Lukas Fenner

Introduction: Despite global progress in tuberculosis (TB) control, treatment outcomes remain suboptimal, particularly in high-burden settings and among people with HIV or drug-resistant TB. Identifying predictors of unsuccessful treatment is essential to improve TB care and policy. Methods: We evaluated TB treatment outcomes and patient characteristics associated with unsuccessful outcomes in five cohorts of the International epidemiology database to evaluate AIDS (IeDEA); Center for Infectious Disease Research, Zambia; Chiure health center, Mozambique; Martin Preuss Center, Lighthouse clinic, Malawi; Masvingo health center Zimbabwe; and Themba Lethu clinic, Hellen Joseph hospital, South Africa. We included all patients with TB aged ≥ 15 years starting TB treatment and assessed their treatment outcomes in association with sociodemographic and clinical characteristics using multivariable mixed-effects models. Unsuccessful outcomes were defined as death, loss to follow-up and treatment failure. Results: Among 1438 people with TB, median age was 39 years, 67% males, 40% with HIV, and 4% with MDR-TB; 1151 (80%) treatment outcomes were successful (606 cured and 545 completed treatment), 221 (15%) unsuccessful (89 deaths, 129 loss to follow-up and 3 treatment failures), and 66 (5%) other (49 unknown and 17 transfer-outs). Unsuccessful outcomes were more probable among people with multidrug-resistant TB (MDR-TB) and among participants without formal education. Risk of death was lower for people with bacteriologically confirmed TB (adjusted odds ratio (aOR) 0.5, 95%-credible interval [CI] 0.25-0.80), those with a secondary or higher education (aOR 0.3, 95%-CI 0.13-0.69) and BMI ≥18 kg/m² (aOR 0.6, 95%-CI 0.36-0.99). MDR-TB was associated with an increase (aOR 2.4 95%-CI 1.17-4.97) and primary and secondary or higher education with a decrease in loss to follow-up (aOR 0.3, 95%-CI 0.14-0.89 and aOR 0.3, 95%-CI 0.11-0.67, respectively). Conclusions: TB treatment outcomes fell short of the targets set by the World Health Organization of <10% unsuccessful outcomes, indicating a critical need for enhanced management strategies. Tackling loss to follow-up is crucial, especially among MDR-TB patients, including stronger retention activities and improved diagnostic capacities.

Introduction: Towards the ‘End TB Strategy’ targets, the WHO recommends the provision of tuberculosis (TB) preventive therapy (TPT) for high-risk groups including people living with HIV (PLWH). 3 years after the release of the updated 2020 WHO guidelines, we investigated the implementation of TPT services at HIV clinics in low-income and middle-income countries (LMICs), focusing on TB screening, populations eligible for TPT and available TPT regimens. Methods: In 2023, we surveyed HIV care clinics in the International Epidemiology Databases to Evaluate AIDS consortium in Africa, the Asia-Pacific and Latin America and the Caribbean. We used descriptive statistics to summarise TPT implementation according to WHO guidelines and multivariable logistic regression models to estimate associations with clinic characteristics. Results: Of 172 HIV clinics included, 142 (83%) were in Africa, 22 (13%) in the Asia-Pacific and 8 (5%) in Latin America; 108 (63%) were located in urban areas. After ruling out active TB, TPT was reportedly offered to PLWH (122 clinics, 71%), household contacts of individuals with active TB (120 clinics, 70%) and other high-risk populations. TPT for PLWH was more frequently available in clinics in lower-income and low-middle-income countries, in high TB burden countries, and in district hospitals compared with other facility types. Clinics reported use of isoniazid-based (160 clinics, 93%) and shorter rifamycin-based (129 clinics, 75%) TPT regimens. Reported barriers to TPT initiation included patient refusal at 71 (41%) and drug shortages at 67 (39%) clinics. Conclusions: TPT was available at most HIV care clinics in LMICs but further efforts are needed to reinforce WHO recommendations and ensure that TPT is consistently accessible to people at higher risk of developing active TB, especially PLWH.

Background: Hospitals in high-burden tuberculosis (TB) settings are important sites of Mycobacterium tuberculosis ( Mtb) transmission, yet the impact of infection prevention and control (IPC) measures targeting crowding is poorly understood. We assessed the effects of simple interventions to reduce spatial clustering and airborne transmission in a Zambian hospital. Methods and findings: From June to August 2024, we prospectively collected clinical data on presumptive (symptom-based screening) and confirmed (Xpert-positive, chest X-ray) TB patients, indoor CO ₂ levels, bioaerosol samples, and continuous person movements (optical sensors) in the hospital’s main waiting hall. Airborne Mtb DNA was detected using hourly cyclonic bioaerosol sampling. Using a spatiotemporal Wells–Riley model integrating ventilation, proximity between visitors, and movement patterns, we estimated Mtb transmission risk under routine conditions and during two IPC interventions: (1) an optimised waiting-area layout with physical distancing measures; and (2) an added one-way patient flow system. During 52 days, 668 presumptive and 45 confirmed TB patients visited the hospital, and 671 840 person movements were recorded. Despite excellent natural ventilation (median CO ₂ 455 ppm; 8.0 air changes per hour), airborne Mtb was detected on six days. The first intervention reduced spatial clustering by an estimated 24% (95% credible interval [CrI] 13–32) and the second by 13% (95% CrI 1–23). The interventions lowered Mtb transmission risk by an estimated 39% (95% CrI 29–48) and 21% (95% CrI 9–32), respectively. Over the four weeks of implementation, they collectively averted an estimated 16 (95% CrI 8–26) infections. Conclusions: In this high-burden, well-ventilated hospital, short-range exposure remained a driver of airborne Mtb transmission. Simple, low-cost operational changes to reduce clustering substantially decreased proximity-driven transmission risk. Integrating proximity-focused strategies can meaningfully strengthen IPC in resource-limited healthcare settings.

