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Objective: To analyze the characteristics of highly-cited papers in Chinese Journal of Epidemiology from 2020 to 2023, and provide a basis for subsequent paper solicitation and identify research hotspots. Methods: On December 9, 2023, the citation frequency of each paper in Chinese Journal of Epidemiology from 2020 to 2023 was obtained from China National Knowledge Infrastructure. The total citation frequency of each paper was sorted using Excel 2016 software, and papers with citation frequency ≥30 were extracted for analysis. The keywords of the papers and Contents in Brief were analyzed. Results: A total of 1 317 papers were included in the analysis, of which 389, 342, 308 and 278 papers were included from 2020 to 2023. The total citation frequency was 11 873, and all papers were cited with an average citation frequency of 9. The keywords with high citation frequency in the papers included 2019-nCoV, hypertension, colorectal tumor, hand-foot-mouth disease, hepatitis B. and the average frequency of citation were 162, 77, 62, 51 and 47, respectively. There were 15 highly cited Contents in Brief in total, 11 of which are vital Contents in Brief or unique Contents in Brief, including Response to COVID-19 Epidemic, China Kadoorie Biobank, Epidemiological Research on Infectious Diseases, Healthy Ageing, Colorectal Cancer Prevention and Control, Prevention and Control of Hepatitis B, Quality Assessment of Cancer Screening Guidelines and Consensus, The 40 th Anniversary of Chinese Journal of Epidemiology , Expert Forum, Review, Standard-Protocol-Guide. The total citation frequency was 3 951, accounting for 72.6% (3 951/5 438) of highly cited papers. Conclusions: In the past four years, the highly cited papers of this journal mainly focused on the research field of emerging infectious diseases and chronic diseases. The response to the 2019-nCoV epidemic highlights the academic leading role. The effect of selecting and planning a topic, commissioning authors to write on given topics and making an arrangement in advance with a subject for contribution to vital Contents in Brief or unique Contents in Brief of this journal is pronounced, and the academic influence of the journal continues to improve.

Abstract Mendelian randomization (MR) is a powerful epidemiological method for causal inference. However, its recent surge in popularity has brought two concerning trends. First, the public availability of summary results from genome-wide association studies has led to an explosion of low-quality two-sample mendelian randomization (2SMR) studies. These studies add minimal – if any – value and overwhelm reviewers and journals. Second, the availability of large datasets with individual-level genotype data, like UK Biobank, has spurred the development and use of novel MR methods. However, some methods are being applied without proper testing, leading to misleading results, as exemplified by recent spurious findings that are being retracted and/or corrected relating to vitamin D. What can editors and peer reviewers do to handle the deluge of 2SMR studies and the premature application of highly complex MR methods? We advise editors to simply reject papers that only report 2SMR findings, with no additional supporting evidence. For reviewers receiving such papers, we provide a template for rejection. In addition, reviewers should demand rigorous testing of novel methods, including through the use of positive and negative controls before they are applied. Rejecting non-contributory 2SMR papers and imposing intensive scrutiny to novel methods is crucial if the scientific community is to reclaim MR.

Sihem Lazreg,1 Mohamed Hosny,2 Muhammad A Ahad,3 Mazen M Sinjab,4 Riadh Messaoud,5 Shady T Awwad,6 Antoine Rousseau7 1Ophthalmology Cabinet, Blida, Algeria; 2Refractive and Cornea Service, Cairo University Hospitals, Cairo, Egypt; 3Department of Ophthalmology, Anterior Segment Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 4Dr Sulaiman Al Habib Hospital, DHCC, Dubai, United Arab Emirates; 5Department of Ophthalmology, Tahar SFAR University Hospital, Mahdia, Tunisia; 6Department of Ophthalmology, American University of Beirut - Medical Center, Beirut, Lebanon; 7Department of Ophthalmology, Bicêtre Hospital, Paris-Saclay University, Le Kremlin-Bicêtre, FranceCorrespondence: Antoine Rousseau, Pierre Testas Building, Bicêtre Hospital, 78 Rue du Général Leclerc, Le Kremlin-Bicêtre, 94270, France, Tel +33145213690, Email arousseau1010@gmail.comAbstract: In the Middle East and Northern Africa (MENA), dry eye disease (DED) is often misdiagnosed or overlooked. This review summarizes a series of conversations with ophthalmologists in the region around a variety of climatic, lifestyle, and iatrogenic factors that contribute to specific features of DED in the MENA region. These considerations are further classified by patient lifestyle and surgical choices. All statements are based on discussions and formal voting to achieve consensus over three meetings. Overall, a deeper understanding of the disease characteristics of DED specific to MENA can better guide local eyecare practitioners on appropriate management and follow-up care. Additionally, population-based studies and patient and physician education on ocular surface diseases, together with the use of culturally appropriate and language-specific questionnaires can help ease the public health burden of DED in this region.Keywords: ocular surface, regional clinical practice, epidemiology, treatment, patient outcomes

