Epidemiology and Infection

Background: Tuberculosis recurrence accounts for a substantial proportion of incident tuberculosis in many settings. Distinguishing between its mechanisms can inform public health interventions for prevention. Methods: We conducted a retrospective study of individuals with multiple culture-confirmed TB episodes and available sequential isolates from 2012 to 2023 in Dourados and Campo Grande, Mato Grosso do Sul state, Brazil. Patients were classified as having recurrent TB after treatment completion or retreatment following non-curative outcomes. Whole-genome sequencing was used to assess pairwise genetic distances between isolates, classifying relapse or persistent infection ([≤]12 single-nucleotide polymorphisms [SNPs]) versus reinfection or retreatment with reinfection (>12 SNPs). Results: Among 9,293 individuals with TB, 772 recurrent or retreatment episodes were identified. Paired isolates from 82 individuals were available for comparisons. Among individuals who completed treatment, reinfection accounted for 74.1% (40/54) of recurrent episodes, while 25.9% (14/54) were classified as relapse. Among individuals with non-curative outcomes, persistent infection (53.6%, 15/28) and retreatment with reinfection (46.4%, 13/28) occurred at similar frequencies. Persistent infection and relapse occurred earlier after the initial episode, whereas reinfection and retreatment with reinfection predominated after two years. Incarceration history was strongly associated with reinfection after treatment completion (92.5%, p=0.012) and after non-curative outcomes (76.9%, p=0.016). Conclusions: In this high-burden setting, reinfection drives TB recurrence among individuals who complete treatment, particularly at longer intervals after initial disease, reflecting sustained exposure risk. Relapse and persistent infection remain clinically important, especially following non-curative outcomes. These findings underscore the need for integrated strategies combining adherence support to prevent treatment-related recurrence with interventions to reduce transmission, particularly in high-risk settings.

Background In northern Thailand, scrub typhus primarily affects rural and hill tribe communities, yet awareness is low. In 2020 we trained community health volunteers (CHVs) to raise awareness in their communities using a train-the-trainer approach. CHV knowledge rose dramatically. However, we did not assess the effectiveness in community members and our strategy relied heavily on CHVs, who have limited availability. Methods In a second phase, object of this manuscript and conducted in 2022-2023, after training CHVs we measured the effectiveness in community members and compared in-person sessions carried out by CHVs with sessions using video or audio recordings only. All materials included key information about scrub typhus transmission, symptomatology, prevention, and management and had been developed following feedback from participants from the first round of activities in 2020. Effectiveness was evaluated using a questionnaire assessing scrub typhus knowledge. CHVs were also asked to rate the feasibility of suggested preventative measures. Results A total of 74 community members participated in six sessions. Knowledge of scrub typhus significantly improved post-training (median score increased from 2 to 6 out of 9, p<0.001) and audio and video recordings were as effective as in-person trainings. CHVs noted that some of the preventative measures recommended are difficult to put in practice such as wearing gloves, washing daily after work, avoiding kneeling and resting on the ground, and washing clothes daily. Conclusions Our findings support the use of locally adapted multimedia training for scrub typhus prevention, showing that scalable formats can be as effective as in-person ones. Further collaborative work with people at risk should refine preventative messages to improve feasibility and acceptance.

Objective: The study aimed to describe the challenges, best practices, and lessons learned during meningitis vaccination campaigns conducted in the context of COVID-19 in Cameroon in 2020. Results: During the prevention campaigns, 3,460 individuals were selected. All were tested before the campaign (100%). Eight cases were positive, representing a positivity rate of 0.23% (8/3,460). The campaign was carried out using a fixed strategy in health facilities and prisons and a fixed-temporary strategy in communities. Most health areas received sufficient quantities of COVID-19 equipment for some items and insufficient quantities for others. No screening was done during or after the campaign. The main difficulties encountered were compliance with social distancing and the continuous wearing of gowns. The challenges faced were the screening of actors and the use of personal protective equipment. Lessons learned: aspects related to COVID-19 impacted the speed of the campaign. Vaccination coverage ranged from 91% to 140% in prisons on the one hand, and from 35% to 112% in the health areas surrounding prisons on the other. The campaign in the context of COVID-19 was effective. Compliance with barrier measures was not optimal due to difficulties encountered with aspects such as social distancing, continuous wearing of gowns, screening of participants during and after the campaign, and insufficient personal protective equipment.

