Applications of Information Theory to Epidemiology
Material type:
ArticleLanguage: English Publication details: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021Description: 1 electronic resource (238 p.)ISBN: - books978-3-0365-0317-2
- 9783036503165
- 9783036503172
- Research & information: general
- Biology, life sciences
- Ebola model
- Caputo derivative
- Caputo–Fabrizio derivative
- Atangana–Baleanu derivative
- numerical results
- entropy
- information theory
- multiple diagnostic tests
- mutual information
- relative entropy
- balance
- Jensen–Shannon divergence
- observational study
- selection bias
- probability
- forecast
- likelihood ratio
- positive predictive value
- negative predictive value
- diagnostic information
- Shannon entropy
- epidemic model
- transient behavior
- vaccination and treatment intervention controls
- diagnostic test
- evaluation
- ROC curve
- PROC curve
- binormal
- prevalence
- Bayes’ rule
- leaf plot
- expected mutual information
- predictive ROC curve
- PV-ROC curve
- SS-ROC curve
- SS/PV-ROC plot
- empirical
- urinary bladder cancer
- sensitivity
- specificity
- HIV/AIDS epidemic
- regression model
- Newton–Raphson procedure
- Fisher scoring algorithm
- time series
- early detection
- Asiatic citrus canker
- latent class
- field diagnostic
- scent signature
- direct assay
- deployment
- average mutual information
- stochastic processes
- deterministic dynamics
- n/a
Open Access star Unrestricted online access
• 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.
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