Epidemiological Approach Research Articles

Abstract 2388: Artificial neural network based ensemble models for single-arm glioblastoma trials: A new historical control adjustment method

Abstract Background: Despite a long history of poor decision making leading to repeated failed phase 3 trials, phase 2 single-arm studies continue to be common in glioblastoma (GBM). With the drawback of inflated false positive rate in current adjustment method for historical control data as concurrent controls, the new statistical methods and validation approach will be needed for adequate covariate adjustment in the GBM single-arm trial data. Methods: The systematic review was performed to extract the summary-level external data of survival outcomes (mean progression-free survival, mPFS, and PFS at 6 months, PFS6) and prognostic factors (age, gender, extent of resection, KPS, methylation status, and treatment history) from published randomized clinical trials for the standard of care (SOC) treatment in GBM. Four models of the standard, bootstrap aggregating, random subspaces, and random patches models were developed to construct a powerful predictive tool by comprising a series of connections producing survival outputs as a function of prognostic inputs using (1) artificial neural network (ANN) method and (2) linear method (Fig1). The root mean square errors (RMSEs) were calculated to evaluate the model performance using the five-fold cross-validation approach with the effects of ensemble size. The predictive survival outcomes among prognostic factors were calculated to evaluate the relative importance of factors. Results: We identified 19 Phase 2 and 3 clinical trials in glioblastoma and two survival outcomes and seven prognostic factors (Table 1). ANN models have less prediction error and therefore better performance on the test set than linear models. Presumably, the relationships in the data are highly nonlinear, and thus linear models cannot capture these relationships (Table 2). Bagging models typically outperform their standard counterparts for both ANNs and linear models. Ensemble methods can capture many trends within the data by manipulation of the training set and are therefore less prone to biases of individual models exacerbated by the small sample size. The previous treatment history and methylation status were the top two influential prognostic factors for both mPFS and PFS6, followed by the extent of resection and mean age (Fig2). With the examination of the ANN parameters of sample size, learning rate, training hyperparameters, it could be observed that there is no clear change in error when increasing sample size beyond 10 (Fig3). Conclusions: High failure rate of phase 3 glioblastoma trials emphasizes the need for greater reliability of earlier studies in phase 2 single-arm trials. The proposed statistical and epidemiologic approach based on the ensemble-based ANN models will be an effective tool to lead to better decision with phase 2 single-arm trials, which may give better chance to appropriately advance to phase 3 trials with higher predictive power. Citation Format: Wonsuk Yoo, Tortsen Ullrich, Nader Sanai. Artificial neural network based ensemble models for single-arm glioblastoma trials: A new historical control adjustment method [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2388.

Estimating multiplicity of infection, allele frequencies, and prevalences accounting for incomplete data.

Molecular surveillance of infectious diseases allows the monitoring of pathogens beyond the granularity of traditional epidemiological approaches and is well-established for some of the most relevant infectious diseases such as malaria. The presence of genetically distinct pathogenic variants within an infection, referred to as multiplicity of infection (MOI) or complexity of infection (COI) is common in malaria and similar infectious diseases. It is an important metric that scales with transmission intensities, potentially affects the clinical pathogenesis, and a confounding factor when monitoring the frequency and prevalence of pathogenic variants. Several statistical methods exist to estimate MOI and the frequency distribution of pathogen variants. However, a common problem is the quality of the underlying molecular data. If molecular assays fail not randomly, it is likely to underestimate MOI and the prevalence of pathogen variants. A statistical model is introduced, which explicitly addresses data quality, by assuming a probability by which a pathogen variant remains undetected in a molecular assay. This is different from the assumption of missing at random, for which a molecular assay either performs perfectly or fails completely. The method is applicable to a single molecular marker and allows to estimate allele-frequency spectra, the distribution of MOI, and the probability of variants to remain undetected (incomplete information). Based on the statistical model, expressions for the prevalence of pathogen variants are derived and differences between frequency and prevalence are discussed. The usual desirable asymptotic properties of the maximum-likelihood estimator (MLE) are established by rewriting the model into an exponential family. The MLE has promising finite sample properties in terms of bias and variance. The covariance matrix of the estimator is close to the Cramér-Rao lower bound (inverse Fisher information). Importantly, the estimator's variance is larger than that of a similar method which disregards incomplete information, but its bias is smaller. Although the model introduced here has convenient properties, in terms of the mean squared error it does not outperform a simple standard method that neglects missing information. Thus, the new method is recommendable only for data sets in which the molecular assays produced poor-quality results. This will be particularly true if the model is extended to accommodate information from multiple molecular markers at the same time, and incomplete information at one or more markers leads to a strong depletion of sample size.