Introduction: Assessments direct students towards learning. There are three types of learning: cognitive, affective, and psychomotor. While all three are interlinked, the cognitive domain, which covers knowledge and intellectuality, is foundational and can be assessed through theory examinations. Theory exams are the best way to test the cognitive domain of a learner, while practical exams can assess the psychomotor and affective domains. Since the question paper is the most important tool in theory exams, it is essential that the question paper covers relevant topics and tests all levels of cognitive learning, which encompass knowledge, comprehension, application, analysis, synthesis, and evaluation. Aim: To assess the level of cognitive domains assessed and the weightage allocated to various topics in the undergraduate summative examination question paper of community medicine. Materials and Methods: A cross-sectional study was conducted at Department of Community Medicine, Pramukh Swami Medical College and Sri Krishna Hospital, Bhaikaka University, Karamsad, Anand, Gujarat, India in which the five-year question papers (2016-2020) from five Universities were analysed to assess the level of cognitive domains and the weightage assigned to various topics. Each question was categorised as recall, comprehension, or application based on the cognitive domain it assessed. Furthermore, each question was analysed to determine the topic it pertained to, and the marks allocated to that question were assigned to the corresponding topic. Results: The majority of marks in Universities 1, 2, 3, 4, and 5 were, respectively allocated as follows: 324 (80.62%), 459 (84.66%), 453 (75.5%), 895 (89.5%), and 379 (63.16%) for questions testing the recall ability of the learners. For questions assessing comprehension ability, the marks allotted were 20 (4.87%), 0, 81 (13.5%), 65 (6.5%), and 51 (8.15%). The fewest marks were assigned to questions testing application, synthesis, or evaluation abilities. Epidemiology had the highest weightage in all five Universities, with marks of 73 (18.25%), 75 (13.89%), 93 (15.5%), 141 (14.1%), and 83 (13.83%). Conclusion: The cognitive domains assessed in the subject across all five Universities were unsatisfactory. The weightage of marks allotted to topics varied, highlighting the need to develop a question paper plan that facilitates a systematic distribution based on different levels of cognitive domains and topics.

Mendelian randomization (MR) is a powerful epidemiological method for causal inference. However, its recent surge in popularity has brought two concerning trends. First, the public availability of summary results from genome-wide association studies has led to an explosion of low-quality two-sample mendelian randomization (2SMR) studies. These studies add minimal – if any – value and overwhelm reviewers and journals. Second, the availability of large datasets with individual-level genotype data, like UK Biobank, has spurred the development and use of novel MR methods. However, some methods are being applied without proper testing, leading to misleading results, as exemplified by recent spurious findings that are being retracted and/or corrected relating to vitamin D. What can editors and peer reviewers do to handle the deluge of 2SMR studies and the premature application of highly complex MR methods? We advise editors to simply reject papers that only report 2SMR findings, with no additional supporting evidence. For reviewers receiving such papers, we provide a template for rejection. In addition, reviewers should demand rigorous testing of novel methods, including through the use of positive and negative controls before they are applied. Rejecting non-contributory 2SMR papers and imposing intensive scrutiny to novel methods is crucial if the scientific community is to reclaim MR. [ABSTRACT FROM AUTHOR]

Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE‐mediated diseases and glioma. Allergic disease stems from a Th2‐biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour‐immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro‐Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult‐type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune–glioma interactions to ultimately improve patient prognosis and survival. [ABSTRACT FROM AUTHOR]

Background: Hypertensive disorders of pregnancy (HDP) are a major cause of maternal morbidity and mortality, and their association with increased cardiovascular disease (CVD) risk represents a major public health concern. However, assessing CVD risk in women with a history of these conditions presents unique challenges, especially when studies are carried out using routinely collected data. Objectives: To summarise and describe key challenges related to the design and conduct of administrative studies assessing CVD risk in women with a history of HDP and provide concrete recommendations for addressing them in future research. Methods: This is a methodological guidance paper. Results: Several conceptual and methodological factors related to the data‐generating mechanism and study conceptualisation, design/data management and analysis, as well as the interpretation and reporting of study findings should be considered and addressed when designing and carrying out administrative studies on this topic. Researchers should develop an a priori conceptual framework within which the research question is articulated, important study variables are identified and their interrelationships are carefully considered. Conclusions: To advance our understanding of CVD risk in women with a history of HDP, future studies should carefully consider and address the conceptual and methodological considerations outlined in this guidance paper. In highlighting these challenges, and providing specific recommendations for how to address them, our goal is to improve the quality of research carried out on this topic. [ABSTRACT FROM AUTHOR]