Scorpionism is a public health concern in warm regions, particularly affecting children under 10 years old. Timely treatment with antivenom, provided free by the Brazilian Unified Health System, at strategic care points (PEs) is crucial to prevent avoidable deaths. Our study focused on the Sao Paulo state (SP), which has the largest population in Brazil. The objectives were to adapt a network analysis method suited to SPs context; to assess the efficiency of the SP PE network coverage, considering the 90-minute response time; and to determine the ideal number of vials to be stored at each PE. After adapting the healthcare network analysis, we applied spatial coverage models to evaluate the adequacy of PE response times. We also estimated the demand for antivenom vials at each PE based on Notifiable Diseases Information System data from 2021 to 2023, which is currently limited to the state level. We identified 12 areas lacking coverage, of which only one was suitable for a new PE. The estimated serum requirements aligned with SP's current distributions. However, the estimation carried out according to the PEs has the advantage of reducing the risk of antivenom shortages, especially in emergencies, thus ensuring timely care to prevent avoidable deaths. Our adapted method and PE serum estimates can enhance the scorpion sting care system by supporting geographic planning and optimizing resource allocation. Moreover, these findings and methodologies have potential applicability to other Brazilian regions and warm countries facing similar challenges, contributing to improved access and outcomes for scorpionism victims.

Background India accounts for nearly one-fourth of the global tuberculosis (TB) burden. The country's progress towards elimination of TB is hindered by considerable heterogeneity in behavioural, social, and health system determinants, which influence transmission dynamics and care access. Evidence from the recent national TB prevalence survey showed that almost half of individuals with active disease were asymptomatic, underscoring the limitations of symptom -based case finding. Achieving the End TB targets will therefore require strategies that simultaneously address the substantial pool of individuals with undiagnosed, asymptomatic disease and those symptomatic individuals who do not seek care. Methods We developed a transmission model of TB that explicitly incorporates individuals with asymptomatic disease, and those who do not seek care. Model calibration was performed within a Bayesian framework using epidemiological and programmatic data for India. The calibrated model was then used to project the potential impact of intervention on TB incidence and mortality. Results Under the baseline scenario, the estimated TB incidence and mortality rates for 2024 were 180 (163-203) and 24 (18-31) per 100,000 population, respectively. Across all intervention scenarios targeting improved diagnosis, active case finding, nutrition support and their combination the reduction in incidence rate by 2030 ranged from 13% to 60% compared with 2025, while the corresponding decline in mortality rate ranged from 16% to 66%. Conclusion While individual interventions yield measurable reductions in TB incidence and mortality, but greater impact is achieved when implemented in combination reflecting the need for a comprehensive, multi-component response towards TB elimination.

Background During infectious disease outbreaks, characteristics of reported cases are routinely collected. These give information on becoming infected but not on infecting others. We assess whether linking infectees to infectors, together with their characteristics, can help understand transmission. Methods From the start of the COVID-19 pandemic in the Netherlands, reported cases were asked to identify their most probable infector in routine surveillance, enabling the linking of cases. We assess for the period 27 February 2020 - 11 April 2022 whether the infectees of these transmission pairs are representative of all reported cases, whether the transmission pairs yield verifiable estimates of epidemiological characteristics (here the serial interval), and whether they provide information on transmission that cannot be obtained otherwise. Results Of 8,003,008 reported cases, 678,482 (8.5%) could be linked to their most probable infector. These infectees were largely representative of the reported cases regarding age group, sex, and geographical location. The mean serial interval of 3.6 days (sd 3.4 days) from transmission pairs aligns with literature. Transmissions between age groups largely follow known contact patterns. Most transmissions in September 2021 occurred between persons who were not (fully) vaccinated, indicating the effectiveness of the vaccine, and relatively few between persons with different vaccination status, indicating assortative mixing in vaccination status. Conclusion Transmission pairs can be efficiently collected in routine surveillance, providing insight into disease transmission. The current post-pandemic period provides an excellent opportunity to adjust reporting systems for linking infectees to their most probable infector as preparation for future outbreaks.

