skin lesions (aOR, 2.39; 95% CI, 1.58-3.60) were independently associated with increased odds of MTZ prescription. In contrast, fever (aOR, 0.66; 95% CI, 0.49-0.87), respiratory symptoms (aOR, 0.44; 95% CI, 0.26-0.71), and malaria (aOR, 0.21; 95% CI, 0.15-0.28) were associated with decreased odds. Visits in the private sector were also associated with higher odds of MTZ prescription compared with the public sector (aOR, 2.31; 95% CI, 1.78-3.02). Conclusion: MTZ is the second most commonly prescribed antibiotic in primary care in the study area, with its use largely driven by digestive symptoms. Further studies are needed to assess the appropriateness of this prescription. Additionally, research is warranted to understand better the determinants of higher antimicrobial prescribing in the private healthcare sector.

BackgroundTuberculosis (TB) remains a leading cause of morbidity and mortality among people living with HIV (PLHIV), who face a 12-fold higher risk of active TB reactivation than HIV-negative individuals. TB preventive therapy (TPT) is an effective intervention, yet TB/HIV co-infection persists at 40-45%, raising questions about the durability of a single course of TPT. This study assessed the time from TPT completion to TB diagnosis and predictors of early TB reactivation. MethodsWe conducted a retrospective case-only cohort study using routine data from Ugandas electronic medical record system, TB registers, and patient files at three TASO Centres of Excellence (Soroti, Mbale, Tororo). PLHIV on antiretroviral therapy (ART) diagnosed with TB after completing TPT between 2022-2024 were included. Participant characteristics and time to TB diagnosis were summarised descriptively; predictors of early TB were identified using logistic regression. ResultsAmong 670 participants, most were female (464, 69.3%) with mean age 51.6 years (SD 14.5). Newly diagnosed TB accounted for 638 (95.2%), including bacteriologically confirmed pulmonary TB (535, 79.9%), clinically diagnosed TB (123, 18.4%), and extrapulmonary TB (12, 1.8%). Overall, 548 (82.8%) participants were virally suppressed, with most on Dolutegravir-based regimens (641, 95.7%). Early TB occurred in 144 (21.5%), with average time to diagnosis 2.6 years. Multivariable analysis showed care at TASO Soroti was protective (aOR = 0.104, p < 0.001), while clinically diagnosed TB (aOR = 1.91, p = 0.007), shorter ART duration (<5 years: aOR = 3.07, p = 0.001; 5-10 years: aOR = 1.74, p = 0.018), and viral suppression (aOR = 1.87, p = 0.014) increased odds of early TB. ConclusionsTB can occur soon after TPT completion, with one in five PLHIV developing early disease particularly those with shorter ART duration despite viral suppression. Strengthening TB screening, continuous monitoring, and repeat TPT for high-risk groups may improve prevention.

Background: In sub-Saharan Africa where both tuberculosis (TB) and HIV are prevalent, empiric TB treatment in people living with HIV (PLHIV) persists due to limited sensitivity of sputum-based TB tests. We evaluated mortality among molecular test-negative presumptive TB adult PLHIV in a population where the majority are or have been on antiretroviral therapy (ART), comparing mortality between those who received empiric TB treatment and those who did not. Materials and Methods: From November 2017 to December 2020, Xpert-negative presumptive TB adult PLHIV were recruited at Mulago Referral Hospital and Kisenyi Health Centre-IV in Kampala, Uganda. Clinical data including TB symptoms, chest X-ray, and empiric TB treatment decision were collected. Laboratory investigations included CD4 cell count, serum cryptococcal antigen (CrAg), urine TB-lipoarabinomannan (TB-LAM), microbiological blood cultures, and sputum mycobacterial growth indicator tube (MGIT) cultures. Participants were followed monthly for 12 months to ascertain vital status. Results: Overall, 300 participants were enrolled; 61.3% inpatients, 55.7% female, median age 37 (IQR 29-45) years, 82.3% on ART, median CD4 206 cells/mm3 (IQR 36-507). Of the 300 participants, 68 (22.7%) received empiric TB treatment, of which 53 (77.9%) were inpatients. 12-month mortality was 31.0% (93/300); 91.4% among inpatients, 72% within three months post-enrolment. Mortality was higher among those who received empiric TB treatment (51.5 vs. 30.2 per 1,000 person-months; p=0.013) compared to those who did not. TB cultures were positive in 5.0% (15/300), of whom seven (46.7%) were also TB-LAM positive. CrAg was positive in 12.3% and 3.7% had positive blood culture. Conclusion: We found high mortality among Xpert-negative PLHIV, particularly those who received empiric TB treatment, despite high ART coverage. Cryptococcal antigenemia and bacteremia were not uncommon. In presence of negative Xpert results in PLHIV, clinicians should perform extensive laboratory evaluations to identify possible comorbidities or alternative non-TB diagnosis.