Introduction: Assessments direct students towards learning. There are three types of learning: cognitive, affective, and psychomotor. While all three are interlinked, the cognitive domain, which covers knowledge and intellectuality, is foundational and can be assessed through theory examinations. Theory exams are the best way to test the cognitive domain of a learner, while practical exams can assess the psychomotor and affective domains. Since the question paper is the most important tool in theory exams, it is essential that the question paper covers relevant topics and tests all levels of cognitive learning, which encompass knowledge, comprehension, application, analysis, synthesis, and evaluation. Aim: To assess the level of cognitive domains assessed and the weightage allocated to various topics in the undergraduate summative examination question paper of community medicine. Materials and Methods: A cross-sectional study was conducted at Department of Community Medicine, Pramukh Swami Medical College and Sri Krishna Hospital, Bhaikaka University, Karamsad, Anand, Gujarat, India in which the five-year question papers (2016-2020) from five Universities were analysed to assess the level of cognitive domains and the weightage assigned to various topics. Each question was categorised as recall, comprehension, or application based on the cognitive domain it assessed. Furthermore, each question was analysed to determine the topic it pertained to, and the marks allocated to that question were assigned to the corresponding topic. Results: The majority of marks in Universities 1, 2, 3, 4, and 5 were, respectively allocated as follows: 324 (80.62%), 459 (84.66%), 453 (75.5%), 895 (89.5%), and 379 (63.16%) for questions testing the recall ability of the learners. For questions assessing comprehension ability, the marks allotted were 20 (4.87%), 0, 81 (13.5%), 65 (6.5%), and 51 (8.15%). The fewest marks were assigned to questions testing application, synthesis, or evaluation abilities. Epidemiology had the highest weightage in all five Universities, with marks of 73 (18.25%), 75 (13.89%), 93 (15.5%), 141 (14.1%), and 83 (13.83%). Conclusion: The cognitive domains assessed in the subject across all five Universities were unsatisfactory. The weightage of marks allotted to topics varied, highlighting the need to develop a question paper plan that facilitates a systematic distribution based on different levels of cognitive domains and topics. [ABSTRACT FROM AUTHOR]

Background: Natural language processing, such as ChatGPT, demonstrates growing potential across numerous research scenarios, also raising interest in its applications in public health and epidemiology. Here, we applied a bibliometric analysis for a systematic assessment of the current literature related to the applications of ChatGPT in epidemiology and public health. Methods: A bibliometric analysis was conducted on the Biblioshiny web-app, by collecting original articles indexed in the Scopus database between 2010 and 2023. Results: On a total of 3431 original medical articles, "Article" and "Conference paper", mostly constituting the total of retrieved documents, highlighting that the term "ChatGPT" becomes an interesting topic from 2023. The annual publications escalated from 39 in 2010 to 719 in 2023, with an average annual growth rate of 25.1%. In terms of country production over time, the USA led with the highest overall production from 2010 to 2023. Concerning citations, the most frequently cited countries were the USA, UK, and China. Interestingly, Harvard Medical School emerges as the leading contributor, accounting for 18% of all articles among the top ten affiliations. Conclusions: Our study provides an overall examination of the existing research interest in ChatGPT's applications for public health by outlining pivotal themes and uncovering emerging trends. [ABSTRACT FROM AUTHOR]

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Following up the previously published systematic review on the same topic and realizing that new studies and evidence had emerged on the matter, we conducted an update on the same research terms. With the objective of updating the information relating environmental risk factors on neurodegenerative diseases and the geographic approaches used to address them, we searched PubMed, Web of Science and Scopus for all scientific studies considering the following three domains: neurodegenerative disease, environmental atmospheric factor and geographical analysis, using the same keywords as in the previously published systematic review. From February 2020 to February 2023, 35 papers were included versus 34 in the previous period, with dementia (including Alzheimer's disease) being the most focused disease (60.0%) in this update, opposed to multiple sclerosis on the last review (55.9%). Also, environmental pollutants such as PM2.5 and NO2 have gained prominence, being represented in 65.7% and 42.9% of the new studies, opposed to 9.8% and 12.2% in the previous review, compared to environmental factors such as sun exposure (5.7% in the update vs 15.9% in the original). The mostly used geographic approach remained the patient's residence (82.9% in the update vs 21.2% in the original and 62.3% in total), and remote sensing was used in 45.7% of the new studies versus 19.7% in the original review, with 42.0% of studies using it globally, being the second most common approach, usually to compute the environmental variable. This review has been registered in PROSPERO with the number CRD42020196188. [ABSTRACT FROM AUTHOR]

The increasing prevalence of diabetes worldwide, including in Mexico, presents significant challenges to healthcare systems. This has a notable impact on hospital admissions, as diabetes is considered an ambulatory care-sensitive condition, meaning that hospitalizations could be avoided. This is just one example of many challenges faced in the medical and public health fields. Traditional healthcare methods have been effective in managing diabetes and preventing complications. However, they often encounter limitations when it comes to analyzing large amounts of health data to effectively identify and address diseases. This paper aims to bridge this gap by outlining a comprehensive methodology for non-physicians, particularly data scientists, working in healthcare. As a case study, this paper utilizes hospital diabetes discharge records from 2010 to 2023, totaling 36,665,793 records from medical units under the Ministry of Health of Mexico. We aim to highlight the importance for data scientists to understand the problem and its implications. By doing so, insights can be generated to inform policy decisions and reduce the burden of avoidable hospitalizations. The approach primarily relies on stratification and standardization to uncover rates based on sex and age groups. This study provides a foundation for data scientists to approach health data in a new way. Dataset License: CC-BY [ABSTRACT FROM AUTHOR]

