scholarly journals Public Health Implications of Bioinformatics

2004 ◽  
Vol 13 (01) ◽  
pp. 137-143
Author(s):  
F. Martin-Sanchez ◽  
V. Maojo
Keyword(s):  
Public Health ◽  
Informed Consent ◽  
Biomedical Research ◽  
Genetic Epidemiology ◽  
Genomic Information ◽  
Policy Makers ◽  
Clinical Databases ◽  
Study Designs ◽  
Informatics Tools ◽  
Bioinformatics Community

Abstract:Epidemiologists are reformulating their classical approaches to diseases by considering various issues associated to “omics” areas and technologies. Traditional differences between epidemiology and genetics include background, training, terminologies, study designs and others. Public health and epidemiology are increasingly looking forward to using methodologies and informatics tools, facilitated by the Bioinformatics community, for managing genomic information. Future microarray developments will also facilitate the analysis of entire genomes on single arrays, enhancing genetic epidemiology research. The use of biomarkers, biobanks, and integrated genomic/clinical databases poses serious challenges for bioinformaticians in order to extract useful information and knowledge for biomedical research and healthcare. In this regard, there are various ethical, privacy, informed consent and social implications that should be carefully addressed by researchers, practitioners and policy makers.

Bioinformatics: Towards New Directions for Public Health

2004 ◽  
Vol 43 (03) ◽  
pp. 208-214 ◽  
Author(s):  
F. Martin-Sanchez ◽  
V. Maojo
Keyword(s):  
Public Health ◽  
Public Health Practice ◽  
Practice Research ◽  
Genomic Information ◽  
Biological Ontologies ◽  
Internet Resources ◽  
Clinical Databases ◽  
Environmental Agents ◽  
Research And Education ◽  
Study Designs

Summary Objectives: Epidemiologists are reformulating their classical approaches to diseases by considering various issues associated to “omics” areas and technologies. Traditional differences between epidemiology and genetics include background, training, terminologies, study designs and others. Public health and epidemiology are increasingly looking forward to using methodologies and informatics tools, facilitated by the Bioinformatics community, for managing genomic information. Our aim is to describe which are the most important implications related with the increasing use of genomic information for public health practice, research and education. To review the contribution of bioinformatics to these issues, in terms of providing the methods and tools needed for processing genetic information from pathogens and patients. To analyze the research challenges in biomedical informatics related with the need of integration of clinical, environmental and genetic data and the new scenarios arisen in public health. Methods: Review of the literature, Internet resources and material and reports generated by internal and external research projects. Results: New developments are needed to advance in the study of the interactions between environmental agents and genetic factors involved in the development of diseases. The use of biomarkers, biobanks, and integrated genomic/clinical databases poses serious challenges for informaticians in order to extract useful information and knowledge for public health, biomedical research and healthcare. Conclusions: From an informatics perspective, integrated medical/biological ontologies and new semantic-based models for managing information provide new challenges for research in areas such as genetic epidemiology and the “omics” disciplines, among others. In this regard, there are various ethical, privacy, informed consent and social implications, that should be carefully addressed by researchers, practitioners and policy makers.

scholarly journals Reflection about systematic review in public health

2014 ◽  
Vol 23 (2) ◽  
pp. 479-483
Author(s):  
Fabiana Villela Mamede
Keyword(s):  
Public Health ◽  
Systematic Review ◽  
Systematic Reviews ◽  
Health Program ◽  
Decision Makers ◽  
Public Health Program ◽  
Policy Makers ◽  
Reporting Requirements ◽  
Study Designs ◽  
Health Review

This study is a reflection on conducting a systematic review in public health. Systematic reviews of public health are fraught with challenges. Complexity is inherent and this may be due to multi-component interventions, diverse study populations, multiple outcomes measured, mixed study designs, or implementation and effectiveness of the review. For policy makers and practitioners to use systematic reviews to implement effective systematic reviews of public health program, the reviews must include this information, which seeks to answer the questions posed by decision-makers, including recipients of the program. We discuss methodological and practice issues that need to be considered when undertaking systematic reviews in this field, including recommendations to reviewers on the issues to address within a systematic public health review and, indirectly, provides advice to researchers on the reporting requirements of primary studies for the production of high quality systematic reviews.

scholarly journals Use of Genomic Information in Health Impact Assessment is Yet to Come: A Systematic Review

2020 ◽  
Vol 17 (24) ◽  
pp. 9417
Author(s):  
Balázs Ádám ◽  
Szabolcs Lovas ◽  
Róza Ádány
Keyword(s):  
Public Health ◽  
Impact Assessment ◽  
Genetic Epidemiology ◽  
Health Impact Assessment ◽  
Public Health Practice ◽  
Health Impact ◽  
Genomic Information ◽  
Gene Environment ◽  
Fast Pace ◽  
To Come

