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Modeling of H1N1 Outbreak in Rajasthan: Methods and Approaches.

Gupta SD, Lal V, Jain R, Gupta OP - Indian J Community Med (2011)

Bottom Line: We attempted to fit the actual reported data and compared with prediction models.The duration of epidemic may be prolonged if R(0) is reduced.Decreasing the value of R(0) would decrease the proportion of total population infected by H1N1; however, the duration of the outbreak may be prolonged.

View Article: PubMed Central - PubMed

Affiliation: Institute of Health Management Research, Jaipur, India.

ABSTRACT

Background: Mathematical models could provide critical insights for informing preparedness and planning to deal with future epidemics of infectious disease.

Objective: The study modeled the H1N1 epidemic in the city of Jaipur, Rajasthan using mathematical model for prediction of progression of epidemic and its duration.

Materials and methods: We iterated the model for various values of R(0) to determine the effect of variations in R(0) onthe potential size and time-course of the epidemic, while keeping value of 1/γ constant. Further simulation using varying values of 1/γ were done, keeping value of R(0) constant. We attempted to fit the actual reported data and compared with prediction models.

Results: As R(0) increases,incidence of H1N1 rises and reaches peak early. The duration of epidemic may be prolonged if R(0) is reduced. Using the parameters R(0) as 1.4 and 1/γ as 3, it estimated that there would have been 656 actually infected individuals for each reported case.

Conclusion: The mathematical modeling can be used for predicting epidemic progression and impact of control measures. Decreasing the value of R(0) would decrease the proportion of total population infected by H1N1; however, the duration of the outbreak may be prolonged.

No MeSH data available.


Related in: MedlinePlus

Fitting of SIR Model
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Related In: Results  -  Collection

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Figure 3: Fitting of SIR Model

Mentions: For a population of urban Jaipur of 2.3 million and using the parameters R0 as 1.4 and 1/γ as 3, we obtained from the fitting, the estimate of 656 actually infected individuals for each reported case [Figure 3].


Modeling of H1N1 Outbreak in Rajasthan: Methods and Approaches.

Gupta SD, Lal V, Jain R, Gupta OP - Indian J Community Med (2011)

Fitting of SIR Model
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3104706&req=5

Figure 3: Fitting of SIR Model
Mentions: For a population of urban Jaipur of 2.3 million and using the parameters R0 as 1.4 and 1/γ as 3, we obtained from the fitting, the estimate of 656 actually infected individuals for each reported case [Figure 3].

Bottom Line: We attempted to fit the actual reported data and compared with prediction models.The duration of epidemic may be prolonged if R(0) is reduced.Decreasing the value of R(0) would decrease the proportion of total population infected by H1N1; however, the duration of the outbreak may be prolonged.

View Article: PubMed Central - PubMed

Affiliation: Institute of Health Management Research, Jaipur, India.

ABSTRACT

Background: Mathematical models could provide critical insights for informing preparedness and planning to deal with future epidemics of infectious disease.

Objective: The study modeled the H1N1 epidemic in the city of Jaipur, Rajasthan using mathematical model for prediction of progression of epidemic and its duration.

Materials and methods: We iterated the model for various values of R(0) to determine the effect of variations in R(0) onthe potential size and time-course of the epidemic, while keeping value of 1/γ constant. Further simulation using varying values of 1/γ were done, keeping value of R(0) constant. We attempted to fit the actual reported data and compared with prediction models.

Results: As R(0) increases,incidence of H1N1 rises and reaches peak early. The duration of epidemic may be prolonged if R(0) is reduced. Using the parameters R(0) as 1.4 and 1/γ as 3, it estimated that there would have been 656 actually infected individuals for each reported case.

Conclusion: The mathematical modeling can be used for predicting epidemic progression and impact of control measures. Decreasing the value of R(0) would decrease the proportion of total population infected by H1N1; however, the duration of the outbreak may be prolonged.

No MeSH data available.


Related in: MedlinePlus