Introduction: A good understanding of biostatistics can improve clinical thinking, decision-making, evaluations, and medical research. Undoubtedly, medical professionals are becoming aware of the importance of learning and applying biostatistical methods in their research. This study was done to assess the knowledge and attitude among medical graduates regarding the role and application of biostatistics in medical science. Method: The study was a cross-sectional study conducted in a tertiary care teaching hospital among 120 medical students pursuing MBBS third and final year. Systematic random sampling was used to select the study participants. A pretested validated semi-structured questionnaire was used for data collection. Results: Majority of the study participants, strongly agree that the subject helps in interpretation (75.8%), and is important in medical practice (61.7%). However, 85% of the study participants feel that software is difficult to use. 90% of the study participants find the subject hard to understand. The mean score of subject content, understanding, the current impact was significantly higher among the fourth-year students than the third-year students. There was no significant difference between the genders. Conclusion: Introduction of data collection sessions and appraisal of excerpts in published articles can provide practical knowledge and accentuate the role of bio statistics in health care.

This article is a direct consequence of the authors' desire to discuss the role of statistics in data analysis. The analysis of coronavirus (COVID-19) databases are used as to show simple, but powerful statistical frameworks. We do believe that models for assessing future trends in temporal data in general, and in cases and/or deaths of COVID-19, belongs to the area of (Bio)Statistics. Just as engineers use knowledge of physics, chemistry and often architecture, when constructing bridges, buildings and roads, statisticians use knowledge of mathematics, computer science and even physics for modelling, analysing, and forecasting in order to transform data into information. While the statistician's contribution is rarely acknowledged, everyone knows that a building is a work of an engineer. Nonetheless, nowadays statistics has been gaining the attention that it deserves due to the rise of big data and data science that was built on the foundationsof statistics. This article shows that, even with only basic knowledge of statistics, one can adequately collaborate with the community in dealing with very important issues such as the COVID-19 numbers. In order to model and to obtain predictions we use well-known distributions to statisticians working on survival analysis: gamma, Weibull and log-normal distributions. We also make use of singular spectrum analysis, a simple non-parametric time series methodology, for an analogous purpose. Survival analysis is a research area widely used in Biostatistics and even in Reliability, while time series analysis is widely used across areas where the data is measured along the time.

After the fruitful completion of Human Genetics 2020 which is happened in the month of March 16-17, 2020 in Frankfurt, Germany. With the grace of success, we are now delighted to share the experience in the conference. The stage is has laid the road all the scientists in the field of genetics and medicine. The stage that gives an ideal combination of brilliant science, an open environment and enables participants and speakers to focus effectively on the scholastic exchange of thoughts and relevant experiences that also encompasses the entire scope of Human genetic and Clinical Microbiology. Francis Crick, the famous face behind the identification of DNA structure, once said, “Almost all aspects of life are engineered at the molecular level, and without understanding molecules we can only have a very sketchy understanding of life itself ” This conference will provide a vibrant atmosphere and venue for Human genetics and medicine scientists to present their findings, investigations and studies and report on them. Most scientists, clinical therapeutics, bioinformatics and statistics, gene editing and gene therapy fields have undergone major advances in recent years, driven by analytical techniques and novel work. In addition, such work remains a lively research field with escalating applications and innovative developing encounters. Human genetics Congress 2020 seeks original and high-quality contributions in the areas of Bio informatics and Statistics, Cancer genetics and Genomics, Cardiovascular genetics, Epigenetics, Genetic Counselling, Immunology and other related fields of Genetics and Therapeutics allow researchers to gage physiological impacts and scan for adverse reactions to tranquilizations.

A set of 157 multiple choice quiz questions for biostatistics courses, organized and searchable by 18 concepts/skills.

La investigación se realizó con el objetivo de determinar la relación entre el estrés académico y el aprendizaje de la asignatura Bioestadística en estudiantes de Ciencias de la Salud de la Universidad Técnica de Manabí. Se desarrolló metodológicamente desde el tipo descriptiva – correlacional transeccional, con una muestra poblacional de 367 estudiantes de la facultad de ciencias de la salud. La correlación de Pearson entre estrés académico y aprendizaje en Bioestadística tiene un resultado de -0,048 lo cual indica que existe correlación lineal e inversamente proporcional entre las variables, siendo que el aprendizaje en Bioestadística es un factor que genera estrés académico en los estudiantes. La apatía se genera como un factor de riesgo que sirve de base para la profundización de aptitudes no favorables por parte de los estudiantes, entre las cuales se hace mención de la desmotivación, percepción negativa de la materia y de los profesores.