Simple Summary: Much research has been conducted on the causes of childhood cancer, but many areas of uncertainty remain. We conducted a detailed search of recent studies investigating the causes of childhood cancer. Our findings, based on publications from 2014 to 2021, are summarized by topic in three separate papers: factors acting during childhood (Paper 1), factors relating to the parents and pregnancy (Paper 2), and factors relating to the environment (Paper 3). In this first paper, we summarize convincing evidence from studies that show increased childhood cancer risk associated with genetic cancer predisposition, birth defects, prior cancer, medical ionizing radiation, organ transplantation and exposure to cancer-causing viruses, and a reduced risk associated with some childhood vaccinations. Other factors discussed in this paper include the impact of the child's diet, allergies, medications, and body mass index. This review of factors associated with childhood cancer may help evidence-based efforts to reduce cancer in our pediatric populations. Purpose: To review the childhood risk factors for pediatric cancer (diagnosis before age 20). Methods: We conducted literature searches using Ovid Medline and Scopus to find primary research studies, review articles, and meta-analyses published from 2014 to 3 March 2021. Results: Strong evidence indicates that an array of genetic and epigenetic phenomena, structural birth defects, and chromosomal anomalies are associated with an increased risk of various childhood cancers. Increased risk is also associated with prior cancer, likely due to previous treatment agents and therapeutic ionizing radiation. Convincing evidence supports associations between several pediatric cancers and ionizing radiation, immunosuppression, and carcinogenic virus infection both in healthy children and in association with immune suppression following organ transplantation. Breastfeeding and a childhood diet rich in fruits and vegetables appears to reduce the risk of pediatric leukemia but the evidence is less strong. Childhood vaccination against carcinogenic viruses is associated with a lower risk of several cancers; there is less strong evidence that other childhood vaccinations more broadly may also lower risk. Ultraviolet (UV) radiation is associated with increased melanoma risk, although most melanomas following childhood UV exposure occur later, in adulthood. Evidence is weak or conflicting for the role of body mass index, other childhood infections, allergies, and certain treatments, including immunomodulator medications and human growth therapy. [ABSTRACT FROM AUTHOR]

Mathematical models within the Ross–Macdonald framework increasingly play a role in our understanding of vector-borne disease dynamics and as tools for assessing scenarios to respond to emerging threats. These threats are typically characterized by a high degree of heterogeneity, introducing a range of possible complexities in models and challenges to maintain the link with empirical evidence. We systematically identified and analysed a total of 77 published papers presenting compartmental West Nile virus (WNV) models that use parameter values derived from empirical studies. Using a set of 15 criteria, we measured the dissimilarity compared with the Ross–Macdonald framework. We also retrieved the purpose and type of models and traced the empirical sources of their parameters. Our review highlights the increasing refinements in WNV models. Models for prediction included the highest number of refinements. We found uneven distributions of refinements and of evidence for parameter values. We identified several challenges in parametrizing such increasingly complex models. For parameters common to most models, we also synthesize the empirical evidence for their values and ranges. The study highlights the potential to improve the quality of WNV models and their applicability for policy by establishing closer collaboration between mathematical modelling and empirical work. [ABSTRACT FROM AUTHOR]

In recent years, the proliferation of health data sources due to computer technologies has prompted the use of visualization techniques to tackle epidemiological challenges. However, existing reviews lack a specific focus on the spatial and temporal analysis of epidemiological data using visualization tools. This study aims to address this gap by conducting a scoping review following the PRISMA-ScR guidelines, examining the literature from 2000 to 2024 on spatial–temporal visualization techniques when applied to epidemics, across five databases: PubMed, IEEE Xplore, Scopus, Google Scholar, and ACM Digital Library until 24 January 2024. Among 1312 papers reviewed, 114 were selected, emphasizing aggregate measures, web platform tools, and geospatial data representation, particularly favoring choropleth maps and extended charts. Visualization techniques were predominantly utilized for real-time data presentation, trend analysis, and predictions. Evaluation methods, categorized into standard methodology, user experience, task efficiency, and accuracy, were observed. Although various open-access datasets were available, only a few were commonly used, mainly those related to COVID-19. This study sheds light on the current trends in visualizing epidemiological data over the past 24 years, highlighting the gaps in standardized evaluation methodologies and the limited exploration of individual epidemiological data and diseases acquired in hospitals during epidemics. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a global pandemic, however, estimating its burden is a complex process. As a result, many countries rely on global estimates to infer burden within their own setting. With a growing number of recent publications quantifying AMR burden in Australia, and an expansion of surveillance programs, enumerating AMR mortality for Australia is feasible. We aimed to leverage existing published data to assess methodological factors contributing to the considerable variation in AMR-related mortality and provide two reliable estimates of AMR mortality in Australia. This is a necessary step towards generating meaningful measures of AMR burden in Australia. What is known about the topic? Antimicrobial resistance is a significant global health threat, but estimating the burden of disease is complicated by data challenges. What does this paper add? This paper highlights progress in estimating the number of people dying from antimicrobial resistance in Australia and highlights the importance of rigorous antimicrobial resistance mortality estimates in Australia to assess burden of disease. What are the implications for practitioners? Practitioners should use only rigorous estimates of burden of disease to inform actions on reducing the threat of antimicrobial resistance. [ABSTRACT FROM AUTHOR]