Wastewater-based estimation of diabetes mellitus prevalence in 237 cities: A cross-China study

Diabetes mellitus, a metabolic disease characterized by hyperglycemia, has been witnessed as a rapidly escalating worldwide health crisis. China currently had 140.9 million diabetic population in 2021, which was the largest globally. DM has witnessed a significant surge in the past few decades, leading to an alarming rise in the overall burden caused by this disease. To monitor the near real-time DM prevalence and the consumption of first-line anti-diabetic drugs, a wastewater-based epidemiology (WBE) approach based on the back-calculation of metformin concentration was implemented in 237 cities in China. The quantitative analysis of metformin in wastewater was conducted by LC-MS/MS with satisfactory results of method validation. The average concentration of metformin in wastewater was 14.07 ± 13.16 μg/L, and the per capita consumption was 5.16 ± 2.08 mg/day/inh, ranging from 0.90 to 10.36 ± 4.63 mg/day/inh. The calculated metformin prevalence was found to be 0.52 % ± 0.28 %, and the final estimated DM prevalence was 11.33 % ± 4.99 %, which was nearly consistent with the result of the International Diabetes Federation survey of 9.98 %. The results suggested that metformin might be one of the suitable WBE biomarkers in DM monitoring and WBE strategy could potentially enable the estimation of DM prevalence in most of Chinese cities after reasonable correction of associated parameters.

Stochastic near-optimal controls for treatment and vaccination in a COVID-19 model with transmission incorporating Lévy jumps

The COVID-19 pandemic has triggered a groundbreaking reliance on mathematical modelling as an important tool for studying and managing the spread of the virus since its emergence. Public health preventive measures such as vaccination and therapeutics can effectively reduce or eradicate an infectious disease. This work investigates these two strategies for controlling the COVID-19 epidemic through a stochastic epidemiological modelling approach. The existence and uniqueness of a positive solution of the stochastic system is studied. A priori estimates of the vaccination and treatment controls are established. Sufficient and necessary conditions are obtained for the near-optimal control problem of the stochastic model using the maximum condition of the Hamiltonian function and the Ekeland principle. Finally, to support our theoretical results, numerical simulations for a combination of optimized vaccination and treatment strategies were presented to understand the challenges posed by COVID-19 in Brazil.

Estimation of the spatial pattern of gout prevalence across China by wastewater-based epidemiology

Gout is a metabolic arthritis caused by hyperuricemia. In recent years, the prevalence of gout has been increased significantly in China due to the improvement of the living standards, and gout has become another common metabolic disease following diabetes mellitus. Gout severely affects the health status and life quality of human. In order to monitor the near real-time prevalence of gout, a wastewater-based epidemiology (WBE) approach was carried out in 257 Chinese cities using febuxostat as the biomarker. Febuxostat in wastewater was measured by a LC-MS/MS method with satisfactory results of method validation. The average concentration of febuxostat in wastewater was 53.05 ± 31.76 ng/L, with the estimated per capita consumption of 124.40 ± 73.37 mg/day/1000 inhabitant. The calculated prevalence of febuxostat was 0.41 % ± 0.24 %, and the prevalence of gout was finally estimated to be 1.30 % ± 0.77 % (0.60 % to 2.11 %), which was nearly consistent with value of 1.10 % obtained from the Guideline for the diagnosis and management of hyperuricemia and gout in China (2019). The results indicated that the febuxostat-based WBE approach might be reasonable to assess the near real-time gout prevalence in China.

