Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases Page: 5
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Personal Health Care
Vaccine Design
Molecular Biology Therapeutics
Environmental Sciences Diagnostics
Medical Geography
Biostatistics 'Public Health Community Health Care
SociologyVaccine Dissemination
Computer ScienceDisease Control and Prevention
Surveillance
Figure 1.1. Public Health - Multi-disciplinary Domain
planning tool for the allocation of public health resources. Most models operate on the pre-
sumption of a closed population, assuming that the epidemic spreads rapidly enough that the
changes brought in by births, deaths, migration and demographic changes are negligible [8].
Recently, some computational disease models have emerged, which facilitate the simulation
and thus the investigation of different disease characteristics. These include models that
exploit the susceptibles-infectives-removals paradigm, cellular automata methodology, agent-
based modeling and Bayesian reasoning. This study focuses on the probabilistic analysis of
the progression of infectious diseases in non-delineated environments.
1.3.1. Interdisciplinary Domain of Public Health
Public health domain in the modern world brings together diverse disciplines, including
molecular biology, environmental sciences, medical geography, biostatistics, sociology and
computer science (Fig. 1.1). The enhanced understanding of epidemiology and public health
will increase the quality of individual health care, including vaccine design, therapeutics and
diagnostics, as well as augment the community health care through better measures for
vaccine dissemination, surveillance, disease control and prevention.
The study of progression of infectious diseases in different demographic and geographic
populations is intrinsically correlated to the genetic makeup, population dynamics and en-
vironmental factors of the region (Fig. 1.2). The correlation of these factors will lend to
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Abbas, Kaja Moinudeen. Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases, dissertation, May 2006; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc5302/m1/18/: accessed April 16, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .