Epidemiology and Infection

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.

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.

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.

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.

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.

While SARS-CoV-2 and influenza continue to place a significant burden on population health, within-household differences in decisions towards vaccination and seeking care across these two pathogens, and across sociodemographic groups, remain largely unexplored. By conducting a household-level survey in Illinois, we found that many individuals made inconsistent decisions about vaccination: among all adults, 29% were vaccinated for only one of COVID-19 or influenza, and among those with children in the home, 39% lived with a child whose influenza or COVID-19 vaccination status differed from their own. A higher proportion of adults were vaccinated against COVID-19 compared to influenza, while the opposite was true for those younger than 18 years old. These differences hold even when accounting for disparities in coverage by age, race/ethnicity, political affiliation, and socioeconomic status. While vaccinated individuals consistently reported wanting to protect themselves or others, those who declined vaccination reported highly heterogeneous reasons ranging from resource constraints to distrust or misconceptions about vaccination. These differences are even more pronounced for COVID-19, with larger partisan gaps and higher refusal driven by safety concerns, lack of trust, or religious reasons than those who decide not to get the influenza vaccine. In contrast to vaccination, the decision to seek medical care when sick showed opposite sociodemographic trends, that are likely attributable to illness severity. Our findings highlight that closing gaps in COVID-19 and influenza vaccination coverage will require an integrative strategy that accounts for diverse motivations, fears, and barriers to access, while addressing social inequalities common to both diseases.

Introduction-India's immunization initiatives are among the largest globally, characterized by a substantial birth cohort of 27 million children annually, and have achieved significant progress in increasing coverage through the UIP. However, there are still challenges that persist, and multiple determinants contribute to the existing challenges; parental migration is one of them. Migration has always been a key driver of socio-economic and demographic changes, particularly in low and middle-income countries (LMICs). Specifically, there is a need to better understand the vulnerabilities of immunization among recent migrants. To examine this, the study explores the association between a mother's recent migration and the full immunization coverage of children aged 12-23 months in India. Data & Methods-Our study utilized data from the National Family Health Survey-5 (2019-21). The outcome variable of interest in this study is the receipt of all basic vaccinations (full immunization) for children. The primary predictor variable in this study is the children's migration status. We used a series of multivariate logistic regression models to examine the relationship between full Immunization and recent migration of children, with some data restrictions in the models. Results - The results show a 17% difference in full immunization between migrant and non-migrant children. The odds ratios for children who had recently migrated were lower for full immunization (OR: 0.39, 95% CI: 0.35-0.43) compared to children who had not recently migrated. Even across the household wealth quintile and social groups, the recent migration of children was associated with being less likely to be fully immunized among children 12-23 months. Conclusion- The findings of this study provide significant quantitative evidence that recent migration (less than 3 years) of children is a key factor influencing Immunization coverage and is a predictor of full vaccination among children aged 12-23 months in India. The recent migration was consistently linked to a lower likelihood of full immunization coverage across different household wealth levels and social groups. This study suggests that recently migrated children are a vulnerable subgroup of the population at risk of not receiving all basic vaccinations by their first birthday.

ABSTRACT Background Dog bite injuries are a major yet largely preventable public health concern worldwide. They contribute significantly to morbidity, healthcare burden, and economic costs, particularly in emergency department .The present study aims to analyse the demographics and injury pattern of dog bite cases presenting to the emergency department of a tertiary care hospital in Chennai. Methods We conducted a cross-sectional study with dog bite injured participants attending the Causality from November 2025 to April 2026 data was collected using a structured tool including details on demographics (Age, Gender, Education) injury related characteristics , history of pure bite site of dog bite injury type, WHO bitten criteria and information to management etc. We used here non probability statistical analysis and age specific dog bite cases and independent variables were analysed using SPSS (2.0 version). Result A total of Two hundred sixteen dog bite cases were analysed in the study by period of 6 months The majority of participants were 172 (79.6%) were above 18 years and 44 (20.4) were below 18 year, 130 (60%) from rural areas and 86 (39.8%) from urban areas, 136 (63.0%) of Victims presented within a day of the bite, 61( 28.2) next day and 19 (8.8%) in after one week 66 (30.6) were bitten by own dog and 150(69.4%)were bitten by neighbour / friended dog. 124(57.4) were bitten by stray dog 92(42.6) bitten by pet dog. 117(54.2) were vaccinated dog and 99(45.8%) were not vaccinated .110(50.9) victims were injured by laceration. 26(12.0%) were injured by puncture wound.46(21.3) were injured by abrasion 10(4.6) were injured by avulsion 15(6.9%) were injured by crush injury. 156(72.2%) were had minor wound.45(20.8%) victims had moderate wound and 15(6.9%) victims had severe wound. 112(51.9%) victims were taken antibiotics.104(48%) were not taken antibiotics. 185(85.6%) victims received tetanus toxoid, 31(14.4%) were not received tetanus toxoid. CONCLUSION There is a high burden of dog bite injuries from stray dogs in India. Despite early hospital presentation in many cases gaps in first aid practices and rabies post exposure prophylaxis were evident and highlighting inadequate awareness. Key words Rabies immunoglobulin, Dog bite, WHO criteria, Anti rabies vaccine, stray Dog, wound