Molecular epidemiology of the HIV-1 epidemic in Fiji

Very little is known about the HIV-1 epidemic in Fiji, nor the wider South Pacific region more generally, yet new reported HIV-1 infections are on the rise. As of 2023, there are an estimated 2000 cases of HIV-1 in Fiji with heterosexual contact the primary route of transmission. In this study, we used a molecular epidemiological approach to better understand the genetic diversity of the HIV-1 epidemic in Fiji and reveal patterns of viral transmission. Between 2020 and 2021, venous blood samples were collected from people who had previously been diagnosed with HIV-1. We generated molecular data from 53 infections, representing ~2–3% of reported cases, to identify HIV-1 subtypes and determine the outbreak’s trajectory. Among the 53 HIV-1 cases, we used Bayesian inference to estimate six separate introductions with at least two of these introductions leading to sustained transmission forming large, nation-wide clusters of HIV-1 subtype C. We found that since the introduction of public health interventions circa 2014, the effective reproductive number, Re, decreased among the major clusters identified from an average of 2.4 to just below 1. Molecular epidemiological analysis suggested that public health efforts aimed at decreasing the spread of the disease were at least somewhat effective. Nevertheless, with a recent rise in reported HIV-1 cases, this study demonstrates the utility of molecular data to inform a more targeted public health approach for controlling its spread.

Exposure to environmental pollutants: A mini-review on the application of wastewater-based epidemiology approach.

Wastewater-based epidemiology (WBE) is considered an innovative and promising tool for estimating community exposure to a wide range of chemical and biological compounds by analyzing wastewater. Despite scholars' interest in WBE studies, there are uncertainties and limitations associated with this approach. This current review focuses on the feasibility of the WBE approach in assessing environmental pollutants, including pesticides, heavy metals, phthalates, bisphenols, and personal care products (PCPs). Limitations and challenges of WBE studies are initially discussed, and then future perspectives, gaps, and recommendations are presented in this review. One of the key limitations of this approach is the selection and identification of appropriate biomarkers in studies. Selecting biomarkers considering the basic requirements of a human exposure biomarker is the most important criterion for validating this new approach. Assessing the stability of biomarkers in wastewater is crucial for reliable comparisons of substance consumption in the population. However, directly analyzing wastewater does not provide a clear picture of biomarker stability. This uncertainty affects the reliability of temporal and spatial comparisons. Various uncertainties also arise from different steps involved in WBE. These uncertainties include sewage sampling, exogenous sources, analytical measurements, back-calculation, and estimation of the population under investigation. Further research is necessary to ensure that measured pollutant levels accurately reflect human excretion. Utilizing data from WBE can support healthcare policy in assessing exposure to environmental pollutants in the general population. Moreover, WBE seems to be a valuable tool for biomarkers that indicate healthy conditions, lifestyle, disease identification, and exposure to pollutants. Although this approach has the potential to serve as a biomonitoring tool in large communities, it is necessary to monitor more metabolites from wastewater to enhance future studies.

Analysis of bicycle crash characteristics and typical scenarios in France: A descriptive epidemiology and clustering approach

Bicycle crashes can result in severe injuries and fatalities, emphasizing the importance of identifying typical scenarios and characteristics of these crashes to develop effective prevention and mitigation strategies. This study analyzed datasets of bicycle crashes in France from 2005 to 2021 extracted from the French national road traffic accident database, evaluating bicycle accident characteristics through conventional descriptive epidemiology approaches and using the K-medoids clustering method to identify typical scenarios and their associated characteristics. Among 1,121,571 road traffic accidents in France, 80,851 were bicycle crashes, with a decline between 2005 and 2013 but a steady increase since then, peaking in 2020 at approximately 1.74 times that of 2005. Victims of bicycle crashes were primarily between 11 and 62 years old, with the largest population among 14–33 years old. Male victims were more involved in bicycle crashes than female victims, with the majority of crashes involving a moving vehicle. The majority of bicyclists involved in accidents were found not wearing helmets, and even bicyclists wearing helmets still sustained injuries. Typical bicycle crash scenarios included four bicycle-vehicle head-on-side collisions, one bicycle-obstacle collision, and two bicycle-pedestrian collisions, with bicycle-obstacle collisions often resulting in serious injuries similar to bicycle-vehicle collisions. Pedestrians were more likely to sustain injuries than bicyclists during bicycle-pedestrian collisions, and their injuries were often more severe than those of bicyclists. The study provides insights into the characteristics and typical scenarios of bicycle crashes in France and can be used to develop targeted interventions to improve road safety for cyclists.

Cardiogenic Shock in Older Adults: A Focus on Age-Associated Risks and Approach to Management: A Scientific Statement From the American Heart Association.