Background: High levels of multidrug and rifampicin resistant tuberculosis (MDR/RR-TB) are a global concern, although they have declined over the last decade. TB patients are at increased risk of acquired rifampicin resistance if they have HIV coinfection, especially at low CD4 counts, but this dynamic has not previously been modelled. Methods: We extended a previously-developed model that simulates HIV and TB in South African adults, to include the acquisition and transmission of rifampicin resistance. In line with systematic reviews, the risk of acquiring RR with TB treatment is modelled as being negatively associated with patients’ CD4 counts. We allow for temporal changes in drug susceptibility testing, both before treatment initiation and at treatment failure, as well as other changes in TB prevention and treatment. The model is calibrated to data from national TB drug-resistance surveys, and recorded numbers of MDR/RR-TB laboratory diagnoses and patients initiating second-line TB treatment, using a Bayesian approach. Results: The model estimates that the proportion of South African TB patients with rifampicin resistance at diagnosis increased from 2.0% (95% CI: 1.7-2.3%) in 1986 to 5.9% (5.2-6.9%) in 2013, in line with survey data. In the absence of HIV, the prevalence of MDR/RR-TB would have increased to 4.1% (2.7-5.1%) in 2013, suggesting a third of rifampicin resistance in 2013 was attributable to HIV. In the absence of antiretroviral treatment (ART), the prevalence of rifampicin resistance would have been higher (6.5% [5.6-7.6%] in 2013, rising to 6.9% [5.7-8.2%] in 2019). ART reduced the prevalence of rifampicin resistance in 2019 by 17%. Conclusions: In countries with high HIV prevalence, HIV may be a major driver of rifampicin resistance in people with TB. ART programmes have the potential to reduce the emergence of resistance substantially.

Close-proximity interactions are considered a key risk factor for respiratory virus transmission, but their importance relative to shared space and air quality remains unclear. We conducted a six-week longitudinal study in a Swiss secondary school (67 students, aged 14–15). We detected 87 infections in saliva samples and recorded absences to identify plausible transmissions, excluding implausible ones through genomic analysis. Time in close proximity (within 1.5 metres) was measured using wearable sensors and air quality via CO ₂ monitors. Students spent 21.2 minutes per day in close proximity (interquartile range 7.8–44.2) and 5.3 hours in shared classrooms (IQR 3.8–6.2), during which air quality was suboptimal for 1.9 hours (IQR 1.2–3.0). Using pairwise survival models, we found that transmission was more likely within than between classes. Close proximity was modestly associated with higher transmission risk overall (rate ratio 1.16 per doubling daily time, 95%-CI 1.01–1.33), while time in shared classrooms (RR 3.17, 95%-CI 1.96–5.17) and suboptimal air quality (RR 1.90 95%-CI 1.23–2.94) also predicted within-class risk. Prolonged exposure in shared, poorly ventilated spaces, which potentially includes several infectious sources, drives respiratory virus transmission more than close contact.

Background: Viral respiratory infections contribute to sick days in school children. We monitored respiratory infections, absences, and symptoms in a Swiss school. Methods: Serial saliva sampling (three per week) and daily recording of absences and symptoms over 6 weeks during the winter of 2023/24 in four Swiss school classes (age 14–15). Results: We analyzed 1047 samples of 67/84 (80%) participants, identifying 87 infection episodes across eight viruses: 28 (32%) human rhinovirus, 18 (21%) influenza A/B, 11 (13%) respiratory syncytial virus, 14 (16%) human coronaviruses, 6 (7%) parainfluenza virus, and 5 (6%) influenza B; SARS‐CoV‐2 was not detected. Spatiotemporal trends revealed seasonal epidemic trends and evidence of transmission within classes. Viral loads (interquartile range 29.5–36.9 Ct) and duration of detection (modeled range 3.2–5.3 days) were similar for all viruses. School absences were more likely temporally associated with influenza B infections than with other respiratory viral infections (> 99% vs. 38%, p = 0.005), and the absences tended to be longer (average 4.2 vs. 2.2 days). Symptoms varied depending on the pathogen detected, with absences temporally associated with human rhinovirus and parainfluenza virus infections commonly involving runny nose and sore throat, while absences associated with influenza infections often involved fever. Conclusions: Class‐specific distribution patterns suggest a major contribution of within‐class to overall respiratory virus transmission. Respiratory viruses showed certain distinct profiles in relation to school absences and symptoms. This highlights the importance of infection control measures, including vaccination, and virus‐specific monitoring to better understand transmission dynamics in schools.