Demographic transitions accompanied with epidemiological shifts are affecting many countries around the globe. These apprehensions have raised the concern for constructing and sustaining healthcare systems especially among resource-constrained low- and middle-income-countries (LMICs) such as India. Introducing Health-Technology-Assessment (HTA) in the educational initiatives could support planners and policy-makers in formulating evidence-based-decision-making along with tackling inequalities/inefficiencies and promoting cost-effectiveness in resource allocation. A mapping exercise has been undertaken for examining the feasibility and implementation of HTA curriculum in the existing courses in India. To gain best possible insight on HTA curriculum, a situational analysis was conducted using systematic search strategy through search engines such as Google, Google Scholar, ProQuest and PubMed. Currently, seventy-one institutes in India are offering one or more courses through regular mode at undergraduate/postgraduate/diploma-certificate/doctorate-level pertaining to Medical-technology (MT), Biostatistics (BS), and Health-economics (HE). MT was offered in 37 institutes (52.12%), followed by BS in 23 (32.39%), and HE in nine (12.67%). Only two institutes (2.81%) are offering certificate-courses on HTA, mainly confined in virtual modules. This review reveals noticeable gaps in the existing curriculum in India and necessitates a novel academic initiative by introducing HTA in a full-fledged manner. Reforms in the research and educational initiatives need to be brought for promoting awareness regarding HTA. The application of domain needs to be widened from the field of health-policy formulators to research and teaching. This should be further strengthened with the strong academic collaborations to generate replicable findings, address challenges, and offer solutions for existing threats to HTA.

In [1] the authors proposed a new ”transmuted transmuted – G (TT–G) family” of distributions.The authors’ assertion that probability distribution (in some particular cases) pro-duces very good results in approximating specific data from different fields such aspopulation dynamics, biostatistics, survival analysis and others has encouraged us toconduct further studies on ” saturation ” in Hausdorff sense of the corresponding com-mutative function to the horizontal asymptote.We also analyze some experimental data.The experiments show that in some cases the use of the model proposed in [1] andanalyzed in this article with ”respect to the Hausdorff distance” is satisfactory.Numerical examples, illustrating our results are presented using programming en-vironment CAS Mathematica.

Biostatistics classes can cause many medical students to feel frustrated and frantic. Why is biostatistics part of the body of knowledge that is deemed essential and fundamental for the medical student and eventual practitioner? This is a question that many perplexed (because of trying to comprehend biostatistics) medical students ask. To reiterate, not perceiving the practical role (not just the test-taking role) of biostatistics may didn’t better motivate medical students to learn–and avoid want to learn–the language, purpose and practicality of biostatistics.

Objective: The objectives of the present study were to evaluate the academic self-efficacy, content knowledge and confidence in these responses, as well as attitudes of students in an undergraduate biostatistics course. Design: The study was a cross-sectional analytical design. Setting: The study was carried out in Masinde Muliro University of science and technology Sample: Sampling frame consisting of 114 students who had at least taken a biostatistics course. Probability sampling technique of purposive sampling method was applied to select the students. ( n = 114 ) Analysis: Data were analyzed through path analysis and confirmatory factor analysis. Main measures: Self-efficacy, confidence, attitude and knowledge Results: The estimation of this hypothesized structural model yielded an acceptable fit to the data, χ2 =45.9, df = 2; χ 2 /df ratio =22.123 (good), CFI = .933; RMSEA = .071, with 90% C.I. = .044 - .083, SRMR = .078. Attitude was a direct predictor of self-efficacy (β = .490, p < .001), confidence was a direct predictor of self-efficacy (β = .400, p < .001), self-efficacy was a direct predictor of knowledge (β = .515, p < .001). Conclusion: The study concludes that academic self-efficacy and optimism were strongly related to performance. Therefore, this study supports previous literature that found academic self-efficacy affects the success of students in the sciences. Recommendation: Educators should be aware of students' personality antecedents in order to improve their students' beliefs about their capabilities to master different areas of coursework. Article visualizations:

Different longstanding and emerging challenges for public health have been identified including population ageing, migration, infectious and non-communicable diseases, the environment and climatic changes, increasing risks of misinformation and chronic underinvestment. The multi- and inter-disciplinary public health approach - including biology, epidemiology, biostatistics, anthropology and public policy - raises the need to train experienced professionals in different fields. The education on these matters is fundamental to ensure the human well-being. In the last years, education in schools of public health is changing in response to new evidence-based knowledge, opportunities for improvement and scientific discoveries. In this manuscript the current scenario of teaching Hygiene in all the Italian degree courses in Biology were reviewed and summarized and the most excellent examples of academic training offer of Public Health for Biologists worldwide were provided and discussed as a source of inspiration for novel Masters and PhD degree programmes in Italy.