Information generated by genetic epidemiology and genomics studies has been accumulating at fast pace, and this knowledge opens new vistas in public health, allowing for the understanding of gene–environment interactions. However, the translation of genome-based knowledge and technologies to the practice of healthcare, and especially of public health, is challenging. Because health impact assessment (HIA) proved to be an effective tool to assist consideration of health issues is sectoral policymaking, this study aimed at exploring its role in the translational process by a systematic literature review on the use of genetic information provided by genetic epidemiology and genomics studies in HIA. PubMed, Scopus, and Web of Science electronic databases were searched and the findings systematically reviewed and reported by the PRISMA guidelines. The review found eight studies that met the inclusion criteria, most of them theoretically discussing the use of HIA for introducing genome-based technologies in healthcare practice, and only two articles considered, in short, the possibility for a generic application of genomic information in HIA. The findings indicate that HIA should be more extensively utilized in the translation of genome-based knowledge to public health practice, and the use of genomic information should be facilitated in the HIA process.

Identifying Public Health Problems

2018 ◽  
Author(s):  
Scott Burris ◽  
Micah L. Berman ◽  
Matthew Penn, and ◽  
Tara Ramanathan Holiday
Keyword(s):  
Public Health ◽  
Health Problems ◽  
Health Priorities ◽  
Disability Adjusted Life Years ◽  
Quality Adjusted Life Years ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Study Designs ◽  
Quality Adjusted Life

Chapter 5 discusses the use of epidemiology to identify the source of public health problems and inform policymaking. It uses a case study to illustrate how researchers, policymakers, and practitioners detect diseases, identify their sources, determine the extent of an outbreak, and prevent new infections. The chapter also defines key measures in epidemiology that can indicate public health priorities, including morbidity and mortality, years of potential life lost, and measures of lifetime impacts, including disability-adjusted life years and quality-adjusted life years. Finally, the chapter reviews epidemiological study designs, differentiating between experimental and observational studies, to show how to interpret data and identify limitations.

The Ethics of AI in Biomedical Research, Patient Care, and Public Health

2020 ◽  
pp. 702-718 ◽  
Author(s):  
Alessandro Blasimme ◽  
Effy Vayena
Keyword(s):  
Public Health ◽  
Patient Care ◽  
Biomedical Research ◽  
Disease Surveillance ◽  
Ethical Issues ◽  
Ethical Review ◽  
Ethical Challenges ◽  
Healthcare Provision ◽  
Social Scientists ◽  
Ethical Frameworks

This chapter explores ethical issues raised by the use of artificial intelligence (AI) in the domain of biomedical research, healthcare provision, and public health. The litany of ethical challenges that AI in medicine raises cannot be addressed sufficiently by current regulatory and ethical frameworks. The chapter then advances the systemic oversight approach as a governance blueprint, which is based on six principles offering guidance as to the desirable features of oversight structures and processes in the domain of data-intense biomedicine: adaptivity, flexibility, inclusiveness, reflexivity, responsiveness, and monitoring (AFIRRM). In the research domain, ethical review committees will have to incorporate reflexive assessment of the scientific and social merits of AI-driven research and, as a consequence, will have to open their ranks to new professional figures such as social scientists. In the domain of patient care, clinical validation is a crucial issue. Hospitals could equip themselves with “clinical AI oversight bodies” charged with the task of advising clinical administrators. Meanwhile, in the public health sphere, the new level of granularity enabled by AI in disease surveillance or health promotion will have to be negotiated at the level of targeted communities.

scholarly journals Conceptualising natural and quasi experiments in public health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Frank de Vocht ◽  
Srinivasa Vittal Katikireddi ◽  
Cheryl McQuire ◽  
Kate Tilling ◽  
Matthew Hickman ◽  
...  
Keyword(s):  
Public Health ◽  
Study Design ◽  
Grey Literature ◽  
Public Health Research ◽  
Natural Experiments ◽  
Target Trial ◽  
Design Elements ◽  
Randomized Controlled ◽  
Study Designs ◽  
The Impact

Abstract Background Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework. Methods A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature. Results Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered ‘as-if randomized’. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES. Conclusions NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions.

scholarly journals Obstetric Violence in Spain (Part III): Healthcare Professionals, Times and Areas