BackgroundThe World Health Organization has developed several global template protocols for epidemiological investigations, including for household transmission investigations (HHTIs). These investigations facilitate rapid characterisation of novel or re-emerging respiratory pathogens and support evidence-based public health actions. Beyond technical readiness, community buy-in is central to the feasibility and acceptability of HHTIs. Research is needed to determine the perceived legitimacy among the community to inform local protocol adaptation and development of implementation plans that consider community attitudes and needs. MethodsIn 2025, we conducted a convenience survey of community members living in Victoria, Australia to explore: their understanding of emerging respiratory diseases; their willingness to take part in public health surveillance activities such as HHTIs; the acceptability of clinical and epidemiological data collection and respiratory/blood sample collection as main components of HHTIs, and; participant comfort towards including their companion animals in HHTIs. ResultsWe received 282 survey responses, of which 235 were included in the analysis dataset. Compared to the general Victorian population, our participants included a higher proportion of participants who reported being female, tertiary-educated, of Aboriginal and/or Torres Strait Islander heritage, born in Australia and speaking only English at home. Participants indicated overall high levels of comfort and acceptability towards participation in HHTIs, particularly in relation to clinical and epidemiological data collection, with lesser but still high levels of comfort with providing multiple respiratory specimens in a 14-day period. Participants were least comfortable with other specimens such as urine and blood. Involving companion animals in HHTIs was similarly acceptable as human-focused components. ConclusionsDespite our survey population being non-representative of the general Victorian population, our findings provide valuable descriptive insights into the acceptability of HHTIs in Victoria, Australia from which to benchmark future local and international surveys and community engagement activities.

ObjectiveHealthcare workers (HCWs) are at increased risk of COVID-19 infection and play a critical role in influencing public vaccine acceptance. This study aimed to assess vaccination coverage and identify the determinants of vaccine uptake among healthcare workers in Cameroon, in order to inform targeted strategies to strengthen immunization programs and improve epidemic preparedness. ResultsAmong 406 participants (75.6% female, 65.5% aged 30-44 years, 61.3% nurses), 42.4% were fully vaccinated against COVID-19, while only 4.7% had completed the cholera vaccine series. Coverage varied across districts, with Biyem-Assi (53.0%) and Odza (46.0%) recording the highest COVID-19 uptake, and Nkolndongo (11.5%) leading for cholera vaccination. Independent predictors of COVID-19 uptake included being a nurse (aOR = 3.96; 95% CI: 2.07-7.81; p = 0.001) and laboratory technician professions (aOR = 8.00; 95% CI: 1.38-69.8; p =0.032). For cholera vaccination, working in internal medicine wards (aOR=11.2; 95% CI: 1.04-120; p = 0.046) and being a nurse (aOR = 1.54; p = 0.001) emerged as significant predictors. Although 62.8% of HCWs perceived their work environment as high-risk, knowledge of recommended vaccines was limited, with only 18.7% aware of cholera vaccination recommendations. Strengthening vaccine education, improving accessibility, and reducing financial barriers could enhance vaccine acceptance among HCWs. These findings provide important insights for designing targeted immunization strategies in Cameroon and similar contexts.

