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Efficient control of epidemics spreading on networks: balance between treatment and recovery.

Oleś K, Gudowska-Nowak E, Kleczkowski A - PLoS ONE (2013)

Bottom Line: The differences in models affect choice of the strategy only for very cheap treatment and slow spreading disease.However for the combinations of parameters that are important from the epidemiological perspective (high infectiousness and expensive treatment) the models give similar results.Moreover, even where the choice of the strategy is different, the total cost spent on controlling the epidemic is very similar for both models.

View Article: PubMed Central - PubMed

Affiliation: M. Kac Complex Systems Research Center and M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland. kas@cs.stir.ac.uk

ABSTRACT
We analyse two models describing disease transmission and control on regular and small-world networks. We use simulations to find a control strategy that minimizes the total cost of an outbreak, thus balancing the costs of disease against that of the preventive treatment. The models are similar in their epidemiological part, but differ in how the removed/recovered individuals are treated. The differences in models affect choice of the strategy only for very cheap treatment and slow spreading disease. However for the combinations of parameters that are important from the epidemiological perspective (high infectiousness and expensive treatment) the models give similar results. Moreover, even where the choice of the strategy is different, the total cost spent on controlling the epidemic is very similar for both models.

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Related in: MedlinePlus

Control size, , as a function of both infectiousness, , and treatment cost, , for model 1 (left column) and model 2 (right column).Simulation parameters for top panel ((a) and (b)): ; for bottom panel ((c) and (d)): ; other parameters: , , , . Disease spreading on regular networks.
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pone-0063813-g006: Control size, , as a function of both infectiousness, , and treatment cost, , for model 1 (left column) and model 2 (right column).Simulation parameters for top panel ((a) and (b)): ; for bottom panel ((c) and (d)): ; other parameters: , , , . Disease spreading on regular networks.

Mentions: Control size, depends strongly on the cost of treatment, , and on the infectiousness of the disease, (fig. 6). For small and , both models suggest preventive control extended to the whole population (GS) (lower left part of each plot in fig. 6). In case of highly infectious disease and low treatment costs, model 1 predicts higher effectiveness of GS whereas model 2 selects LS as an optimal solution, upper left part of each plot in fig. 6. However, in both examined models the total cost of epidemic, X, is approximately the same, see fig. 3. As treatment cost, , increases, LS becomes the most cost-effective strategy. LS changes to NS when is of order 1 for small and of order 10 for high , regardless of the choice of the model or the exact value of , compare fig. 6a, b with fig. 6c, d.


Efficient control of epidemics spreading on networks: balance between treatment and recovery.

Oleś K, Gudowska-Nowak E, Kleczkowski A - PLoS ONE (2013)

Control size, , as a function of both infectiousness, , and treatment cost, , for model 1 (left column) and model 2 (right column).Simulation parameters for top panel ((a) and (b)): ; for bottom panel ((c) and (d)): ; other parameters: , , , . Disease spreading on regular networks.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3672130&req=5

pone-0063813-g006: Control size, , as a function of both infectiousness, , and treatment cost, , for model 1 (left column) and model 2 (right column).Simulation parameters for top panel ((a) and (b)): ; for bottom panel ((c) and (d)): ; other parameters: , , , . Disease spreading on regular networks.
Mentions: Control size, depends strongly on the cost of treatment, , and on the infectiousness of the disease, (fig. 6). For small and , both models suggest preventive control extended to the whole population (GS) (lower left part of each plot in fig. 6). In case of highly infectious disease and low treatment costs, model 1 predicts higher effectiveness of GS whereas model 2 selects LS as an optimal solution, upper left part of each plot in fig. 6. However, in both examined models the total cost of epidemic, X, is approximately the same, see fig. 3. As treatment cost, , increases, LS becomes the most cost-effective strategy. LS changes to NS when is of order 1 for small and of order 10 for high , regardless of the choice of the model or the exact value of , compare fig. 6a, b with fig. 6c, d.

Bottom Line: The differences in models affect choice of the strategy only for very cheap treatment and slow spreading disease.However for the combinations of parameters that are important from the epidemiological perspective (high infectiousness and expensive treatment) the models give similar results.Moreover, even where the choice of the strategy is different, the total cost spent on controlling the epidemic is very similar for both models.

View Article: PubMed Central - PubMed

Affiliation: M. Kac Complex Systems Research Center and M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland. kas@cs.stir.ac.uk

ABSTRACT
We analyse two models describing disease transmission and control on regular and small-world networks. We use simulations to find a control strategy that minimizes the total cost of an outbreak, thus balancing the costs of disease against that of the preventive treatment. The models are similar in their epidemiological part, but differ in how the removed/recovered individuals are treated. The differences in models affect choice of the strategy only for very cheap treatment and slow spreading disease. However for the combinations of parameters that are important from the epidemiological perspective (high infectiousness and expensive treatment) the models give similar results. Moreover, even where the choice of the strategy is different, the total cost spent on controlling the epidemic is very similar for both models.

Show MeSH
Related in: MedlinePlus