Cardiogenic shock continues to portend poor outcomes, conferring short-term mortality rates of 30% to 50% despite recent scientific advances. Age is a nonmodifiable risk factor for mortality in patients with cardiogenic shock and is often considered in the decision-making process for eligibility for various therapies. Older adults have been largely excluded from analyses of therapeutic options in patients with cardiogenic shock. As a result, despite the association of advanced age with worse outcomes, focused strategies in the assessment and management of cardiogenic shock in this high-risk and growing population are lacking. Individual programs oftentimes develop upper age limits for various interventional strategies for their patients, including heart transplantation and durable left ventricular assist devices. However, age as a lone parameter should not be used to guide individual patient management decisions in cardiogenic shock. In the assessment of risk in older adults with cardiogenic shock, a comprehensive, interdisciplinary approach is central to developing best practices. In this American Heart Association scientific statement, we aim to summarize our contemporary understanding of the epidemiology, risk assessment, and in-hospital approach to management of cardiogenic shock, with a unique focus on older adults.

Evaluation of outbreak persistence caused by multidrug-resistant and echinocandin-resistant Candida parapsilosis using multidimensional experimental and epidemiological approaches

ABSTRACT Candida parapsilosis is known to cause severe and persistent outbreaks in clinical settings. Patients infected with multidrug-resistant C. parapsilosis (MDR Cp) isolates were identified in a large Turkish hospital from 2017–2020. We subsequently identified three additional patients infected with MDR Cp isolates in 2022 from the same hospital and two echinocandin-resistant (ECR) isolates from a single patient in another hospital. The increasing number of MDR and ECR isolates contradicts the general principle that the severe fitness cost associated with these phenotypes could prevent their dominance in clinical settings. Here, we employed a multidimensional approach to systematically assess the fitness costs of MDR and ECR C. parapsilosis isolates. Whole-genome sequencing revealed a novel MDR genotype infecting two patients in 2022. Despite severe in vitro defects, the levels and tolerances of the biofilms of our ECR and MDR isolates were generally comparable to those of susceptible wild-type isolates. Surprisingly, the MDR and ECR isolates showed major alterations in their cell wall components, and some of the MDR isolates consistently displayed increased tolerance to the fungicidal activities of primary human neutrophils and were more immunoevasive during exposure to primary human macrophages. Our systemic infection mouse model showed that MDR and ECR C. parapsilosis isolates had comparable fungal burden in most organs relative to susceptible isolates. Overall, we observed a notable increase in the genotypic diversity and frequency of MDR isolates and identified MDR and ECR isolates potentially capable of causing persistent outbreaks in the future.

Etiology, Epidemiology, and Therapeutic Approaches for Primary Sclerosing Cholangitis in the Context of Concurrent Non-specific Inflammatory Bowel Diseases

Introduction: Primary sclerosing cholangitis (PSC) is a chronic, idiopathic disease characterized by persistent and progressive inflammation of the intrahepatic and/or extrahepatic bile ducts. This leads to fibrosis, cholestatic complications, and liver failure. In over 70% of patients, non-specific intestinal inflammations coexist, particularly ulcerative colitis, and sporadically Crohn's disease. Aim: Our study aimed to assess current literature on primary sclerosing cholangitis (PSC), covering its causes, symptoms, treatment methods, and the connection between PSC and inflammatory bowel disease (IBD) co-occurrence. Materials and methods: We conducted a PubMed literature review using keywords like "primary sclerosing cholangitis pathogenesis," "primary sclerosing cholangitis and inflammatory bowel disease," and "primary sclerosing cholangitis and ulcerative colitis.” Results: Our research extensively covered PSC epidemiology, pathogenesis, and treatment options. Emphasis was placed on the heightened prevalence of inflammatory bowel diseases, including ulcerative colitis, among PSC patients. Summary: Primary sclerosing cholangitis (PSC) is a disease causing gradual damage to bile ducts within or outside the liver. Over 70% of patients also experience inflammatory bowel disease (IBD), mainly ulcerative colitis. The exact causes of PSC and its connection to IBD remain unclear. The theories involve hyperactive "intestinal" T cells or the impact of gut microbiome on their growth. Presently, a liver transplant stands as the sole remedy.