Background Use of oral cholera vaccine (OCV) is globally recommended as a public health response to cholera outbreaks, alongside water, sanitation and hygiene (WASH) interventions. Estimating vaccine effectiveness during emergencies in low-and middle-income countries is challenging because vaccination campaigns are often implemented over short time frames, while individual-level data are frequently incomplete due to constraints in infrastructure, resources and data systems. There is a need for pragmatic approaches that can generate timely, policy-relevant evidence using routinely collected data. Methods We analysed routine surveillance data from a large 2022-2023 cholera outbreak in Blantyre District, Malawi. The EpiEstim framework was used to generate estimates of the time-varying reproduction number (Rt) from line-listed case data. We modelled changes in Rt as a function of cumulative OCV coverage using a log-linear framework and propagated uncertainty through posterior sampling. Lagged WASH exposure variables were incorporated in the model to generate adjusted vaccine effectiveness estimates and to explore potential interaction effects. Sensitivity analyses assessed robustness to alternative lag structures. Findings The Blantyre outbreak was characterised by an initial period of low-level transmission followed by a sharp increase in cases from late November 2022, after which transmission declined steadily through April 2023. This decline coincided with the implementation of a reactive OCV campaign. The majority of the cases were among middle-aged men living in urban Blantyre. The unadjusted vaccine-associated reduction in transmission was estimated at 53.52% (95% credible interval (CrI):42.5-64.1%). After adjusting for a 7-day rolling average WASH activity, total vaccine effectiveness increased to 62.1% (95% CrI: 49.3-74.9%). Sensitivity analyses using alternative lag structures for WASH exposure produced comparable adjusted estimates. Interpretation Implementation of OCV contributed to a substantial reduction in cholera transmission during the outbreak. This study demonstrates a feasible approach for estimating vaccine-attributable impact whilst accounting for public health and social measures, such as WASH interventions. The methods described will be useful in outbreaks where classical observational designs are not possible, providing actionable evidence to policy makers for outbreak response in resource-limited settings.

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.

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.

Abstract Background Anemia is a condition characterized by nutritional deficiencies and blood disorders, predominantly affecting children aged 6 to 59 months and women of reproductive age, especially in low and middle-income countries. In Zambia, anemia is a public health problem. This study aims to assess the spatial patterns and determine factors associated with anemia severity in Zambia over six years (2018 to 2024). Method The study included a total of 19,362 WRA from the two waves of the ZDHS, 2018 and 2024. The ZDHS is a periodic national survey that uses multistage sampling. We adopted an analytical cross-sectional design, and the three-level multivariable ordinal logistic regression model was used to identify variables (individual, household, and community level) associated with anemia severity. Global Morans I, Local Morans I, and Getis-Ord Gi* statistics were used to determine the hotspots and spatial patterns, while spatial scan statistics were used to detect primary and secondary clusters and their distribution over the two cycles. Results The prevalence of anemia among women of reproductive age in Zambia was 31.0% (n=3,946) and 30.4% (n=2,015) in 2018 and 2024, respectively. The factors associated with higher odds of anemia severity were HIV status (HIV-positive: AOR=2.63, 95% CI:2.25,3.09), pregnancy (AOR=1.96, 95% CI:1.67,2.31), and rural residency (AOR=1.21, 95% CI:1.08,1.35). While being in a union was protective compared to never being in a union (AOR=0.66, 95% CI:0.57,0.77), not having financial barriers for medical assistance was equally protective. Spatial analysis showed geographic disparities and a non-random distribution of anemia (Global Morans I, 2018: I=0.147, p<0.001; 2024: I=0.130, p<0.001). the Hotspot analysis depicted an expansion of high-risk areas Western in 2018 to the North-Western and Luapula in 2024. Spatial scan analysis identified the south-west region (Western, Southern and North-Western) as the significant primary cluster of anemia consistently for both waves.