A Methodology For Performing Global Uncertainty And Sensitivity Analysis In Systems Biology
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TLDR
This work develops methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models and provides a complete methodology for performing these analyses, in both deterministic and stochastic settings, and proposes novel techniques to handle problems encountered during these types of analyses.About:
This article is published in Journal of Theoretical Biology.The article was published on 2008-09-07 and is currently open access. It has received 2014 citations till now. The article focuses on the topics: Uncertainty analysis & Sensitivity analysis.read more
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Optimal targeting of seasonal influenza vaccination toward younger ages is robust to parameter uncertainty
Martial L. Ndeffo Mbah,Jan Medlock,Jan Medlock,Lauren Ancel Meyers,Alison P. Galvani,Jeffrey P. Townsend +5 more
TL;DR: This analysis demonstrated that previous recommendations of targeting schoolchildren and young adults are generally robust in the face of uncertainty, but when the outcome measure is to minimize deaths, years of life loss, or contingent valuation, uncertainty analysis identified scenarios under which it is optimal to target people at high risk for complications, even when vaccine are in abundance.
Journal ArticleDOI
Comparing the impact of artemisinin-based combination therapies on malaria transmission in sub-Saharan Africa.
TL;DR: DP should be considered as a replacement for AL as first-line treatment of uncomplicated malaria in highly endemic P. falciparum communities, and the predictions of the model were shown to be robust to the empirical uncertainty summarizing the epidemiological parameters.
Journal ArticleDOI
Modeling the Potential Impact of Host Population Survival on the Evolution of M. tuberculosis Latency
TL;DR: A mathematical model is used to show that indeed, Mycobacterium Tuberculosis persistence is optimal for an intermediate duration of latency and level of activation, suggesting that human co-evolution has lead to host immunity, which keeps MTB below its evolutionary optimum.
Journal ArticleDOI
A mathematical model for HIV prevention and control among men who have sex with men in China.
Z Lu,L M Wang,Lu Wang,Hui Xing,Gengfeng Fu,Hongjing Yan,Zhenpeng Li,Junjie Xu,Ning Wang,Kai Wang,Zhihang Peng +10 more
TL;DR: The 90-90-90 strategy alone may not eliminate the HIV epidemic in Chinese MSM, and Behavioural and biologic interventions are the most effective interventions to control the HIV/AIDS epidemic among MSM.
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The impact of within-vector parasite development on the extrinsic incubation period.
Lauren M. Childs,Olivia Prosper +1 more
TL;DR: In this paper, the authors used the Simons Foundation Collaboration Grant for Mathematicians (SCF-DMS) and National Science Foundation (NSF)-DMS Award (DBI-1300426) to support the work of the University of Tennessee, Knoxville.
References
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Book
An Introduction to Multivariate Statistical Analysis
TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
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A comparison of three methods for selecting values of input variables in the analysis of output from a computer code
TL;DR: In this paper, two sampling plans are examined as alternatives to simple random sampling in Monte Carlo studies and they are shown to be improvements over simple sampling with respect to variance for a class of estimators which includes the sample mean and the empirical distribution function.
Journal Article
Factorial sampling plans for preliminary computational experiments
TL;DR: The proposed experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects, those changes in an output due solely to changes in a particular input.
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Factorial sampling plans for preliminary computational experiments
TL;DR: In this article, the problem of designing computational experiments to determine which inputs have important effects on an output is considered, and experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects.