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Non-linear phenomena in host-parasite interactions.

  • RM Anderson
  • RM May
  • S Gupta
Parasitology 1989; :
Abstract
The paper examines non-linear dynamical phenomena in host-parasite interactions by reference to a series of different problems ranging from the impact on transmission of control measures based on vaccination and chemotherapy, to the effects of immunological responses targeted at different stages in a parasite's life-cycle. Throughout, simple mathematical models are employed to aid in interpretation. Analyses reveal that the influence of a defined control measure on the prevalence or intensity of infection, whether vaccination or drug treatment, is non-linearly related to the magnitude of control effort (as defined by the proportion of individuals vaccinated or treated with a drug). Consideration of the relative merits of gametocyte and sporozoite vaccines against malarial parasites suggests that very high leves of cohort immunization will be required to block transmission in endemic areas, with the former type of vaccine being more effective in reducing transmission for a defined level of coverage and the latter being better with respect to a reduction in morbidity. The inclusion of genetic elements in analyses of the transmission of helminth parasites reveals complex non-linear patterns of change in the abundance of different parasite genotypes under selection pressures imposed by either the host immunological defences or the application of chemotherapeutic agents. When resistance genes are present in parasite populations, the degree to which abundance can be suppressed by chemotherapy depends critically on the frequency and intensity of application, with intermediate values of the former being optimal. A more detailed consideration of the impact of immunological defences on parasite population growth within an individual host, by reference to the erythrocytic cycle of malaria, suggests that the effectiveness of a given immunological response is inversely related to the life-expectancy of the target stage in the parasite's developmental cycle.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
default 0.0 1.0
Id Name Initial quantity Compartment Fixed
S Merozoites 1.0 default
T T-lymphocytes 0.0001 default
X RBC 120.0 default
Xy Erythrocyte abundance 120.0 default
Y iRBC 0.0 default
Yi porportion of infected rbc nan default

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
v1 v1 ∅ = X

lambda
v10 v10 Y = ∅

g * Y * T
v11 v11 ∅ = T

k * Y * T
v2 v2 X = ∅

mu * X
v3 v3 S + X = Y

beta * X * S
v4 v4 Y = ∅

alfa * Y
v5 v5 ∅ = S

alfa * r * Y
v6 v6 S = ∅

d * S
v7 v7 S = ∅

h * S * T
v8 v8 ∅ = T

gamma * S * T
v9 v9 T = ∅

a * T

Global parameters

Id Value
a 0.05
alfa 0.2
beta 0.1
d 72.0
g 0.05
gamma 1.0
h 0.1
k 0.05
lambda 1.0
mu 0.00833
r 16.0

Local parameters

Id Value Reaction

Assignment rules

Definition
Xy = X + Y
Yi = Y / (X + Y)

Rate rules

Definition

Algebraic rules

Definition
Definition
Trigger Assignments