Background: Incomplete childhood vaccination undermines individual and herd immunity and increases vulnerability to vaccine-preventable diseases. Understanding local determinants of vaccination adherence is essential for targeted interventions. This study assessed routine immunization completion and dropout patterns among children aged 0-15 months in Bayelsa State, Nigeria. Objectives: To determine vaccination completion rates, identify factors influencing adherence, analyze temporal patterns across immunization milestones, and provide evidence-based recommendations for improving coverage. Methods: A comparative longitudinal study was conducted from March 2023 to July 2024 across three Local Government Areas (LGAs), representing each senatorial district. A total of 369 mother-child pairs (123 per LGA) were enrolled. Data were obtained from health facility immunization registers and supplemented with semi-structured questionnaires. Children were followed through the 6th week, 10th week, 14th week, 9th month, and 15th month immunization visits. Completion rates were analyzed using descriptive statistics and chi-square tests. Ethical approval was obtained from the State Ministry of Health, and informed consent was obtained from all mothers. Results: Completion rates varied across LGAs, with the highest in LGA C (86.2%) and lowest in LGA B (61.0%). Phone-based reminders achieved the highest adherence, outperforming routine and home visit strategies. Progressive attrition was observed along the immunization schedule, with dropout exceeding completion by the 15th month. Principal reasons for non-completion included forgetfulness, travel, and caregiver busyness. Maternal age, education, and occupation significantly influenced adherence, indicating disparities across LGAs. Conclusion: Vaccination adherence is shaped by maternal characteristics and operational strategies. While early-stage coverage is high, attrition increases at later milestones, particularly in LGAs with lower resource engagement. Recommendations: Implement targeted phone-based reminders, milestone-specific outreach, and community engagement programs to reduce dropout, enhance timely completion, and strengthen childhood immunity.

Background/Objectives: Influenza infection is a major trigger of pneumonia and acute exacerbations among patients with chronic obstructive pulmonary disease (COPD). However, national laboratory-confirmed evidence on influenza vaccine effectiveness (VE) in this high-risk population remains limited. This study aimed to estimate the effectiveness of seasonal influenza vaccination against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.Methods: We conducted a nationwide retrospective test-negative design study using administrative healthcare data from the National Health Security Office linked with laboratory-confirmed influenza surveillance data between June 1, 2013, and May 31, 2025, covering twelve influenza seasons (2013-2024). COPD-related clinical episodes among patients aged [&ge;]40 years who presented with pneumonia or acute exacerbation of COPD and underwent RT-PCR testing for influenza were included. Multilevel Poisson regression models were used to estimate adjusted risk ratios (RRs), and VE was calculated as (1 - adjusted RR) x 100.Results: A total of 606,072 COPD-related clinical episodes were included, of which 192,224 (31.7%) were influenza-positive. The overall adjusted VE against influenza-associated pneumonia was 63.2% (95% CI: 62.5-64.0), while VE against influenza-associated COPD exacerbations was 67.0% (95% CI: 48.8-78.8). VE estimates were broadly similar across age groups and remained substantial across COPD severity strata. Although point estimates were numerically higher in severe and very severe COPD, subgroup differences should be interpreted cautiously.Conclusions: Seasonal influenza vaccination was associated with substantial protection against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.

Phylodynamics bridges the gap between epidemiology and pathogen genetic data by estimating epidemiological parameters from time-scaled pathogen phylogenies. Multi-type birth-death (MTBD) models are phylodynamic analogies of compartmental models in classical epidemiology. They serve to infer the average number of secondary infections R and the infection duration d. Moreover, more complex MTBD models add extra parameters, such as the average length of the incubation period or the proportion of superspreaders in the infected population. However, these additional parameters come at an important computational cost: Apart from the simplest, BD, model, MTBD models do not have a closed-form solution and require numerical methods for their likelihood computation. This leads to increased computational times and potential numerical errors. Therefore, the BD model remains the favorite researchers choice for real dataset analyses, and is often applied even in cases where more complex epidemiological aspects are present. We investigated, using simulations, how model misspecification influences inference of R and d in the phylodynamic framework. We showed that the use of models not accounting for various epidemiological aspects leads to bias. In particular the simplest, BD, estimator tends to underestimate R in the presence of super-spreading or incubation, which might be dangerous from the public health prospective. However, deep-learning-based estimators for complex models, which account for multiple epidemiological factors, perform well both on the data where those factors are present and where they are absent. This advocates for the use of complex epidemiologically realistic estimators, whose design has recently become possible thanks to deep learning.

Background Rabies is a zoonotic neglected public health problem associated with animal bites, especially domestic carnivores claiming 59,000 deaths annually predominantly in developing countries of Africa and Asia. There is a high risk of exposure among rural communities endemic with animal rabies where adoption of prevention strategies is minimal. This study determined the prevalence of suspected rabies exposure, associated factors, and delayed post-exposure care-seeking among animal-bite human cases in Busia district, Uganda. Methods: This was a cross-sectional study that involved 332 consecutively sampled animal bite human cases that occurred within the period 2023 to 2024. Data for the bite cases from records were collected using a data abstraction tool. In addition, interviewer-administered semi-structured questionnaires were used to collect data on sociodemographic, animal-related and environmental characteristics. Approximate bite locations were collected using Global Positioning System (GPS) coordinates via Kobo collect. Analysis was carried out in STATA 17 using mixed effects modified Poisson regression for factors associated with suspected rabies exposure. Results: The median age of the bite cases was 18 (IQR: 9-36) with the male gender predominantly affected. The prevalence of suspected rabies exposure was 53.6% (95% Confidence interval - CI: 46.8-60.3). Factors associated were urban versus (vs) rural residence (adjusted prevalence ratio-aPR: 1.04, 95%CI: 1.00-1.08), being bitten by a stray animal (aPR: 1.28, 95% CI: 1.22-1.35) and wild animal (aPR: 1.22, 95% CI: 1.14-1.30) vs domestic animal, vaccination status of the biting animal i.e. vaccinated vs unvaccinated (aPR: 0.76, 95% CI: 0.69-0.85), provoked vs unprovoked bites (aPR: 0.82, 95% CI: 0.79-0.86), and distance to nearest river ([&ge;]5km) vs <5km (aPR: 0.93, 95% CI: 0.87-0.99). The prevalence of delayed post-exposure seeking was 23.0% (95% CI: 16.5-31.1) among the suspected rabies exposures. Conclusion: The study reveals a high prevalence of suspected rabies exposure. Factors associated are multidimensional i.e. are of human, animal and environmental origin. The one health paradigm should be emphasized during routine surveillance of rabies-related cases. The study observed that 1 in 5 bite cases delayed to seek care post bite exposure. We recommend collaborations between sectors, routine vaccination and awareness campaigns, and monitoring of wild carnivore populations and environmental dynamics in rabies-related surveillance.

In spite of well-established global immune landscape, SARS-CoV-2 is still able to further spread and continue causing infection waves. The current understanding about the reason behind is limited, and it is still difficult to predict the evolution or spreading tread of SARS-CoV-2. Therefore, it is necessary to investigate whether the establishment of population immunity has changed the virus evolution or spreading pattern. In this investigation, one overall analysis of the SARS-CoV-2 spreading in the past several years have been carried out through one thorough genomic epidemiology study, with Germany being chosen as one representative location in view of the systemic efforts for genomic surveillance. The growth advantage of a few predominant variants in its early spreading period has been evaluated through a logistic regression model. The results have revealed that the major circulating SARS-CoV-2 variants since 2023 are mainly derived from the Omicron BA.2 family. Since middle of 2024, most predominant variants were produced primarily through recombination, indicating that the evolution derived from recombination might be the major driving force for the continuous spread of SARS-CoV-2 despite the existence of population immunity. Furthermore, the lower growth advantage of recently emerged variants might possibly lead to a tread of reduction in the frequency of infection wave. The information revealed from this investigation suggests that although short-term spreading tread can be affected by specific virus feature as well as local immunity landscape, the long-term spreading tread is mainly decided by the genomic diversity of the viruses, and can be predicted through phylogenetic and genomic epidemiology investigation. The results have emphasized the importance of maintaining the efforts for genomic surveillance of SARS-CoV-2, which is essential from both medical and research perspectives.

