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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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Related in: MedlinePlus

For healthy behavior interventions, resident and transient populations are further divided based on whether they visit one of four museums.The Residents – Transients at museums subpopulation represents residents who visit the museums and meet both residents and transients. Similarly, the Transients – Residents at museums subpopulation represents transients who visit the museums and meet both transients and residents. These two subpopulations are denoted as rtm and trm and they have contacts inside the museums (red) and outside the museums (blue). The other three subpopulations (rrnm, rtnm and trnm) represent subpopulations of individuals who do not visit museums.
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f11: For healthy behavior interventions, resident and transient populations are further divided based on whether they visit one of four museums.The Residents – Transients at museums subpopulation represents residents who visit the museums and meet both residents and transients. Similarly, the Transients – Residents at museums subpopulation represents transients who visit the museums and meet both transients and residents. These two subpopulations are denoted as rtm and trm and they have contacts inside the museums (red) and outside the museums (blue). The other three subpopulations (rrnm, rtnm and trnm) represent subpopulations of individuals who do not visit museums.

Mentions: As healthy behavior interventions are assumed to be effective only inside the museums, we further divide each of the four subpopulations used for the ODE model into the people who go to the four museums and those who don't, resulting in six subpopulations. However, the subpopulation of residents who visit museums but only meet residents is very small, and so it is ignored. The contact pattern among the subpopulations is as shown in Figure 11. Using the ODE model and the next generation method, we numerically evaluate the reproductive number for different compliance rates and reduced transmissibility values as shown in Figure 12. The reduction of reproductive number27 is nonlinearly proportional to the reduced transmissibility value. The nonlinearity is clearly observed for higher compliance rate. For compliance rate of 50%, when the transmissibility is reduced to 80% and 60% of its original value, the reproductive number is reduced by 9% and 18%, respectively. Significant reduction in the reproductive number is observed when the transmissibility is reduced to 40% and 20% of its original value. We also notice that the largest reduction of reproductive number is 58% for compliance rate of 100% and reduced transmissibility value of 0 inside the museums.


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

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

For healthy behavior interventions, resident and transient populations are further divided based on whether they visit one of four museums.The Residents – Transients at museums subpopulation represents residents who visit the museums and meet both residents and transients. Similarly, the Transients – Residents at museums subpopulation represents transients who visit the museums and meet both transients and residents. These two subpopulations are denoted as rtm and trm and they have contacts inside the museums (red) and outside the museums (blue). The other three subpopulations (rrnm, rtnm and trnm) represent subpopulations of individuals who do not visit museums.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f11: For healthy behavior interventions, resident and transient populations are further divided based on whether they visit one of four museums.The Residents – Transients at museums subpopulation represents residents who visit the museums and meet both residents and transients. Similarly, the Transients – Residents at museums subpopulation represents transients who visit the museums and meet both transients and residents. These two subpopulations are denoted as rtm and trm and they have contacts inside the museums (red) and outside the museums (blue). The other three subpopulations (rrnm, rtnm and trnm) represent subpopulations of individuals who do not visit museums.
Mentions: As healthy behavior interventions are assumed to be effective only inside the museums, we further divide each of the four subpopulations used for the ODE model into the people who go to the four museums and those who don't, resulting in six subpopulations. However, the subpopulation of residents who visit museums but only meet residents is very small, and so it is ignored. The contact pattern among the subpopulations is as shown in Figure 11. Using the ODE model and the next generation method, we numerically evaluate the reproductive number for different compliance rates and reduced transmissibility values as shown in Figure 12. The reduction of reproductive number27 is nonlinearly proportional to the reduced transmissibility value. The nonlinearity is clearly observed for higher compliance rate. For compliance rate of 50%, when the transmissibility is reduced to 80% and 60% of its original value, the reproductive number is reduced by 9% and 18%, respectively. Significant reduction in the reproductive number is observed when the transmissibility is reduced to 40% and 20% of its original value. We also notice that the largest reduction of reproductive number is 58% for compliance rate of 100% and reduced transmissibility value of 0 inside the museums.

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