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Applications of Novel Analytical Methods in Epidemiology
The repertoire of quantitative analytical techniques in disciplines such as ecology, decision science, and evolutionary biology has grown, in part enabled by the development and increased availability of computational resources. Integration of cutting-edge, quantitative tools into veterinary epidemiology that have been borrowed from such disciplines has offered opportunities to advance the study of disease dynamics in animal populations, to improve and guide decision-making related to disease prevention, control, or eradication. Furthermore, the need to explore new analytical methods for veterinary epidemiology has been driven by the increasing availability and complexity of animal disease d...
Epidemiology of Avian Influenza Viruses
Avian influenza is a highly contagious viral disease, characterized by intense circulation in the wild waterbird reservoirs, with periodical introductions into the domestic poultry sector. AI viruses have been the source of devastating economic losses in the poultry industry over the last three decades, and have become a major veterinary and public health concern due to their zoonotic potential. The most emblematic illustration of this impact has been the emergence of the HPAI H5N1 virus in southern China in the mid-1990s, followed by its continental spread across East and Southeast Asia, and the unprecedented epidemics recorded in 2003–2004. More recently (from 2014 to 2017), several subt...
Bridging Science and Policy for Animal Health Surveillance: ICAHS4 2022
The current COVID-19 pandemic has expanded lay people’s vocabulary; PCR-testing is no longer mentioned only by virologists, nor are the terms basic reproduction ratio and herd-immunity limited to epidemiologists. This expansion of vocabulary that was previously only used in specialist settings already demonstrates global, societal impact. We have learnt that it is insufficient simply to act on disease emergence and spread. More focus is needed on prevention and surveillance of the precursors of emerging infectious disease, as well as early detection. To succeed in this, it is a necessity to collaborate across sectors – academics, governments, industry and the public – in a transdisciplinary way.
Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications
Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.
