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Bio-PEPA for Epidemiological Models [PDF]

Electronic Notes in Theoretical Computer Science, 2010
Many models have been defined in order to describe the evolution of a disease in a population. The modelling of diseases is helpful to understand the mechanisms for their spread and to predict their future evolution.
Federica Ciocchetta, Jane Hillston
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Mathematical modeling and the epidemiological research process

European Journal of Epidemiology, 2009
The authors of this paper advocate for the expanded use of mathematical models in epidemiology and provide an overview of the principles of mathematical modeling. Mathematical models can be used throughout the epidemiological research process. Initially they may help to refine study questions by visually expressing complex systems, directing literature
Mikayla C, Chubb, Kathryn H, Jacobsen
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Epidemiology: Use and utility in the process

Fundamental and Applied Toxicology, 1984
Much of this volume is oriented to the laboratory assessment of food safety. I, however, will focus on the search for adverse consequences of food consumption by humans who are not participating in an experiment. While others work on the problems of extrapolating from bacteria and rodents to man, and this work is certainly important, I prefer to ...
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A consideration of group work processes in modern epidemiology

Annals of Epidemiology, 2014
In the field of epidemiology, much attention has been given to the reduction of random or systematic errors in study design, analysis, and reporting. This article reviews relevant literature on group work processes. The review orients attention toward optimizing group work processes to enhance group decision making and optimize the conduct of ...
Karl, Mattingly, Anne-Louise, Ponsonby
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Nonlinearity in the Epidemiology of Complex Health and Disease Processes

Theoretical Medicine and Bioethics, 1998
The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been referred to as a web of causality. This web extends theoretically beyond risk markers. It includes determinants of emergence/non-emergence of disease.
P, Philippe, O, Mansi
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Biological Processes in the Epidemiology of Heartwater

1992
Heartwater, a rickettsial disease of ruminants, caused by Cowdria ruminantium, is transmitted by various tick species of the genus Amblyomma. It occurs through most of sub-Saharan Africa, where it is of considerable economic importance, and has spread to a number of islands in the Indian and Atlantic Oceans and the Caribbean and now poses a threat to ...
R. A. I. Norval, H. R. Andrew, C. E. Yunker, M. J. Burridge   +3 more
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An epidemiological study: Processing by a low-capacity computer

Computers and Biomedical Research, 1971
Abstract The data collected on the occasion of a cross-sectional epidemiological study on atherosclerosis (129 parameters for each of the 843 subjects) have been processed by means of an IBM 360 20 , a computer not intended for scientific problems, and lacking magnetic storage media. In this purpose, it has been necessary to program down to the
D, Jaloustre, E, Panak, M, Ricoeur, J P, Du Pasquier, E, Edmond, J, Daver   +5 more
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Epidemiology and the Public Policy Process

2009
After completing this chapter, you will be able to: 1. Apply epidemiologic measures to distinguish among community health problems for receiving priority attention by the policy process. 2. Monitor policy effectiveness in eliminating health care disparities using epidemiologic measures.
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Epidemiology and the Public Policy Process

1995
Public policy and epidemiology function in a dynamic environment influenced by political, economic, social, and other factors. As demonstrated by the national health goal to eliminate health disparities among population groups by 2010, it will be important to have policies that demonstrate an understanding of societal determinants of health.
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Analysis of Low-dimensional Complex Processes in Epidemiology

1991
A new method of time series analysis based on measures of information for conditional one step predictions seems to be particularly suited to disentangle the role of chance and low dimensional unstable “deterministic” dynamics in generating the unpredictability in the behaviour of individual and collective biological systems.
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