A standard form of citation of this article is:
Stroud, Phillip, Del Valle, Sara, Sydoriak, Stephen, Riese, Jane and Mniszewski, Susan (2007). 'Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society'. Journal of Artificial Societies and Social Simulation 10(4)9 <https://www.jasss.org/10/4/9.html>.
The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:
@article{stroud2007,
title = {Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society},
author = {Stroud, Phillip and Del Valle, Sara and Sydoriak, Stephen and Riese, Jane and Mniszewski, Susan},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {10},
number = {4},
pages = {9},
year = {2007},
URL = {https://www.jasss.org/10/4/9.html},
keywords = {Agent Based Modeling, Computer Simulation, Epidemic Simulation, Public Health Policy},
abstract = {EpiSimS is a massive simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations, and of the dynamics of contagious disease spread on the resulting social contact network. This paper describes the assumptions and methodology in the EpiSimS model. It also describes and presents a simulation of the spatial dynamics of pandemic influenza in an artificial society constructed to match the demographics of southern California.
As an example of the utility of the massive simulation approach, we demonstrate a strong correlation between local demographic characteristics and pandemic severity, which gives rise to previously unanticipated spatial pandemic hotspots. In particular, the average household size in a census tract is strongly correlated with the clinical attack rate computed by the simulation. Public heath agencies with responsibility for communities having relatively high population per household should expect to be more severely hit by a pandemic.},
}The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.
TY - JOUR
TI - Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society
AU - Stroud, Phillip
AU - Del Valle, Sara
AU - Sydoriak, Stephen
AU - Riese, Jane
AU - Mniszewski, Susan
Y1 - 2007/10/31
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 10
IS - 4
SP - 9
UR - https://www.jasss.org/10/4/9.html
KW - Agent Based Modeling
KW - Computer Simulation
KW - Epidemic Simulation
KW - Public Health Policy
N2 - EpiSimS is a massive simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations, and of the dynamics of contagious disease spread on the resulting social contact network. This paper describes the assumptions and methodology in the EpiSimS model. It also describes and presents a simulation of the spatial dynamics of pandemic influenza in an artificial society constructed to match the demographics of southern California. As an example of the utility of the massive simulation approach, we demonstrate a strong correlation between local demographic characteristics and pandemic severity, which gives rise to previously unanticipated spatial pandemic hotspots. In particular, the average household size in a census tract is strongly correlated with the clinical attack rate computed by the simulation. Public heath agencies with responsibility for communities having relatively high population per household should expect to be more severely hit by a pandemic.
ER -