BackgroundHigh-demand sanitary crises, such as the COVID-19 pandemic, impose a high burden on healthcare professionals, increasing their risk of burnout. Healthcare postgraduate (HCP) trainees compound the general healthcare professional workforce and may face unique risks and challenges. This study aimed to evaluate the incidence of burnout and identify its predictors among healthcare postgraduate trainees during a high-demand sanitary crisis. MethodsA longitudinal observational study was conducted during the pandemic among healthcare postgraduate trainees from 67 Brazilian healthcare institutions. Participants were assessed at baseline (July to September 2020) and after an 18-months follow-up. Individuals with burnout at baseline were excluded. Several questionnaires, including the Oldenburg Burnout Inventory (OLBI) and the depressive disorder PHQ-9 scale were applied. Associations between baseline characteristics and the development of burnout were analyzed using chi-squared and t tests, and log-binomial regression. The study received ethical approval (CAAE: 33493920.0.0000.5558). ResultsA total of 313 participants were included; mean (SD) age: 28.2 (4.6) years; 80.1% (n=250) were biological females; 58.5% (n=183) whites; 51.1% (n=160) physicians; 12.5% (n=39) nurses; 36.4% (n=114) other HCP trainees; 47.9% (n=150) had depressed symptoms at baseline. Burnout incidence rate [95% CI] was 202.9 [166.5, 239.3] cases per 1000 person-years. In bivariate analyses, depressive mood at baseline predicted future burnout (relative risk [95% CI] = 2.14 [1.49, 3.08]; p<0.001), while older age (mean difference, MD [95% CI] = 1.10 [0.16, 2.09] years; p=0.029), higher autonomy (MD [95% CI] = 0.57 [0.10, 1.04] on a 10-point visual numerical scale, VNS; p=0.018) and adequate professional training (MD [95% CI] =0.85 [0.30, 1.40] on VNS; p=0.003) showed protective effects. Sex, race and weekly workload could not predict burnout. In multivariate analyses, depressive symptoms at baseline remained independently associated with higher risk of burnout (risk ratio, RR [95% CI] = 1.84 [1.26, 2.71]; p=0.002), while having adequate professional training showed a protective effect (RR [95% CI] = 0.61 [0.43, 0.87]; p=0.007). ConclusionsVery high incidence of burnout among HCP trainees was observed under a global sanitary crisis. Depressed mood at baseline was the most relevant predictor of subsequent burnout. Providing mental health support for HCP trainees in future widespread sanitary crises seems advisable to preserve the workforce.

Introduction: Current tuberculosis (TB) screening tools, such as the WHO four-symptom screen (W4SS), lack sufficient sensitivity and specificity for effective community-based active case finding, contributing to both missed diagnoses and unnecessary diagnostic evaluations. This study aimed to develop and validate a machine learning (ML) model to improve TB risk prediction among persons aged >=15 years in community settings of Zambia and South Africa. Methods: A large, harmonized dataset was created from four community-based TB prevalence surveys in South Africa and Zambia (N=169,813), restricted to individuals not under treatment at the time of survey. A binary reference outcome was defined based on available microbiological and radiographic data, grouping individuals as either 'Possible TB' or 'Unlikely TB'. An XGBoost model was trained on 80% (N=135,854) of the data using demographic, clinical, and socio-economic variables, and model interpretability was assessed using SHapley Additive exPlanations (SHAP) values. Internal validation was performed using a 20% hold-out test set (N=33,959). Model performance was assessed using discrimination, calibration, and clinical utility measures compared to the W4SS and against WHO's 2025 Target Product Profile (TPP) for a tool in a two-step screening algorithm. Results: Overall, 16,413 (9.7%) of individuals were labelled as 'Possible TB'. On the test set, the XGBoost model yielded an area under the curve (AUC) of 79.7% (95% CI: 78.7, 80.7), outperforming the W4SS (AUC 57.0%; 95% CI: 56.1, 57.8). The XGBoost model achieved 81.5% sensitivity (95% CI: 77.6, 84.9) at a 60% specificity threshold. This exceeded the W4SS, which achieved only 38.2% sensitivity (95% CI: 36.5, 39.9) on the same dataset. SHAP analysis identified age, previous TB treatment, times treated for TB and unemployment as the primary contributors to risk. Conclusion: The ML XGBoost model shows promise as a screening tool to support community-based active case finding activities prior to diagnostic testing. However, as performance remained below TPP targets, and adding variables, e.g. on geolocation, could be considered.