2021 ◽  
Vol 18 (7) ◽  
pp. 3359
Author(s):  
Desirée Mena-Tudela ◽  
Susana Iglesias-Casás ◽  
Víctor Manuel González-Chordá ◽  
María Jesús Valero-Chillerón ◽  
Laura Andreu-Pejó ◽  
...  
Keyword(s):  
Public Health ◽  
Primary Care ◽  
Informed Consent ◽  
Healthcare Professionals ◽  
Public Health Problem ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Lack Of Information ◽  
Obstetric Violence

Background: Obstetric violence is a worldwide public health problem, which seems greater in Spain. As no studies were found that identify the most representative healthcare professionals, times, and areas involved in obstetric violence, the objective of this work was to study at what time of maternity, with which professionals, and in what areas women identified obstetric violence. Methods: This descriptive, retrospective, and cross-sectional study was performed from January 2018 to June 2019. The main variables were the area (hospital, primary care, both), the time (pregnancy, birth, puerperium), and the professionals attending to women. Results: Our sample comprised 17,541 participants. The area identified with the most obstetric violence for the different studied variables was hospitals. Women identified more obstetric violence at time of birth. Findings such as lack of information and informed consent (74.2%), and criticism of infantile behavior and treatment (87.6%), stood out. The main identified healthcare professionals were midwives and gynecologists, and “other” professionals repeatedly appeared. Conclusions: Having identified the professionals, times, and areas of most obstetric violence in Spain, it seems necessary to reflect on not only the Spanish National Health System’s structure and management but also on healthcare professionals’ training.

EXPRESS: The Gift of Data: Industry-Led Food Reformulation and the Obesity Crisis in Europe

2020 ◽  
pp. 074391562098384
Author(s):  
Norah Campbell ◽  
Sarah Browne ◽  
Marius Claudy ◽  
Melissa Mialon ◽  
Hercberg Serge ◽  
...  
Keyword(s):  
Public Health ◽  
Food Industry ◽  
Processed Food ◽  
Policy Makers ◽  
Intelligence System ◽  
Gift Economy ◽  
Nutrition Policies ◽  
The Gift ◽  
Marketing Intelligence ◽  
The Impact

Ultra-processed food manufacturers have proposed that product reformulation should be a key strategy to tackle obesity. In determining the impact of reformulation on population dietary behaviours, policy makers are often dependant on data provided by these manufacturers. Where such data are “gifted” to regulators there may be an implicit expectation of reciprocity that adversely influences nutrition policies. We sought to assess Europe’s industry-led reformulation strategy in five countries deploying critical policy studies as an approach. We found that interim results on industry-led food reformulation did not meet their targets. Information asymmetries exist between food industry and policy makers: the latter are not privy to marketing intelligence and must instead rely on data that are voluntarily donated by food industry actors. These data represent a distorted snippet of the marketing intelligence system from whence they came. Because these data indeed bear all the hallmarks of a gift, regulatory and public health authorities operate within a gift economy. The implications of this “data gift economy” are strategic delay and goal-setting when the field is not visible. Ultimately, this could diminish the implementation of public health nutrition policies that are contrary to the commercial interests of ultra-processed food producers.

scholarly journals A stochastic time-delayed model for the effectiveness of Moroccan COVID-19 deconfinement strategy

2020 ◽  
Vol 15 ◽  
pp. 50 ◽  
Author(s):  
Houssine Zine ◽  
Adnane Boukhouima ◽  
El Mehdi Lotfi ◽  
Marouane Mahrouf ◽  
Delfim F.M. Torres ◽  
...  
Keyword(s):  
Public Health ◽  
Health Administration ◽  
Policy Makers ◽  
Public Health Administration ◽  
Additional Degree ◽  
Epidemiological Trend ◽  
The Impact ◽  
Near Future ◽  
Stochastic Time ◽  
Delayed Model

Coronavirus disease 2019 (COVID-19) poses a great threat to public health and the economy worldwide. Currently, COVID-19 evolves in many countries to a second stage, characterized by the need for the liberation of the economy and relaxation of the human psychological effects. To this end, numerous countries decided to implement adequate deconfinement strategies. After the first prolongation of the established confinement, Morocco moves to the deconfinement stage on May 20, 2020. The relevant question concerns the impact on the COVID-19 propagation by considering an additional degree of realism related to stochastic noises due to the effectiveness level of the adapted measures. In this paper, we propose a delayed stochastic mathematical model to predict the epidemiological trend of COVID-19 in Morocco after the deconfinement. To ensure the well-posedness of the model, we prove the existence and uniqueness of a positive solution. Based on the large number theorem for martingales, we discuss the extinction of the disease under an appropriate threshold parameter. Moreover, numerical simulations are performed in order to test the efficiency of the deconfinement strategies chosen by the Moroccan authorities to help the policy makers and public health administration to make suitable decisions in the near future.

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