Environmental Metagenomic Analysis of "ESKAPE" Pathogens in the Pediatric Intensive Care Unit of General Hospital Yogyakarta Indonesia

Healthcare-associated infections (HAIs) are infections that occur while receiving health care, develop in a hospital or other healthcare facility, and first appear 48 hours or more after hospital admission, or within 30 days after having received health care. HAIs are linked to high mortality rates, prolonged stays, increased hospital overhead costs, and financial burdens on patients. Bacterial transmission from medical personnel or the environment, or patient-to-patient contact are all potential causes of these infections. A molecular epidemiology approach is needed to examine the contribution of risk factors and the distribution of "ESKAPE" pathogens within the hospital environment. In this study, we conducted a comprehensive analysis of the distribution of ESKAPE bacterial pathogens in the environment of pediatric intensive care units over a 30-day time interval using shotgun metagenomics. We collected samples from handwashing sinks, the floor around patients, and ventilator screens and tubes in the pediatric intensive care unit (PICU) of General Hospital, Yogyakarta, Indonesia in March 2022. We determine taxonomic profiles and also detect resistome, and virulome distribution of ESKAPE pathogens on various environmental surfaces through shotgun metagenomic sequencing. The microbiomes of the floor, sink, and mechanical ventilator exhibit a diverse composition of microbial communities, featuring significant species richness based on Shannon and Simpson’s index. These microbiomes encompass a wide array of microbial species, including ESKAPE bacterial pathogens, as well as profiles related to resistome and virulome. ESKAPE pathogens, especially Acinetobacter baumannii, predominated in the PICU environment. Most virulome have been associated with metabolism/nutrition and adhesion. Noteworthy findings include resistome genes characterized by mechanisms like efflux pumps (MDR) and alterations in antibiotic targets.

(331) A Novel Epidemiological Approach to Geographically Mapping Selective Androgen Modulator Receptors (SARMs) in the United States Through Google Trends

Abstract Introduction Selective androgen receptor modulators (SARMs) are a class of compounds known for their ability to exert agonistic and/or antagonistic effects on androgen receptors. Although there are currently no U.S. Food and Drug Agency-approved indications for SARMs, investigators are exploring the potential uses for these compounds. Objective This study aims to comprehensively assess the level of public interest in SARMs over the past ten years. Methods Google Trends data spanning the past decade was meticulously analyzed to evaluate the public interest in specific SARMs, (Ostarine, LGD-4033, GSK2881078, PF-06260414, AC-262,356), in comparison to testosterone replacement therapy and androgen replacement therapy. As benchmarks, control search terms, such as “news," "weather," "sports," "Google," "Netflix," and "Facebook" were employed. Results The 10 geographical areas with the highest SARM search rate were military instillations or towns surrounding military instillations. Within these areas, the search interest accounted for a median of 4.5% of the control search interest, while the areas displaying the greatest interest reached a substantial 12%. It is noteworthy that even in the presence of an awareness campaign against the use of unapproved supplements (such as SARMs) by the Department of Defense, SARM use steadily increased in close proximity to these identified areas. In contrast, metropolitan areas unrelated to military installations accounted for less than 1% of the control search interest. Search interest for “Testosterone” was 6% nationally, however, in areas associated with high SARM interest, search interest was 6.8%. Conclusions Our results suggest there is a higher rate of internet searches for SARMs at or near military instillations compared to other geographic regions. Since these medications are not FDA approved and still undergoing clinical investigation, the side effect profiles are not well understood potentially leading to adverse events. Further work is needed to understand if this increased interest translates to use of SARMs among our service members. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Advisory board and speaker for Coloplast; consultant for Cynosure; advisory board and speaker for Halozyme; intellectual property with Masimo; advisory board for Promescent; consultant for Sprout; advisory board for Xialla.

High-risk HPV prevalence and vaccination coverage among Indigenous women in the Colombian Amazon: Implications for cervical cancer prevention. Cross-sectional study.