Background Colorectal cancer is a growing public health concern in low- and middle-income countries, particularly in the context of nutritional transition and changing lifestyles. In Mauritania, evidence on factors associated with colorectal cancer remains limited. This study sought to identify nutritional, behavioral and anthropometric factors associated with colorectal cancer among adults living in Nouakchott. Methods A case-control study was conducted in Nouakchott between January and April 2026. The study included 50 confirmed colorectal cancer cases and 100 controls with no personal history of cancer. Data were collected using a standardized questionnaire covering sociodemographic characteristics, dietary habits, behavioral factors and anthropometric measurements. Crude and adjusted odds ratios with 95% confidence intervals were calculated using binary logistic regression. Results Low educational level was more frequent among cases than controls, 70.0% versus 27.0%, and remained independently associated with case status after adjustment (aOR = 4.98; 95% CI: 1.81-13.70; p = 0.002). Being married or living with a partner was also associated with case status (aOR = 3.72; 95% CI: 1.19-11.66; p = 0.024). Abdominal obesity was associated with colorectal cancer in bivariate analysis but not after adjustment. High consumption of salty foods remained associated with case status in the multivariate model (aOR = 47.45; 95% CI: 4.83-466.40; p = 0.001). However, this estimate should be interpreted with caution given the wide confidence interval and the limited sample size (n=50 cases). Refined sugars and canned foods were associated with case status only in bivariate analysis. Inverse associations observed for coffee and sugar-sweetened beverages should be interpreted cautiously because of possible reverse causality. Conclusion Low educational level and high consumption of salty foods were the most defensible factors associated with colorectal cancer in this study. These findings support strengthening nutrition-related prevention and health education interventions in Nouakchott. Larger studies with more detailed dietary assessment are needed to confirm these associations.

Background Microbiological confirmation of paediatric pulmonary tuberculosis is frequently unattainable, rendering chest radiography a critical yet underutilised diagnostic tool. Methods We conducted a retrospective diagnostic accuracy study of the qXR version 4.2.1 (Qure.ai), a paediatric optimized computer-aided detection (CAD) algorithm, for pulmonary tuberculosis. Diagnostic performance was assessed against microbiological (MRS) and clinical reference standards (ClRS). Bayesian latent class analysis (LCA) was applied to address the imperfection of both reference standards in children. Performance was quantified using area under the receiver operating characteristic curve (AUROC) and estimates of sensitivity and specificity. Results We included digital chest radiographs of 932 Gambian children (< 15 years) comprising 80 (9%) children with confirmed tuberculosis, 163 (17%) with unconfirmed tuberculosis, and 689 (74%) classified as unlikely tuberculosis. Against MRS, qXR demonstrated AUROC, sensitivity and specificity of 0.68 (95% CI, 0.61 to 0.75), 54% (95% CI, 43 to 64%), and 82% (95% CI, 79 to 84%), respectively. Against ClRS, the AUROC, sensitivity and specificity were 0.73 (95% CI, 0.69 to 0.77), 41% (95% CI, 34 to 49%), and 87% (95% CI, 84 to 89%), respectively. Bayesian LCA, assuming conditional independence, estimated sensitivity of 79% (95% CrI, 65 to 89%) and specificity of 82% (95% CrI, 79 to 84%). Assuming conditional dependence between qXR and expert radiologist, and between culture and Xpert, estimated sensitivity increased to 89% (95% CrI, 71 to 98%), with specificity remaining at 82% (95% CrI, 79 to 84%). Conclusions Paediatric optimized qXR algorithm provides a valuable complementary tool for diagnosis of paediatric pulmonary tuberculosis. Conventional reference standards likely underestimate the true diagnostic performance of CAD systems in children.