By applying AI techniques to a variety of pandemic-relevant data, artificial intelligence (AI) has substantially supported the control of the spread of the SARS-CoV-2 virus. Along with this, epidemiological machine learning studies of SARS-CoV-2 have been frequently published. While these models can be perceived as precise and policy-relevant to guide governments towards optimal containment policies, their black box nature can hamper building trust and relying confidently on the prescriptions proposed. This paper focuses on interpretable AI-based epidemiological models in the context of the recent SARS-CoV-2 pandemic. We systematically review existing studies, which jointly incorporate AI, SARS-CoV-2 epidemiology, and explainable AI approaches (XAI). First, we propose a conceptual framework by synthesizing the main methodological features of the existing AI pipelines of SARS-CoV-2. Upon the proposed conceptual framework and by analyzing the selected epidemiological studies, we reflect on current research gaps in epidemiological AI toolboxes and how to fill these gaps to generate enhanced policy support in the next potential pandemic. [ABSTRACT FROM AUTHOR]

Leishmaniasis is one of the dangerous diseases that are widespread in the world. Its vectors are mosquitoes. One of the main reasons for the significant increase in the number of leishmaniasis is that the methods of combating vectors are not widely known. It is very important to prevent the disease and determine its species composition. The article shows various methods used to catch mosquitoes. This methods are widely used in research work. When applying the used methods, care should be taken not to disturb the chemical balance and not cause changes in species composition. In the future, steps should be taken to find safer methods. [ABSTRACT FROM AUTHOR]

This document discusses the global concern over antimicrobial-resistant (AMR) bacterial pathogens causing infections in various settings. The document emphasizes the need for collaboration between specialists in microbiology, medicine, molecular biology, and bioinformatics to understand the mechanisms of resistance development and dissemination. The document also highlights the importance of molecular and whole-genome sequencing methods for detecting global clones and investigating AMR genes. The special issue includes papers on the genomic analysis of specific bacterial strains, molecular and genomic epidemiology studies, and novel methods for bacterial detection and prevention. These findings are valuable for researchers studying bacterial pathogen surveillance, detection, and treatment. [Extracted from the article]

An ensemble n-sub-epidemic modeling framework that integrates sub-epidemics to capture complex temporal dynamics has demonstrated powerful forecasting capability in previous works. This modeling framework can characterize complex epidemic patterns, including plateaus, epidemic resurgences, and epidemic waves characterized by multiple peaks of different sizes. In this tutorial paper, we introduce and illustrate SubEpiPredict, a user-friendly MATLAB toolbox for fitting and forecasting time series data using an ensemble n-sub-epidemic modeling framework. The toolbox can be used for model fitting, forecasting, and evaluation of model performance of the calibration and forecasting periods using metrics such as the weighted interval score (WIS). We also provide a detailed description of these methods including the concept of the n-sub-epidemic model, constructing ensemble forecasts from the top-ranking models, etc. For the illustration of the toolbox, we utilize publicly available daily COVID-19 death data at the national level for the United States. The MATLAB toolbox introduced in this paper can be very useful for a wider group of audiences, including policymakers, and can be easily utilized by those without extensive coding and modeling backgrounds. [ABSTRACT FROM AUTHOR]

The purpose of research is to seek answers and new knowledge. When conducted properly and systematically, research adds to humanity's corpus of knowledge and hence to our general advancement. However, this is only possible if reported research is accurate and transparent. Guidelines for all the major types of studies (STROBE, CONSORT, PRISMA, MOOSE, STARD, and SPIRIT) have been developed and refined over the years, and their inception, development, and application are briefly discussed in this paper. Indeed, there are currently over 250 of these guidelines for various types of medical research, and these are published by the EQUATOR network. This paper will also briefly review progress in acceptance and adoption of these guidelines. [ABSTRACT FROM AUTHOR]