Cervical cancer, primarily caused by Human Papillomavirus (HPV) transmission through sexual contact, necessitates comprehensive strategies to combat its impact on women's health. Yet, certain underserved populations, such as low socioeconomic and ethnic minority groups, encounter barriers in accessing timely interventions and early diagnosis. This cross-sectional study was conducted with the aim of assessing HPV prevalence, genotype distribution, and co-infections among 280 adult women residing in a Colombian Indigenous Reserve within the Amazon region. The research adhered to a community-centric approach that respected cultural norms, native languages, and Indigenous authorities' permission. The study revealed an overall HPV infection prevalence of 31.1% (n = 87, 95% CI 25.7-36.8), with 22.5% (n = 63, 95% CI 17.7-27.8) of women infected by at least one high-risk HPV genotype and 15.0% (n = 42, 95% CI 11-19.7) infected by at least one LR genotype. These results align with the findings of other Colombian studies. Notable high-frequency genotypes included 16, 52, 66, 56, and 68, with the most common combinations being [66-52] and [66-58]. The study also assessed the prevalence of HPV vaccination, revealing a rate of 22.9%, lower than the national average. In vaccinated women, the prevalence of genotypes 16 and 18 was significantly reduced, as anticipated. Importantly, it was observed that 57.1% of all high-risk HPV infections could have been prevented with the use of the nonavalent vaccine. These findings underscore the critical need to enhance adherence to early cervical cancer detection and monitor positive cases to evaluate high-risk HPV persistence. Efforts should be directed toward continuing vaccination coverage against high-risk HPV 16 and 18 with the quadrivalent vaccine, while also striving to make the nonavalent vaccine accessible for inclusion in large-scale public health programs. Additionally, the study did not identify a specific pattern of co-infection. The study emphasizes the significance of adopting a locally tailored epidemiological approach to guide and promote cervical cancer prevention efforts in Indigenous communities.

Old and New Aphid-Borne Viruses in Coriander in Chile: An Epidemiological Approach.

In Chile, edible herbs are mainly grown by small farmers. This type of horticultural crop typically requires intensive management because it is highly susceptible to insects, some of which transmit viruses that severely affect crop yield and quality. In 2019, in coriander plants tested negative for all previously reported viruses, RNA-Seq analysis of one symptomatic plant revealed a plethora of viruses, including one virus known to infect coriander, five viruses never reported in coriander, and a new cytorhabdovirus with a 14,180 nucleotide RNA genome for which the species name Cytorhabdovirus coriandrum was proposed. Since all the detected viruses were aphid-borne, aphids and weeds commonly growing around the coriander field were screened for viruses. The results showed the occurrence of the same seven viruses and the alfalfa mosaic virus, another aphid-borne virus, in aphids and weeds. Together, our findings document the presence of multiple viruses in coriander and the potential role of weeds as virus reservoirs for aphid acquisition.

Estimation of anti-diabetes drug metformin in Turkiye using wastewater-based epidemiology.

Metformin is the most commonly used drug for the treatment of type 2 diabetes (T2D), which is dramatically increasing due to factors such as increasing obesity, physical inactivity, and aging of the population. Metformin analysis was carried out in composite wastewater samples seasonally collected from wastewater treatment plants in 10 cities in 2019 and 2020 30 cities in 2021 in Turkiye. Metformin was measured in all wastewater samples, with an average concentration of 97.81 μg/l in 2019, 75.19 μg/l in 2020, and 69.13 μg/l in 2021. This study was utilized to predict metformin usage in different sociodemographic regions in Turkiye using a wastewater-based epidemiology (WBE) approach. As a result of the analysis, the average metformin consumption in Turkiye was estimated to be 22.2 ± 9.6 [1.9-63.8] g/d/1,000 persons (mean ± SD [range]). Furthermore, these estimates were compared with data for time, sociodemographic characteristics, and patient numbers. Assessing the correlation with estimates and the socioeconomic classes of the cities in question revealed that cities with high-income levels had the lowest metformin use rate. Finally, the study provides supporting data aiding the development of public health strategies for decreasing the overall load of T2D across Turkiye.

