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Table 3 Uncertainty analysis results in \(\%\) contribution

From: Uncovering the effects of heterogeneity and parameter sensitivity on within-host dynamics of disease: malaria as a case study

 

Merozoites

iRBCs

Anderson

\(\mu _P\)

\(k_1\)

\(\mu _P\)

\(k_1\)

42.0

13.2

48.3

15.2

Li

\(\mu _P\)

\(k_1\)

\(\mu _P\)

\(k_1\)

45.4

32.2

48.1

34.1

Niger

\(\mu _P\)

\(k_1\)

\(\mu _P\)

\(k_1\)

34.3

14.4

55.8

23.4

Okrinya

r

\(\lambda _X\)

\(\lambda _X\)

\(\mu _Y\)

36.8

17.6

56.7

9.37

  1. The table indicates which parameters contribute the most to uncertainty in the model outputs of merozoites and iRBCs. \(\mu _P\)—Death rate of immune effectors, \(k_1\)—Proliferation rate of immune effectors by iRBCs, r—Number of merozoites released per bursting iRBC, \(\lambda _X\)—Birth rate of healthy RBCs, \(\mu _Y\)—Natural death rate of iRBCs
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BMC Bioinformatics

ISSN: 1471-2105

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