Close-proximity interactions are considered a key risk factor for respiratory virus transmission, but their importance relative to shared space and air quality remains unclear. We conducted a six-week longitudinal study in a Swiss secondary school (67 students, aged 14–15). We detected 87 infections in saliva samples and recorded absences to identify plausible transmissions, excluding implausible ones through genomic analysis. Time in close proximity (within 1.5 metres) was measured using wearable sensors and air quality via CO₂ monitors. Students spent 21.2 minutes per day in close proximity (interquartile range 7.8–44.2) and 5.3 hours in shared classrooms (IQR 3.8–6.2), during which air quality was suboptimal for 1.9 hours (IQR 1.2–3.0). Using pairwise survival models, we found that transmission was more likely within than between classes. Close proximity was modestly associated with higher transmission risk overall (rate ratio 1.16 per doubling daily time, 95%-CI 1.01–1.33), while time in shared classrooms (RR 8.96, 95%-CI 4.85–16.88) and suboptimal air quality (RR 5.59 95%-CI 3.25–9.83) also predicted within-class risk. Prolonged exposure in shared, poorly ventilated spaces drives respiratory virus transmission more than close contact. Supplementary Information Supplementary methods and results for the genetic and pairwise survival analysis as well as genomic sequence accession codes.

Background: Tuberculosis (TB) affects people’s quality of life (QoL). We prospectively monitored physical and mental health-related QoL over time in people with TB in the Southern African region with a high HIV and TB burden. Methods: Adults aged ≥ 15 years with pulmonary TB were enrolled in five cohorts in Malawi, Mozambique, South Africa, Zambia, and Zimbabwe from October 2022 to September 2024. We assessed six QoL outcomes using validated instruments at the start (baseline), end of treatment, and 6 months post-treatment: symptoms of depression (PHQ-9), mental and physical health (SF-12 mental, SF12-MC, SF-12 physical component, SF12-PC), physical fitness (6-Minute Walk Test, 6MWT; 1-min Sit-To-Stand Test, STST), and respiratory health (Saint-George-Respiratory-Questionnaire, SGRQ). Missing QoL scores were imputed with multivariate imputation by chained equations. We compared the proportion of participants with impaired QoL, defining impairment based on outcome-specific cut-off values. We also estimated changes in QoL scores and examined their associations with baseline characteristics using Bayesian multivariable regression models. Results: We included 1438 participants with a median follow-up of 344 days (interquartile range [IQR] 183–373). The median age was 39 years (IQR 30–50); 67% were male, and 39% living with HIV. At baseline, 49% had symptoms of depression, 73% had impaired mental health and 92% impaired physical health-related QoL, 68–74% had reduced physical fitness (68%: 6MWT, 74%: STST), and 78% impaired respiratory health. All QoL outcomes improved by the end of treatment, notably depressive symptoms (48% to 5%), mental health-related QoL (73% to 28%), and respiratory health (78% to 11%). Most QoL impairments continued to decrease post-treatment, especially physical and respiratory health; depressive symptoms remained below 5%. Across QoL domains and study visits, better outcomes were associated with age < 30 (83% probability), and worse outcomes with female gender (86%) and a prior TB history (89%). Living with HIV and alcohol drinking were associated with worse QoL only at baseline (88% and 87%). Conclusions: TB negatively impacts QoL across physical, mental, and social domains, including post-treatment. The study highlights the need for integrated mental and physical healthcare and rehabilitation during TB treatment and beyond, especially for high-risk populations, to address the long-term impact of TB on QoL.

Background: In our research, we investigated student state and habitual well‐being in school during and in the aftermath of the COVID‐19 pandemic (after schools reopened) and analyzed their associations to measures in schools aimed at preventing ongoing infectious diseases.Methods and Measures: We conducted two interventional field studies in Swiss lower secondary education (Grades 8 and 9, students aged 13–15 years) to compare trait and state well‐being during three different study conditions: no infection control measure, facial mask mandates, and the temporary installation of portable air cleaners in classrooms.Results: In Study 1, student enjoyment in school significantly decreased over time and their physical complaints increased. Students reported significantly higher negative activation with masks and air filters when compared to no infectious control measures. However, their negative activation significantly decreased over time with the mask, whereas it increased without measures. In Study 2, student worries in school significantly decreased over time. In one class, students reported an increase in positive activation and valence without air cleaners. In the other class, positive activation and concentration increased with air cleaners and negative activation decreased without air filters.Implications for School Health and Conclusions: Results suggest that infection control measures in school can have short term positive and negative effects on students' self‐reported state well‐being while not significantly impeding student's habitual well‐being. For school health, students might benefit psychologically in times of crisis when they understand the implementation of measures as actions of care and safety.