Introduction: Problematic usage of the internet (PUI) is perhaps one of the most frequently studied phenomena of the 21st century receiving increasing attention in both scientific literature and the media. Despite intensive research there have been relatively few meaningful studies among elementary school students in Hungary and worldwide, who may be considered as a high-risk population with regard to problematic internet use. The aim of our study was to carry out a complex research focusing on the prevalence and risk factors of PUI among elementary school children aged 10–15 years (Grade 5–8). Methods: Demographics included were gender, age, place of stay, type of residence, family type, parental education, start of internet use, used devices, daily internet use, purpose of internet use, internet accounts, ways of keeping in touch with friends and sporting activities. PUI was evaluated using the paper-based version of the Potentially Problematic Use of the Internet Questionnaire. Results: Overall, 2000 paper-based questionnaires were successfully delivered and the final analysis included 1168 responses (overall response rate 58.4%). Mean age was 12.55 ± 1.24 years. Female gender (OR = 2.760, p = 0,006, CI 95% 0.065 to 0.384), younger age (11–12 years) (OR = 3.812, p < 0.001, 95% CI: 1.747–4.731), early exposure to the internet (OR = 3.466, p = 0.001, 95% CI 1.535–5.446), living in a small village (OR = 1.081, p = 0.002, 95% CI 1.041–1.186) urgency to answer online (OR = 4.677, p < 0.001, 95% CI: 2.714–6.639), decreased frequency of personal contact with friends (OR = 2.897, p = 0.004, 95% CI: 1.037–1.681), spending more than 6 h online (OR = 12.913, p < 0.001, 95% CI: 10.798–14.892), morning and nighttime internet use (OR = 3.846, p < 0.001, CI 95% 1.886–5.810) and never doing any sports (OR = 2.016, p = 0.044, 95% CI: 1.050–3.354) were independently associated with problematic internet use. Conclusions: Based on the results of our questionnaire survey more than 10% seemed to be problematic users in our study population, which is a relatively high rate. Early exposure to the internet as well as younger age were strongly related to this phenomenon. Duration of being online as well as daily time interval of internet use are important predisposing factors. Scarcely studied social factors such as being online at the expense of personal relationships and the lack of physical activity should be payed more attention to prevent the development of PUI. [ABSTRACT FROM AUTHOR]

Functional neurological disorder (FND), formerly called conversion disorder, is a condition characterized by neurological symptoms that lack an identifiable organic purpose. These signs, which can consist of motor, sensory, or cognitive disturbances, are not deliberately produced and often vary in severity. Its diagnosis is predicated on clinical evaluation and the exclusion of other medical or psychiatric situations. Its treatment typically involves a multidisciplinary technique addressing each of the neurological symptoms and underlying psychological factors via a mixture of medical management, psychotherapy, and supportive interventions. Recent advances in neuroimaging and a deeper exploration of its epidemiology, pathophysiology, and clinical presentation have shed new light on this disorder. This paper synthesizes the current knowledge on FND, focusing on its epidemiology and underlying mechanisms, neuroimaging insights, and the differentiation of FND from feigning or malingering. This review highlights the phenotypic heterogeneity of FND and the diagnostic challenges it presents. It also discusses the significant role of neuroimaging in unraveling the complex neural underpinnings of FND and its potential in predicting treatment response. This paper underscores the importance of a nuanced understanding of FND in informing clinical practice and guiding future research. With advancements in neuroimaging techniques and growing recognition of the disorder's multifaceted nature, the paper suggests a promising trajectory toward more effective, personalized treatment strategies and a better overall understanding of the disorder. [ABSTRACT FROM AUTHOR]

Objective: To systematically review the progress, advantages, disadvantages, precautions and future trends of virtual simulation technology used in epidemiology teaching. Methods: A systematical literature retrieval was conducted by using PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Wanfang Data and VIP Paper Check System with key words of epidemiology, teaching and virtual simulation, and the literatures included were screened and classified with narrative integration method. Chinese virtual simulation teaching platforms were used to select the literatures about existing epidemiology virtual simulation teaching projects for integration and analysis. Results: A total of 22 articles were included (7 in Chinese and 15 in English), most of which were teaching projects for students majoring in Public Health. We also found 24 national first-class courses and 21 provincial first-class courses in virtual simulation of epidemiology in China. The application of virtual simulation technology in epidemiology education is still in its infancy, and the interaction degree is mostly moderate. It is mainly used in three scenarios: improving the visualization degree of complex concepts and structures, training the operational skills through low-risk and low-cost virtual environment, serving as an effective supplement to the teaching of epidemiological field investigation and response to public health emergencies. In terms of effect, it is conducive to students' understanding of epidemiology related phenomena and principles, and has the advantages of breaking through time and space constraints, reducing teaching costs and risks, improving students' attention and satisfaction and so on. However, it also faces the lack of foundation in the initial stage, and some students have problems such as psychological and physiological discomfort. In the future, we need to optimize the development process, program design and so on. At the same time, we should conduct more in-depth research on cost calculation, effect evaluation and curriculum integration. Conclusions: The application of virtual simulation technology in epidemiology education is an important part of training high-level applied public health talents. We encourage to actively carry out virtual simulation teaching in epidemiology, and train public health talents with Chinese characteristics.