This study analyzes 794,811 digitized medical examina- tions from Indian life-insurance applicants, a working-age, urban-skewed demographic often undersampled by national surveys. The cohort exhibits a pronounced South-Asian car- diometabolic risk profile: among valid adult records, 41.9% met the criteria for dyslipidemia (driven heavily by low HDL and elevated triglycerides), and 61.4% met AHA 2017 crite- ria for stage 1 hypertension. However, canonicalizing this dataset across 33,244 diagnostic centers revealed significant heterogeneity in laboratory reference ranges. At the clinical prediabetes threshold of 110 mg/dL for fasting blood sugar, the record-pair disagreement rate across laboratories was 49.7%, with similar variance across other common tests. This structural inconsistency materially affects patient classi- fication and the tracking of disease prevalence, underscoring a critical need for the national standardization of laboratory reporting in India

Background: Tuberculosis (TB) remains the leading infectious cause of death worldwide, with India accounting for nearly one-fourth of global TB cases. Ni-kshay, the countrys digital case-based TB notification platform is rich in data pertaining to the continuum of care of TB patients. This study aims to develop a standardized analytical approach to programmatic data to identify predictors of unfavourable treatment outcomes and mortality among adult drug-sensitive TB patients at the state level for Maharashtra during 2021 and 2022. Methods: Two separate analyses were undertaken comparing treatment success with: (1) unfavourable outcomes (death, treatment failure, loss to follow-up, regimen change, or not evaluated); and (2) mortality. Multivariate logistic regression was used to compute adjusted odds ratios (aOR) for key risk factors, adjusting for age, gender, and weight. Results: The final cohort included 323,124 cases for unfavourable outcome analysis and 315,579 cases for mortality analysis. Increasing age, male gender, lower body weight, known HIV and diabetes comorbidities, tobacco and alcohol consumption, and "unknown" status for behavioural risks and comorbidity status were significantly associated with increased odds of both unfavourable outcomes and mortality. Conclusions: This study highlights the utility of programmatic data in identifying high-risk TB patients and offers a reproducible analytic framework.

Purpose: This study developed a Bayesian hierarchical spatio-temporal modeling framework to analyze factors and trends in malaria risk across Ghana's 16 administrative regions from 2020 to 2024. The aim was to identify statistically significant areas with elevated or persistent malaria risk, to inform targeted intervention planning and support the National Malaria Elimination Program. Methods: This study utilized malaria incidence data from the Ghana Health Service's District Health Information Management System-II covering the years 2020 to 2024. Meteorological data were sourced from the Visual Crossing Weather Data, and regional population estimates were obtained from the Ghana Statistical Service. To analyze the data, a Bayesian hierarchical spatiotemporal model with a Negative Binomial (NB) likelihood was implemented using Integrated Nested Laplace Approximation to account for overdispersion. The model included Conditional Autoregressive priors for structured spatial effects, first-order random walk priors for temporal dependence, and spatio-temporal interaction terms. Additionally, Local Indicators of Spatial Association (LISA) analysis with 999 conditional permutations was conducted to identify statistically significant spatial clusters, including high-high hotspots and low-low cold spots. Results: The NB model significantly outperformed the Poisson model, leading to a reduction in the dispersion statistic from 9,227.55 to 1.11. Humidity with a 1-month lag showed the strongest positive association with malaria risk, while the ultraviolet index had the greatest protective effect. Predictive relative risk maps identified persistent high-risk clusters in the northern and northwestern regions, specifically Upper West, Upper East, Bono, Ahafo, and Western North. LISA analysis indicated that Bono-Ahafo has been a stable high-high cluster from 2020 to 2023, while Ashanti has remained a consistent low-high anomaly. Additionally, Greater Accra and Central regions formed a significant low-low cluster in 2024. Conclusion: The Bayesian hierarchical spatio-temporal framework effectively characterized the complex transmission dynamics of malaria in Ghana. It revealed significant spatial dependence, temporal correlation, and interactions between these factors. By identifying persistent high-risk clusters and statistically significant spatial associations, this framework provides essential evidence to guide resource allocation. These findings support Ghana's National Malaria Elimination Program Strategic Plan (2024-2028) by enabling targeted interventions in hotspots and optimizing the use of limited resources to sustain progress in low-transmission areas.