Reasons to Believe: Biostatistics and Methodology for the Neurosurgeon.

Trophic metacommunity ecology brings together the spatial thinking of metacommunity ecology and the complexity of food web ecology. While theoretical development in this field has been bountiful, empirical development has been slower. Using a diverse methodology, I bring together three different empirical approaches to understand trophic metacommunities as exemplified by bromeliads macro-invertebrates. First, I used Markov network analysis to study the effect of regional environmental gradients on community composition and trophic interactions. I found that a gradient in precipitation underlies the spatial turnover of some species and that the interactions of certain predators differed due to differences in bromeliad water volume. Second, I combined experimental feeding trials and a food web model to study the effect of body size diversity at the local scale on food web dynamics. I found that predator persistence was maximized when the minimum prey size in the community was intermediate, but as prey diversity increased the minimum body size could take a broader range of values due to Jensen’s inequality. Third, I used population genetics to estimate dispersal kernels of a predator and a prey. I then used these empirical estimates of dispersal kernels and feeding rates to parameterize a trophic metacommunity model, to study the effect of differences in dispersal between a predator and a prey on persistence. From the empirical dispersal kernel estimates, I found that the prey dispersed up to 25 km whereas the predator dispersed up to 200 m. From the trophic metacommunity model, I found that differences in dispersal rates were sufficient to generate differences in occupancy of our modelled landscape, without requiring variation in the abiotic niche. None of this work would have been possible without strong programming skills and a good understanding of statistics. In my final chapter, I studied the effect of using cognitive load theory to design R programming assignments for undergraduate biostatistics courses. I found that students that learned R through our assignments rated their programming ability higher and were more likely to put the usage of R as a skill in their CVs than control students.

The integrated approach to teaching Biostatistics and Epidemiology at Columbia

On March 26 to 28, 2018, the National Institute of Environmental Health Sciences' (NIEHS) National Toxicology Program (NTP), a part of the US National Institutes of Health (NIH), convened a three-day Technical Reports Peer Review Panel meeting in Research Triangle Park, NC, to review the NTP's draft reports on their carcinogenesis studies of cell-phone radio-frequency (RF) radiation in mice and rats [1]. The invited 14-member peer-review panel included three electrical engineering professors, 10 pathologists and toxicologists (three from academia and seven from industry), and one biostatistician; none were from the cell-phone industry.

Diagnostic tests are of vital importance in a number of veterinary fields and are essential for decision-making by veterinary practioners, researchers and the veterinary authorities. The development and evaluation of laboratory diagnostic tests as well as the interpretation of test results engage a number of different veterinary disciplines including virologists, parasitologists, bacteriologists, laboratory experts, clinicians as well as epidemiologists and biostatisticians. This thesis was devised shortly after the section of epidemiology came into existence at the Vetsuisse Faculty end of 2009. The aim is to interrelate veterinary epidemiology - being closely linked to virology, parasitology, bacteriology and clinical medicine - with biostatistics. Thus allowing innovative concepts and recent software developments to provide solutions and answers in our veterinary field. After a brief introduction into diagnostic tests, the thesis is structured into three main parts. First, from a laboratory perspective, aspects of analytical sensitivity and specificity are illustrated by three peer-reviewed papers presenting practical applications of veterinary diagnostic tests for feline calicivirus and porcine parvovirus. Second, in the context of assessing agreement and method comparison studies, categorical test results are compared by Cohen’s k and continuous measurements by linear mixed effects models extending the classical use of Bland-Altman plots with limits of agreement. The former is illustrated in a publication on the diagnostic test Interferon-Gamma to classify bovines being infected with Mycobacterium bovis when analysing samples from the same animals in five different laboratories and from different anatomical locations. Two peer-reviewed papers aim to assess the agreement of serumspecific lipase, as a diagnostic test for feline pancreatitis with a commercial test kit and ultrasonographic findings. In the context of comparing continuous measurements, i.e. cardiac output and blood pressure measured directly and indirectly, two peer-reviewed paper illustrate the application of linear mixed effects models to simultaneously assess bias, precision and covariate information. Typical pitfalls arising in method comparison studies are summarised in a review paper. Building upon the previous parts, the third part adds to the existing knowledge by presenting novel and innovative approaches when assessing the performance of diagnostic tests in the absence of a perfect gold standard. So-called no gold standard models (NGS) are applied to assess the diagnostic test accuracies in the context of zoonotic diseases such as bovine tuberculosis, porcine toxoplasmosis as well as canine and vulpine echinococcosis. Additionally, these models are applied to assess diagnostic test accuracies to diagnose Brachyspira hyodysenteriae, an economically important disease in pigs. Furthermore, they are also utilised to assess diagnostic accuracies of diagnostic tools for subclinical mastitis in dairy cattle. In this part, Bayesian approaches are presented, together with technical aspects including conditional dependencies, Markov Chain Monte Carlo simulations and aspects of model selection. The innovative aspects and main novelty of the work presented in this thesis pertain to the incorporation of covariate information and random effects. Whereas covariate information in the form of risk factors has been included in statistical analyses since decades, considering random effects to account for clustering of animals at herd level just became possible with increased computational power. Nowadays dealing appropriately with the hierarchical structure of animal data is considered as good statistical practice and warranted in epidemiological studies to avoid biased results. However, diagnostic test studies including covariate information and random effects are scarce. The aim of this thesis is to fill this gap by showcasing a number of Bayesian latent class analyses for various infectious diseases in animals.

Book reviewBy Gilberto Levy and Bruce Levin. ISBN 978-1-118-64585-7, John Wiley &amp; Sons, Inc. Hoboken, NJ 2014

Objective To compare the applied signification of optical and ultrasonic biometry in observing the axial length of eyes with vitreous hemorrhage and retinal detachment. Methods This is a prospective clinical study. We randomly selected 57 cases (57 eyes) with vitreous hemorrhage and (or) retinal detachment from May 1, 2016 to May 31. Patients had not been performed eye surgery, also denied the history of ocular trauma and excluded other eye diseases. 25 eyes with vitreous hemorrhage, 24 eyes with retinal detachment, 8 eyes complicated with vitreous and retinal detachment hemorrhage. At 24 hours before surgery, we measured axial length using the Lenstar LS 900, immersion B-ultrasound (IB) and immersion A-ultrasound (IA). The differences between three methods were assessed with paired sample t-test. Results IB and IA data was collected from all 57 eyes, there was no statistical significance between measurements of IB and IA (P>0.05). In the eyes with serious refractive medium opacity (36 eyes), the results showed no statistical significance difference between measurements of IB and IA (P>0.05). The measurements of three groups can be obtained from the rest eyes (21 eyes): significant statistical difference of the measurements between IB and Lenstar was detected [(24.057±1.441) mm vs (23.470±1.775) mm], (t=3.099, P 0.05). Conclusions In the eyes with vitreous hemorrhage and (or) retinal detachment, the measurements of axial length could not be achieved or existed deviations on account of refractive medium opacity when using optical biometry. Under such circumstances, we should choose IA or IB as the optimization method to obtain measurements, in order to get much more accurate results. Key words: Ultrasonography; Vitreous hemorrhage; Retinal detachment; Biostatistics

Curso Extensão

Essentials of biostatistics

An extension of penalized ordinal response models by Qing Zhou A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2015 Major Director: Kellie J. Archer, Ph.D., Professor, Department of Biostatistics Ordinal responses are commonly seen in medical research. Many pathological evaluations and health status outcomes are reported on an ordinal scales. Some examples of ordinal outcomes include cancer stage (I, II, III and IV), or stage of liver disease (normal liver, chronic hepatitis, cirrhosis and end of stage liver disease or hepatocellular carcinoma (HCC)). In recent years, there has been a demand to understanding the pathogenic association between ordinal clinical outcomes and molecular characteristics. Genomic charactersitics are often assayed using a high-dimensional platform where the number of interrogated sites (P ) exceeds the number of samples (n). Unfortunately, traditional ordinal response models often do not perform well when the number of parameter (P ) exceed the number of observations (n). A good solution to this problem is penalization, for example, least absolute shrinkage and selection operator (LASSO). Here, we extend a LASSO method, the generalized monotone incremental