Population screening for breast cancer (BC) is currently offered in the UK for women aged 50 to 71 with the aim of reducing mortality. There is additional screening within the national programme for women identified as having a very high risk of BC. There is growing interest in further risk stratification in breast screening, which would require a whole population risk assessment and the subsequent offer of screening tailored to the individual's risk. Some women would be offered more intensive screening than others or no screening. This might provide a better balance of screening benefits and harms for each individual than the current population age-based programme alone. The UK National Screening Committee (UK NSC) is considering using decision-analytic and other models to evaluate different risk stratification screening strategies and identify remaining gaps in evidence. This paper reports the proceedings of a UK NSC workshop where experts in the field discussed both risk prediction models, as well as decision-analytic models providing a benefit-harm analysis/economic evaluation of risk-stratified screening programmes (see Table 1). The aim of the meeting was to present and discuss the current work of experts, including some data which had not been published at the time of the meeting, to inform the UK NSC. The workshop was not intended to present a balanced evaluation of how to deliver screening in future. Areas for further work identified included methods for comparing models to assess accuracy, the optimum risk assessment tools, the digital screening infrastructure, acceptability of stratification, choice of screening test and reducing inequalities. A move to risk stratification of the whole programme would require a careful phased introduction with continuing assessment of real-world evidence during deployment. [ABSTRACT FROM AUTHOR]

Epilepsy is a common neurological condition in dogs. Analysis of primary care populations across countries can provide a more complete understanding of the epidemiology of this condition and provide context for spectrum of care discussions. This narrative literature review was aimed at understanding canine epilepsy/seizure prevalence in primary care populations, and changes in occurrence across geography, culture, and socioeconomic status. There are few studies to give insight into the true general population of epileptic canines and there is inconsistency in the literature regarding the standards applied for epilepsy diagnosis across primary care and referral practices. Therefore, the future focus should be on more epidemiological research in primary care and mixed populations, more veterinary education to standardize use of medical guidelines in primary care settings, and increased awareness of the benefits of having pet insurance to mitigate the potentially substantial cost of care for dogs with epilepsy. [ABSTRACT FROM AUTHOR]

This article examines epidemics and disease prevention within the War Relocation Authority camps for Japanese Americans during World War II. Although scholars and activists have noted the limits and inadequacies of medical care within the camps, little attention has been given to the actions of camp administrators in curtailing outbreaks of deadly diseases such as polio and tuberculosis, including universal vaccination requirements and the use of quarantine orders. Disease in the camps resulted in cases of social isolation and ostracization and further exacerbated the stresses of life among the confined. Meanwhile, this article explores the use of the camps as sites of scientific study. Administrators and anthropologists documented cases of camp epidemics and published their results in journals on public health. [ABSTRACT FROM AUTHOR]

Background: COVID-19 will not be the last pandemic of the twenty-first century. To better prepare for the next one, it is essential that we make honest appraisals of the utility of different responses to COVID. In this paper, we focus specifically on epidemiologic forecasting. Characterizing forecast efficacy over the history of the pandemic is challenging, especially given its significant spatial, temporal, and contextual variability. In this light, we introduce the Weighted Contextual Interval Score (WCIS), a new method for retrospective interval forecast evaluation. Methods: The central tenet of the WCIS is a direct incorporation of contextual utility into the evaluation. This necessitates a specific characterization of forecast efficacy depending on the use case for predictions, accomplished via defining a utility threshold parameter. This idea is generalized to probabilistic interval-form forecasts, which are the preferred prediction format for epidemiological modeling, as an extension of the existing Weighted Interval Score (WIS). Results: We apply the WCIS to two forecasting scenarios: facility-level hospitalizations for a single state, and state-level hospitalizations for the whole of the United States. We observe that an appropriately parameterized application of the WCIS captures both the relative quality and the overall frequency of useful forecasts. Since the WCIS represents the utility of predictions using contextual normalization, it is easily comparable across highly variable pandemic scenarios while remaining intuitively representative of the in-situ quality of individual forecasts. Conclusions: The WCIS provides a pragmatic utility-based characterization of probabilistic predictions. This method is expressly intended to enable practitioners and policymakers who may not have expertise in forecasting but are nevertheless essential partners in epidemic response to use and provide insightful analysis of predictions. We note that the WCIS is intended specifically for retrospective forecast evaluation and should not be used as a minimized penalty in a competitive context as it lacks statistical propriety. Code and data used for our analysis are available at https://github.com/maximilian-marshall/wcis. [ABSTRACT FROM AUTHOR]

