TY - BOOK ID - 134716412 TI - Applications of Information Theory to Epidemiology PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Ebola model KW - Caputo derivative KW - Caputo–Fabrizio derivative KW - Atangana–Baleanu derivative KW - numerical results KW - entropy KW - information theory KW - multiple diagnostic tests KW - mutual information KW - relative entropy KW - balance KW - Jensen–Shannon divergence KW - observational study KW - selection bias KW - probability KW - forecast KW - likelihood ratio KW - positive predictive value KW - negative predictive value KW - diagnostic information KW - Shannon entropy KW - epidemic model KW - transient behavior KW - vaccination and treatment intervention controls KW - diagnostic test KW - evaluation KW - ROC curve KW - PROC curve KW - binormal KW - prevalence KW - Bayes’ rule KW - leaf plot KW - expected mutual information KW - predictive ROC curve KW - PV-ROC curve KW - SS-ROC curve KW - SS/PV-ROC plot KW - empirical KW - urinary bladder cancer KW - sensitivity KW - specificity KW - HIV/AIDS epidemic KW - regression model KW - Newton–Raphson procedure KW - Fisher scoring algorithm KW - time series KW - early detection KW - Asiatic citrus canker KW - latent class KW - field diagnostic KW - scent signature KW - direct assay KW - deployment KW - average mutual information KW - stochastic processes KW - deterministic dynamics KW - n/a KW - Caputo-Fabrizio derivative KW - Atangana-Baleanu derivative KW - Jensen-Shannon divergence KW - Bayes' rule KW - Newton-Raphson procedure UR - https://www.unicat.be/uniCat?func=search&query=sysid:134716412 AB - • Applications of Information Theory to Epidemiology collects recent research findings on the analysis of diagnostic information and epidemic dynamics. • The collection includes an outstanding new review article by William Benish, providing both a historical overview and new insights. • In research articles, disease diagnosis and disease dynamics are viewed from both clinical medicine and plant pathology perspectives. Both theory and applications are discussed. • New theory is presented, particularly in the area of diagnostic decision-making taking account of predictive values, via developments of the predictive receiver operating characteristic curve. • New applications of information theory to the analysis of observational studies of disease dynamics in both human and plant populations are presented. ER -