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Modeling the effect of transient populations on epidemics in Washington DC.

Parikh N, Youssef M, Swarup S, Eubank S - Sci Rep (2013)

Bottom Line: We find that there are significantly more infections when transients are considered.Surprisingly, closing museums has no beneficial effect.However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak.

View Article: PubMed Central - PubMed

Affiliation: Networks Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, USA.

ABSTRACT
Large numbers of transients visit big cities, where they come into contact with many people at crowded areas. However, epidemiological studies have not paid much attention to the role of this subpopulation in disease spread. We evaluate the effect of transients on epidemics by extending a synthetic population model for the Washington DC metro area to include leisure and business travelers. A synthetic population is obtained by combining multiple data sources to build a detailed minute-by-minute simulation of population interaction resulting in a contact network. We simulate an influenza-like illness over the contact network to evaluate the effects of transients on the number of infected residents. We find that there are significantly more infections when transients are considered. Since much population mixing happens at major tourism locations, we evaluate two targeted interventions: closing museums and promoting healthy behavior (such as the use of hand sanitizers, covering coughs, etc.) at museums. Surprisingly, closing museums has no beneficial effect. However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak. We analytically derive the reproductive number and perform stability analysis using an ODE-based model.

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Contact pattern among four subpopulations.In general, βab→cd represents the infection transmission rate due to the contact between subpopulation ab to subpopulation cd. The infection rates βrr→rr, βrr→rt, βrt→rr, βrt→rt, βrt→tr, βtr→rt and βtr→tr have positive values, while the infection rates βtt→tt, βtt→tr and βtr→tt equal 0 because all transients have contacts with both transients and residents. That is, the population tt represented by the red oval in the lower left vanishes.
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f9: Contact pattern among four subpopulations.In general, βab→cd represents the infection transmission rate due to the contact between subpopulation ab to subpopulation cd. The infection rates βrr→rr, βrr→rt, βrt→rr, βrt→rt, βrt→tr, βtr→rt and βtr→tr have positive values, while the infection rates βtt→tt, βtt→tr and βtr→tt equal 0 because all transients have contacts with both transients and residents. That is, the population tt represented by the red oval in the lower left vanishes.

Mentions: In the synthetic population model, all transients come in contact with residents. Therefore, the subpopulation of transients who only meet transients is not considered, i.e., tt = 0. The contact pattern and the infection transmission rates among these four subpopulations are as shown in Figure 9. There are ten infection transmission rates in the model, of which three are zero because tt = 0, as shown in Figure 9. The remaining seven non-zero transmission rates are used to find a new reproductive number Ro.


Modeling the effect of transient populations on epidemics in Washington DC.

Parikh N, Youssef M, Swarup S, Eubank S - Sci Rep (2013)

Contact pattern among four subpopulations.In general, βab→cd represents the infection transmission rate due to the contact between subpopulation ab to subpopulation cd. The infection rates βrr→rr, βrr→rt, βrt→rr, βrt→rt, βrt→tr, βtr→rt and βtr→tr have positive values, while the infection rates βtt→tt, βtt→tr and βtr→tt equal 0 because all transients have contacts with both transients and residents. That is, the population tt represented by the red oval in the lower left vanishes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3818653&req=5

f9: Contact pattern among four subpopulations.In general, βab→cd represents the infection transmission rate due to the contact between subpopulation ab to subpopulation cd. The infection rates βrr→rr, βrr→rt, βrt→rr, βrt→rt, βrt→tr, βtr→rt and βtr→tr have positive values, while the infection rates βtt→tt, βtt→tr and βtr→tt equal 0 because all transients have contacts with both transients and residents. That is, the population tt represented by the red oval in the lower left vanishes.
Mentions: In the synthetic population model, all transients come in contact with residents. Therefore, the subpopulation of transients who only meet transients is not considered, i.e., tt = 0. The contact pattern and the infection transmission rates among these four subpopulations are as shown in Figure 9. There are ten infection transmission rates in the model, of which three are zero because tt = 0, as shown in Figure 9. The remaining seven non-zero transmission rates are used to find a new reproductive number Ro.

Bottom Line: We find that there are significantly more infections when transients are considered.Surprisingly, closing museums has no beneficial effect.However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak.

View Article: PubMed Central - PubMed

Affiliation: Networks Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, USA.

ABSTRACT
Large numbers of transients visit big cities, where they come into contact with many people at crowded areas. However, epidemiological studies have not paid much attention to the role of this subpopulation in disease spread. We evaluate the effect of transients on epidemics by extending a synthetic population model for the Washington DC metro area to include leisure and business travelers. A synthetic population is obtained by combining multiple data sources to build a detailed minute-by-minute simulation of population interaction resulting in a contact network. We simulate an influenza-like illness over the contact network to evaluate the effects of transients on the number of infected residents. We find that there are significantly more infections when transients are considered. Since much population mixing happens at major tourism locations, we evaluate two targeted interventions: closing museums and promoting healthy behavior (such as the use of hand sanitizers, covering coughs, etc.) at museums. Surprisingly, closing museums has no beneficial effect. However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak. We analytically derive the reproductive number and perform stability analysis using an ODE-based model.

Show MeSH
Related in: MedlinePlus