In this paper, we propose a numerical algorithm to obtain the optimal epidemic parameters for a time-dependent Susceptible-Unidentified infected-Confirmed (tSUC) model. The tSUC model was developed to investigate the epidemiology of unconfirmed infection cases over an extended period. Among the epidemic parameters, the transmission rate can fluctuate significantly or remain stable due to various factors. For instance, if early intervention in an epidemic fails, the transmission rate may increase, whereas appropriate policies, including strict public health measures, can reduce the transmission rate. Therefore, we adaptively estimate the transmission rate to the given data using the linear change points of the number of new confirmed cases by the given cumulative confirmed data set, and the time-dependent transmission rate is interpolated based on the estimated transmission rates at linear change points. The proposed numerical algorithm preprocesses actual cumulative confirmed cases in India to smooth it and uses the preprocessed data to identify linear change points. Using these linear change points and the tSUC model, it finds the optimal time-dependent parameters that minimize the difference between the actual cumulative confirmed cases and the computed numerical solution in the least-squares sense. Numerical experiments demonstrate the numerical solution of the tSUC model using the optimal time-dependent parameters found by the proposed algorithm, validating the performance of the algorithm. Consequently, the proposed numerical algorithm calculates the time-dependent transmission rate for the actual cumulative confirmed cases in India, which can serve as a basis for analyzing the COVID-19 pandemic in India. [ABSTRACT FROM AUTHOR]

Background: The IoT and big data are newer technologies that can provide substantial support for healthcare systems, helping them overcome their shortcomings. The aim of this paper was to analyze the relevant literature descriptively, thematically, and chronologically from an interdisciplinary perspective in a holistic way to identify the most prolific research entities and themes. Methods: Synthetic knowledge synthesis qualitatively and quantitatively analyzes the production of literature through a combination of descriptive bibliometrics, bibliometric mapping, and content analysis. For this analysis, the Scopus bibliometric database was used. Results: In the Scopus database, 2272 publications were found; these were published between 1985 and 10 June 2024. The first article in this field was published in 1985. Until 2012, the production of such literature was steadily increasing; after that, exponential growth began, peaking in 2023. The most productive countries were the United States, India, China, the United Kingdom, South Korea, Germany, and Italy. The content analysis resulted in eight themes (four from the perspective of computer science and four from the perspective of medicine) and 21 thematic concepts (8 from the perspective of computer science and 13 from the perspective of medicine). Conclusions: The results show that the IoT and big data have become key technologies employed in preventive healthcare. The study outcomes might represent a starting point for the further development of research that combines the multidisciplinary aspects of healthcare. [ABSTRACT FROM AUTHOR]

In this study, we investigate different epidemic control scenarios through theoretical analysis and numerical simulations. To account for two important types of control at the early ascending stage of an outbreak, nonmedical interventions, and medical treatments, a compartmental model is considered with the first control aimed at lowering the disease transmission rate through behavioral changes and the second control set to lower the period of infectiousness by means of antiviral medications and other forms of medical care. In all experiments, the implementation of control strategies reduces the daily cumulative number of cases and successfully "flattens the curve". The reduction in the cumulative cases is achieved by eliminating or delaying new cases. This delay is incredibly valuable, as it provides public health organizations with more time to advance antiviral treatments and devise alternative preventive measures. The main theoretical result of the paper, Theorem 1, concludes that the two optimal control functions may be increasing initially. However, beyond a certain point, both controls decline (possibly causing the number of newly infected people to grow). The numerical simulations conducted by the authors confirm theoretical findings, which indicates that, ideally, around the time that early interventions become less effective, the control strategy must be upgraded through the addition of new and improved tools, such as vaccines, therapeutics, testing, air ventilation, and others, in order to successfully battle the virus going forward. [ABSTRACT FROM AUTHOR]

Background: Epidemiological studies of long-term exposure to outdoor air pollution have consistently documented associations with morbidity and mortality. Air pollution exposure in these epidemiological studies is generally assessed at the residential address, because individual time-activity patterns are seldom known in large epidemiological studies. Ignoring time-activity patterns may result in bias in epidemiological studies. The aims of this paper are to assess the agreement between exposure assessed at the residential address and exposures estimated with time-activity integrated and the potential bias in epidemiological studies when exposure is estimated at the residential address. Main body: We reviewed exposure studies that have compared residential and time-activity integrated exposures, with a focus on the correlation. We further discuss epidemiological studies that have compared health effect estimates between the residential and time-activity integrated exposure and studies that have indirectly estimated the potential bias in health effect estimates in epidemiological studies related to ignoring time-activity patterns. A large number of studies compared residential and time-activity integrated exposure, especially in Europe and North America, mostly focusing on differences in level. Eleven of these studies reported correlations, showing that the correlation between residential address-based and time-activity integrated long-term air pollution exposure was generally high to very high (R > 0.8). For individual subjects large differences were found between residential and time-activity integrated exposures. Consistent with the high correlation, five of six identified epidemiological studies found nearly identical health effects using residential and time-activity integrated exposure. Six additional studies in Europe and North America showed only small to moderate potential bias (9 to 30% potential underestimation) in estimated exposure response functions using residence-based exposures. Differences of average exposure level were generally small and in both directions. Exposure contrasts were smaller for time-activity integrated exposures in nearly all studies. The difference in exposure was not equally distributed across the population including between different socio-economic groups. Conclusions: Overall, the bias in epidemiological studies related to assessing long-term exposure at the residential address only is likely small in populations comparable to those evaluated in the comparison studies. Further improvements in exposure assessment especially for large populations remain useful. [ABSTRACT FROM AUTHOR]