Background: Diarrheal illness in children leads to 3.5 million care visits and 200,000 hospitalizations annually in the US. Viruses are responsible for most pediatric diarrheal cases, yet limited guidance on distinguishing viral from bacterial etiologies complicates clinical decision-making, especially regarding empiric antibiotic use. Methods: We used clinical and qualitative molecular etiologic data from the Implementation of Molecular Diagnostics for Pediatric Acute Gastroenteritis (IMPACT) study to develop prediction models for viral etiology of diarrhea. We used conditional random forests to identify informative clinical and environmental predictors and evaluated model performance using logistic regression and random forests within a 5-fold cross-validation framework. We conducted external validation using the Alberta Provincial Pediatric Enteric Infection Team (APPETITE) dataset. Results: Variables predictive of viral etiology included younger age, non-bloody diarrhea, winter season, and presence of vomiting. External validation showed that an AUC of 0.82 can be achieved with a parsimonious 5-variable model, yielding a sensitivity of 0.92 and specificity of 0.55 Conclusion: Our results suggest that in North American healthcare settings, clinical prediction models can inform decision-making by identifying children with a high probability of viral diarrhea, improving diagnostic clarity, and reducing unnecessary testing and treatment.

Background: Mass gathering events (MGEs) are associated with several public health challenges and may cause a strain on healthcare services. Literature findings on the impact of MGEs on emergency departments (EDs) are heterogeneous. Objectives: To examine shifts in ED attendance characteristics during a major sporting tournament, namely the UEFA European Football Championship 2024 held in Germany. Methods: We conducted a retrospective observational study using ED data from the Emergency Department Data Registry. We compared baseline ED attendance characteristics between the tournament and the reference period, defined as two weeks before and two weeks after the tournament, and between Germany game days and non-Germany game days. Hourly attendance patterns were analysed for all Germany games using a reference range. Results: We included data from 41 EDs, totalling 253,493 attendances during the study period. A 1.57% increase in attendance was observed during the tournament compared to the reference period, with baseline characteristics remaining similar. The median daily attendance within all EDs was slightly lower on Germany game days (4066) compared to non-Germany game days (4128). Modest changes were observed in the hourly attendance on Germany game days, most notable during the last Germany game where a decrease in attendance below the reference range extended over three hours. Conclusions: The observed shifts in ED attendance were minimal, suggesting that no major changes of public health relevance occurred in ED attendance during the tournament. We highlight the utility of using ED data for monitoring and for enhancing the understanding of the public health risks and challenges associated with MGEs.

Close to 50% of all bird species are reservoirs of potentially pathogenic fungi, including those listed as priority by the World Health Organization. In Malawi, data on diversity, pathogenic potential, and ecological avian sources of medically important yeast are scarce. A cross-sectional study using a descriptive approach was conducted in Blantyre, Southern Malawi, to characterise medically important yeasts recovered from environments contaminated with excreta/guano from synanthropic pigeons. A total of 20 samples were collected from 4 peri-urban areas, which yielded 71 yeast isolates. To assess the pathogenic potential of the environmental isolates, we compared their phenotypic virulence traits with those of 21 clinical yeast isolates collected from referral hospital laboratories. Pichia kudriavzevii (39%) and Candida orthopsilosis (30%) were the commonly isolated species in the pigeon-guano-contaminated environments. Candida parapsilosis sensu stricto (29%) and Candida albicans (24%) constituted most of the clinical yeast isolates. Half of the species isolated in the pigeon-guano-contaminated environments were also identified among the clinical isolates. A majority of the environmental isolates showed virulence traits similar to or stronger than clinical isolates. The findings underscore the critical need for integrated surveillance under the One Health framework, especially in bird-inhabited spaces close to human settlements.