Applications of Information Theory to Epidemiology

• Format: eBook
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Asiatic citrus canker; Atangana–Baleanu derivative; average mutual information; balance; Bayes’ rule; binormal; Biology, life sciences; Caputo derivative; Caputo–Fabrizio derivative; deployment; deterministic dynamics; diagnostic information; diagnostic test; direct assay; early detection; Ebola model; empirical; entropy; epidemic model; evaluation; expected mutual information; field diagnostic; Fisher scoring algorithm; forecast; HIV/AIDS epidemic; information theory; Jensen–Shannon divergence; latent class; leaf plot; likelihood ratio; Mathematics and Science; multiple diagnostic tests; mutual information; n/a; negative predictive value; Newton–Raphson procedure; numerical results; observational study; positive predictive value; predictive ROC curve; prevalence; probability; PROC curve; PV-ROC curve; Reference, Information and Interdisciplinary subjects; regression model; relative entropy; Research and information: general; ROC curve; scent signature; selection bias; sensitivity; Shannon entropy; specificity; SS-ROC curve; SS/PV-ROC plot; stochastic processes; time series; transient behavior; urinary bladder cancer; vaccination and treatment intervention controls
• ISBN: 9783036503172; 3036503161; 9783036503165; 303650317X
• DOI: 10.3390/books978-3-0365-0317-2

• 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.