Abstract
We present a framework for modeling the spread of pathogens throughout a population and generating policies that minimize the impact of those pathogens on the population. This framework is used to study the spread of human viruses between cities via airplane travel. It combines agent-based simulation, mathematical analysis, and an Evolutionary Algorithm (EA) optimizer. The goal of this study is to develop tools that determine the optimal distribution of a vaccine supply in the model. Using plausible benchmark vaccine allocation policies of uniform and proportional distribution, we compared their effectiveness to policies found by the EA. We then designed and tested a new, more effective policy which increased the importance of vaccinating smaller cities that are flown to more often. This "importance factor" was validated using US influenza data from the last four years.
| Original language | English |
|---|---|
| Pages (from-to) | 3728-3744 |
| Number of pages | 17 |
| Journal | Information Sciences |
| Volume | 180 |
| Issue number | 19 |
| DOIs | |
| State | Published - 1 Oct 2010 |
Fingerprint
Keywords
- Epidemiology
- Evolutionary algorithm
- Influenza
- Migration
- Vaccination
Cite this
}
Effective vaccination policies. / Shaw, L.; Spears, W.; Billings, Lora; Maxim, P.
In: Information Sciences, Vol. 180, No. 19, 01.10.2010, p. 3728-3744.Research output: Contribution to journal › Article
TY - JOUR
T1 - Effective vaccination policies
AU - Shaw, L.
AU - Spears, W.
AU - Billings, Lora
AU - Maxim, P.
PY - 2010/10/1
Y1 - 2010/10/1
N2 - We present a framework for modeling the spread of pathogens throughout a population and generating policies that minimize the impact of those pathogens on the population. This framework is used to study the spread of human viruses between cities via airplane travel. It combines agent-based simulation, mathematical analysis, and an Evolutionary Algorithm (EA) optimizer. The goal of this study is to develop tools that determine the optimal distribution of a vaccine supply in the model. Using plausible benchmark vaccine allocation policies of uniform and proportional distribution, we compared their effectiveness to policies found by the EA. We then designed and tested a new, more effective policy which increased the importance of vaccinating smaller cities that are flown to more often. This "importance factor" was validated using US influenza data from the last four years.
AB - We present a framework for modeling the spread of pathogens throughout a population and generating policies that minimize the impact of those pathogens on the population. This framework is used to study the spread of human viruses between cities via airplane travel. It combines agent-based simulation, mathematical analysis, and an Evolutionary Algorithm (EA) optimizer. The goal of this study is to develop tools that determine the optimal distribution of a vaccine supply in the model. Using plausible benchmark vaccine allocation policies of uniform and proportional distribution, we compared their effectiveness to policies found by the EA. We then designed and tested a new, more effective policy which increased the importance of vaccinating smaller cities that are flown to more often. This "importance factor" was validated using US influenza data from the last four years.
KW - Epidemiology
KW - Evolutionary algorithm
KW - Influenza
KW - Migration
KW - Vaccination
UR - http://www.scopus.com/inward/record.url?scp=77958515662&partnerID=8YFLogxK
U2 - 10.1016/j.ins.2010.06.005
DO - 10.1016/j.ins.2010.06.005
M3 - Article
AN - SCOPUS:77958515662
VL - 180
SP - 3728
EP - 3744
JO - Information Sciences
JF - Information Sciences
SN - 0020-0255
IS - 19
ER -