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Fig. 3 | BMC Bioinformatics

Fig. 3

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

Fig. 3

Results of the local sensitivity analysis. Parameters shown affect the disease variables the most in the reference state. Dark blue indicates a parameter that has a large negative influence on a variable, whereas dark red indicates a large positive influence on a variable. \(\varvec{k_M}\)—Elimination rate of merozoites by immune effectors, \(\varvec{\beta }\)—Probability of infection of RBCs with free roaming merozoites, \(\varvec{\lambda _B}\)—Production rate of immune cells, \(\varvec{\lambda _X}\)—Birth rate of healthy RBCs, \(\varvec{\mu _X}\)—Natural death rate of RBCs, \(\varvec{\mu _N}\)—Natural death rate of iRBCs, \(\varvec{\mu _P}\)—Death rate of innate immune cells/ immune effectors, \(\varvec{\mu _M}\)—Natural death rate of merozoites, \(\varvec{k_2}\)—Proliferation rate of immune effectors by merozoites, \(\varvec{k_1}\)—Proliferation rate of immune effectors by iRBCs, \({\varvec{r}}\)—Number of merozoites released per bursting iRBC. Cross-hatching indicates parameters that were not present in a model

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