Thomas Wilson Meade. 21 January 1936—24 October 2022

Tom Meade made outstanding contributions to our understanding of the role of the haemostatic (clotting) system in the causation of cardiovascular disease by combining epidemiological approaches with rigorous standardization of laboratory methods. As director of the MRC Epidemiology and Medical Care Unit (EMCU) at Northwick Park Hospital he led major prospective studies to investigate the relationship between a range of haemostatic factors and cardiovascular disease outcomes. He also led several major randomized trials of interventions to reduce cardiovascular risk, notably the Thrombosis Prevention Trial. The EMCU also undertook several landmark studies on common and often neglected conditions to improve knowledge of the burden of ill health (for example from incontinence) and effective interventions, including for low back pain and stroke rehabilitation. In his later career he also set up and led a series of large case–control studies among myocardial infarction, stroke, deep vein thrombosis and pulmonary embolism cases, together with their matched controls using a primary care database, showing elevated risks of both arterial and venous thrombosis following respiratory infections. He had many major scientific leadership roles, including playing a significant role in guiding the UK Biobank at its inception and chairing the steering committee of the Heart Protection Study Collaborative Group.

Analysis of long-term dynamics of morbidity by the method of complex assessment at different territorial levels

BACKGROUND: A comparative epidemiological analysis of the primary incidence of tuberculosis was performed using its standard approach with a generalized indicator that considers the main statistical criteria for incidence. The “sensitivity” of the method may vary depending on the population from analyzed territories.
 AIM: This study aimed to perform a comparative assessment of the epidemiology of tuberculosis (TB) in different territories based on the standard incidence rate and modified method of its integral assessment.
 MATERIALS AND METHODS: A retrospective study of the dynamics of the incidence of tuberculosis in the total population from the federal districts (FD) of Russia and participants from the Siberian Federal District (SFD) and urban municipalities of the Irkutsk Region (a structural unit of the SFD) between 2005 and 2019 was performed. Based on the obtained integral indicators, a generalized visibility coefficient was calculated.
 RESULTS: A significant decrease in the incidence of TB was found in all patients from FD and SFD participants. Assessment of the average long-term incidence rates showed that the maximum discrepancy between ranking places was inversely proportional to the size of the studied territories: 1.5 positions, at the level of the FD; two positions, at the level of regional formations; and five positions, at the level of urban settlements.
 CONCLUSIONS: The integral assessment method can be used in the primary analysis of morbidity in all types of infectious and noninfectious pathologies. The generalized morbidity criterion expands the informative possibilities of the standard indicator, contributes to the substantiation of risk areas at the initial stages of epidemiological analysis, and responds more “sensitively” to changes in the epidemiological situation in relatively small areas.

Epidemiological statistical methods: A comparative review of their implementation in public health studies in the USA and Africa

This scholarly exploration delves into the realm of epidemiological statistical methods, juxtaposing their application within the distinct public health landscapes of the United States and Africa. The study's core objective was to dissect and compare the evolution, effectiveness, and adaptability of these methods across these diverse regions, thereby enriching the understanding of global health dynamics. Embracing a qualitative methodology, the study employed advanced analytical tools and AI technologies, ensuring a thorough examination of data, and facilitating a nuanced comparative analysis. The findings reveal a marked evolution in the United States, characterized by a shift from traditional epidemiological approaches to more sophisticated, data-driven techniques. In contrast, African epidemiological practices emphasized community engagement and education in disease prevention, gradually pivoting towards non-communicable diseases and mental health. The study also illuminated the critical role of technology in modern epidemiological research, enhancing efficiency and broadening the scope of investigations. Furthermore, it highlighted the significant impact of international policies on epidemiological methods and underscored the dynamic interplay between technology and policy in shaping public health strategies. Conclusively, this study not only achieved its objectives but also offered a comprehensive view of the current state and potential future directions of epidemiological research. Recommendations emphasize the need for continued innovation in methodologies, adoption of inclusive approaches considering socioeconomic contexts, and alignment of technological advancements with policy decisions. As epidemiology continues to evolve, this study serves as a guiding light, steering future research and interventions towards more effective and equitable public health outcomes.

Piloting a Big Data Epidemiology Approach to Support Frail, Homebound, and Bedridden People.

Frail, homebound, and bedridden people (FHBP) are people living at home whose daily life is physically limited to the boundary of their houses because of their ongoing health, energy, and psychosocial or socio-functional impairments. This definition needs a scientific, systematic, and data-driven view of the distribution (frequency, pattern) and determinants (causes, risk factors) of health-related states and adverse events experienced by FHBP. Thus, we piloted a big data epidemiology approach (Multiple Correspondence Analysis and data visualization) from 300 survey responses about FHBP experiences and identified a positive correlation between perceived health status and reported impairments.