BackgroundEstimates of disease burden from hospital data require well-informed estimates of the size of the catchment population. Data on patient flows from residential areas to a hospital can be used to estimate detailed catchment populations by age, year and type of hospital visit. MethodsCatchment populations were estimated for hospitals throughout France using a proportional flow approach. Data on hospital use and patient residence were accessed from the Agence Technique de lInformation sur lHospitalisation (ATIH). For patients coming from each administrative area, we calculated a preference for each hospital, and combined this with population data for the area to estimate the catchment population of each hospital. For one hospital group, we compared this with data on emergency visits, and data from a retrospective cohort study. ResultsEstimated catchment population by hospital group ranged from 4 million per year for Assistance Publique - Hopitaux de Paris (AP-HP) downwards, with the catchment population strongly reflecting geographic proximity and hospital scale. The type of hospital substantially impacted the size of the catchment area. In the analysis of a single hospital group, the size of the catchment population varied widely with the diagnostic categories associated with the hospital visit. Emergency visits represented a smaller catchment population. The estimated proportional contribution of different departments to the estimated catchment population was similar to their contribution to observed hospital admissions. Incidence rates for a respiratory virus using this catchment population estimation method were consistent with national incidence rates. ConclusionsThis study demonstrates the consistency of the proportional flow framework when applied to appropriate data on hospital usage. The study provides catchment populations for each hospital in France which can be used for burden estimates such as incidence rates, as well as providing insight into the catchment populations served. Analysis at the department geographic level provided an appropriate balance between detail of analysis and the need to mask data for anonymisation. Further analysis should explore how the size of the catchment area corresponds to the associated travel time to the hospital in question.

Occupational activities play a critical role in shaping patterns of infectious disease transmission, as work-related contact, exposure duration, and environmental conditions vary substantially across jobs. Evidence from infectious disease outbreaks, including tuberculosis and other respiratory infections, shows that occupations involving frequent close contact and crowded settings face elevated exposure risk, highlighting the need for systematic occupational risk assessment to inform public health action. This study adopts a data-driven approach to characterize occupational risk for infectious disease transmission in the Philippine workforce. Using job-specific indicators such as encounter frequency, work shift duration, and crowd density, unsupervised clustering methods were applied to group occupations into distinct risk profiles. Unlike predefined sector-based classifications, this approach identifies latent groupings that capture shared exposure characteristics and socioeconomic context. The resulting clusters reveal a clear gradient in exposure risk across occupations, with high-risk roles often concentrated among jobs with lower to moderate income levels, while lower-risk occupations tend to be associated with higher income and greater structural capacity for risk mitigation. These findings provide a framework for occupational risk stratification that is directly relevant for public health planning. Overall, this study demonstrates the value of integrating occupational and socioeconomic data to support targeted workplace interventions, risk-informed surveillance, and more equitable allocation of public health resources for infectious disease prevention and control in the Philippine context.

Bangladesh is experiencing emerging burden of Non-Communicable Diseases (NCDs). Non-communicable diseases (NCDs) are the emerging as major cause of morbidity and mortality, accounting for 61% of deaths in Bangladesh. The study aims to describe the prevalence of NCDs among pregnant women in teagardens in Moulvibazar district. Three teagardens of Sreemongol upazila in Moulvibazar district was selected randomly. The pregnant women were considered for collecting the NCD related information. A sample size of 86 was purposively selected based on relevant literature review. Data was collected by conducting face to face interview with the respondents through pre-tested semi-structured questionnaire. Data was analyzed with the help of SPSS Version 24 Software. For effective use of limited resources, an increased understanding of the shifting burden and better characterization of risk factors of NCDs including Hypertension is needed. Average age of the women attended for screening test was 23 (15-45) years. More than 47% women were found with Gravida 1. The mean duration of pregnancy was found 18.8 weeks. Above 24% percent of GDM women were found at low blood pressure but 2% were identified at high blood pressure. 28% were found underweight with BMI calculation but 11% were identified with overweight. The challenges tests for blood sugar findings of women were found 12.7% GDM positive (7.8-<11 mmol/L). About 16.5% had complications during pregnancy including anaemia, eclampsia, edema, diarrhoea etc. A community based NCDs surveillance model could be developed through participation Government health managers, experts and stakeholders, which were taken by local health system for implementation.

