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A Probabilistic Estimation of the Basic Reproduction Number: A Case of Control Strategy of Pneumonia

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dc.contributor.author Ong’ala Jacob Otieno, Mugisha Joseph,Oleche Paul,
dc.date.accessioned 2020-08-25T08:43:39Z
dc.date.available 2020-08-25T08:43:39Z
dc.date.issued 2014
dc.identifier.citation 3 en_US
dc.identifier.uri https://repository.maseno.ac.ke/handle/123456789/2342
dc.description.abstract Deterministic models have been used in the past to understand the epidemiology of infectious diseases, most importantly to estimate the basic reproduction number, Ro by using disease parameters. However, the approach overlooks variation on the disease parameter(s) which are function of Ro and can introduce random effect on Ro. In this paper, we estimate the Ro as a random variable by first developing and analyzing a deterministic model for transmission patterns of pneumonia, and then compute the probability distribution of Ro using Monte Carlo Markov Chain (MCMC) simulation approach. A detailed analysis of the simulated transmission data, leads to probability distribution of Ro as opposed to a single value in the convectional deterministic modeling approach. Results indicate that there is sufficient information generated when uncertainty is considered in the computation of Ro and can be used to describe the effect of parameter change in deterministic models en_US
dc.publisher cience Publishing Group en_US
dc.subject Basic Reproduction Number, MCMC, Pneumonia Model, Uncertainty, Sensitivity Analysis en_US
dc.title A Probabilistic Estimation of the Basic Reproduction Number: A Case of Control Strategy of Pneumonia en_US
dc.type Article en_US


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