Literature DB >> 20210378

Sensitivity and uncertainty analyses for a sars model with time-varying inputs and outputs.

Robert G McLeod1, John F Brewster, Abba B Gumel, Dean A Slonowsky.   

Abstract

This paper presents a statistical study of a deterministic model for the transmission dynamics and control of severe acute respiratory syndrome (SARS). The effect of the model parameters on the dynamics of the disease is analyzed using sensitivity and uncertainty analyses. The response (or output) of interest is the control reproduction number, which is an epidemiological threshold governing the persistence or elimination of SARS in a given population. The compartmental model includes parameters associated with control measures such as quarantine and isolation of asymptomatic and symptomatic individuals. One feature of our analysis is the incorporation of time-dependent functions into the model to reflect the progressive refinement of these SARS control measures over time. Consequently, the model contains continuous time-varying inputs and outputs. In this setting, sensitivity and uncertainty analytical techniques are used in order to analyze the impact of the uncertainty in the parameter estimates on the results obtained and to determine which parameters have the largest impact on driving the disease dynamics.

Entities:  

Year:  2006        PMID: 20210378     DOI: 10.3934/mbe.2006.3.527

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  15 in total

1.  Threshold dynamics of a non-autonomous SEIRS model with quarantine and isolation.

Authors:  Mohammad A Safi; Mudassar Imran; Abba B Gumel
Journal:  Theory Biosci       Date:  2012-01-06       Impact factor: 1.919

Review 2.  Sensitivity analysis of infectious disease models: methods, advances and their application.

Authors:  Jianyong Wu; Radhika Dhingra; Manoj Gambhir; Justin V Remais
Journal:  J R Soc Interface       Date:  2013-07-17       Impact factor: 4.118

3.  Simulation Study on Effects of Order and Step Size of Runge-Kutta Methods that Solve Contagious Disease and Tumor Models.

Authors:  Z Wang; Q Wang; D J Klinke
Journal:  J Comput Sci Syst Biol       Date:  2016-09-30

4.  Mathematical assessment of the effect of traditional beliefs and customs on the transmission dynamics of the 2014 Ebola outbreaks.

Authors:  Folashade B Agusto; Miranda I Teboh-Ewungkem; Abba B Gumel
Journal:  BMC Med       Date:  2015-04-23       Impact factor: 8.775

5.  Dynamics of Mycobacterium and bovine tuberculosis in a human-buffalo population.

Authors:  A S Hassan; S M Garba; A B Gumel; J M-S Lubuma
Journal:  Comput Math Methods Med       Date:  2014-09-02       Impact factor: 2.238

6.  Mathematical analysis of a model for zoonotic visceral leishmaniasis.

Authors:  Nafiu Hussaini; Kamaldeen Okuneye; Abba B Gumel
Journal:  Infect Dis Model       Date:  2017-12-13

7.  Mathematical model of Zika virus with vertical transmission.

Authors:  F B Agusto; S Bewick; W F Fagan
Journal:  Infect Dis Model       Date:  2017-05-23

8.  Predicting and Evaluating the Epidemic Trend of Ebola Virus Disease in the 2014-2015 Outbreak and the Effects of Intervention Measures.

Authors:  Zuiyuan Guo; Dan Xiao; Dongli Li; Xiuhong Wang; Yayu Wang; Tiecheng Yan; Zhiqi Wang
Journal:  PLoS One       Date:  2016-04-06       Impact factor: 3.240

9.  Mathematical Model of Three Age-Structured Transmission Dynamics of Chikungunya Virus.

Authors:  Folashade B Agusto; Shamise Easley; Kenneth Freeman; Madison Thomas
Journal:  Comput Math Methods Med       Date:  2016-04-05       Impact factor: 2.238

10.  The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China.

Authors:  Pei-Yu Liu; Sha He; Li-Bin Rong; San-Yi Tang
Journal:  Infect Dis Poverty       Date:  2020-09-16       Impact factor: 4.520

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