Background Approximately 59,000 cases and 1700 deaths were reported during the 2022-2023 cholera outbreak in Malawi. In response, the Ministry of Health implemented Oral Cholera vaccination campaigns (OCV) as one of the interventions. Four series of single-dose reactive OCV campaigns were conducted in 21 health districts between May 2022 and September 2023. OCV survey report of 2023 estimated a coverage of 55.40%. It was barely known how a single dose of OCV interrupts community transmission. This study was conducted to provide evidence on the use of a single-dose strategy and its contribution towards reducing the risk of cholera infection. Method A cross-sectional quantitative analysis was conducted to assess the effectiveness of OCV in reducing cholera incidence, severity, and mortality during the 2022-2023 cholera outbreak in Malawi. A national cholera line-list was used for analysis. Results Oral cholera vaccination coverage was at 2.0% of 28,920 suspected cholera cases. The effectiveness of a single dose of OCV towards reducing cholera infections was 98.00%. and associated with lower odds of severe dehydration (OR = 0.50; 95% CI: 0.39-0.64), with OCV effectiveness at 50%(95% CI: 36-61) Case fatality rate among vaccinated was 1.20 (95% CI: 0.54; 2.6, p = 0.025) and among unvaccinated it was 2.80% (95% CI: 2.6; 3.0, p = 0.025). Conclusion A single dose of the OCV campaign conducted during the 2022-2023 cholera outbreak in Malawi contributed to the reduction of cholera incidence. The intervention complemented other long-term interventions such as Water, Sanitation and Hygiene Oral Dehydration Points, Case Area Targeted Intervention, and Risk Communication and Community Engagements.

BackgroundHealthcare workers are at increased risk of post-traumatic stress disorder (PTSD) due to prolonged exposure to high-stress clinical environments. Although the Health Belief Model (HBM) has been widely used to explain health behaviors, its application to psychological outcomes such as PTSD remains limited. The role of cognitive-emotional processes, particularly experiential avoidance, in linking health beliefs to trauma symptoms is not well understood. MethodsThis study adopted a quantitative cross-sectional design to collect data from 475 healthcare workers in Ekiti State, Nigeria. Participants completed standardized measures assessing Health Belief Model constructs, experiential avoidance, and PTSD symptoms. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), with bootstrapping used to test direct, indirect (mediation), and moderation effects. Cluster analysis was also conducted using SPSS to validate differences in PTSD symptom severity across psychological constructs and demographic variables. ResultsExperiential avoidance significantly predicted PTSD symptoms ({beta} = 0.395, 95% CI [0.231, 0.565]). HBM constructs were negatively associated with experiential avoidance ({beta} = - 0.198, 95% CI [-0.270, -0.108]) and PTSD symptoms ({beta} = -0.119, 95% CI [-0.216, -0.006]). Mediation analysis indicated that experiential avoidance partially mediated the relationship between HBM constructs and PTSD ({beta} = -0.078, 95% CI [-0.132, -0.037]), with a total effect of - 0.197. Age moderated the relationship between HBM and experiential avoidance ({beta} = -0.114, 95% CI [-0.207, -0.025]) as well as the indirect pathway to PTSD. Sex significantly predicted PTSD symptoms ({beta} = 0.358, 95% CI [0.214, 0.501]). Cluster analysis showed that experiential avoidance and perceived barriers significantly differentiated high and low PTSD symptom groups. ConclusionThe findings support a conditional cognitive-emotional model in which Health Belief Model constructs influence PTSD symptoms both directly and indirectly through experiential avoidance. Demographic factors shape the strength of these relationships, while perceived barriers and experiential avoidance emerge as key determinants of trauma-related distress among healthcare workers.