Modeling the development of acquired clinical immunity to Plasmodium falciparum malaria

Abstract

Individuals living in regions where malaria is endemic develop an acquired immunity to malaria which enables them to remain asymptomatic while still carrying parasites. Field studies indicate that cumulative exposure to a variety of diverse Plasmodium parasites is required for the transition from symptomatic to asymptomatic malaria. This study used a simulation model of the within-host dynamics of P. falciparum to investigate the development of acquired clinical immunity under different transmission conditions and levels of parasite diversity. Antibodies developed to P. falciparum erythrocyte membrane protein 1 (PfEMP1), a clonally variant molecule, were assumed to be a key human immunological response to P. falciparum infection, along with responses to clonally conserved but polymorphic antigens. The time to the development of clinical immunity was found to be proportional to parasite diversity and inversely proportional to transmission intensity. The effect of early termination of symptomatic infections by chemotherapy was investigated and found not to inhibit the host's ability to develop acquired immunity. However, the time required to achieve this state was approximately double that compared to when no treatment was administered. This study demonstrates that an immune response primarily targeted against PfEMP1 has the ability to reduce clinical symptoms of infections irrespective of whether treatment is administered, supporting its role in the development of acquired clinical immunity. The results also illustrate a novel use for simulation models of P. falciparum infections, investigation of the influence of intervention strategies on the development of naturally acquired clinical immunity.

FIG. 1.

Flowchart of the simulation model used to mimic the within-host dynamics of P. falciparum infections. Bi(a,b) represents the use of a binomial distribution with sample size a and probability b. When a was large, a normal distribution was used as an approximation of the binomial. N(a,b) represents the use of a normal distribution with mean a and standard deviation b. Ab, antibody; NSI, nonspecific immunity.

FIG. 2.

Sample of output from 500 simulations with an infection approximately every 60 days and a population of 1,000 var genes. A) Number of fever occurrences, B) number of days with parasite density of >1,000/μl, and C) proportion of infections that were successful as blood-stage infections lasting more than 10 days. Shaded regions in A and B represent the interquartile range of the simulated data; dots represent the 5th and 95th percentiles. In C, the line represents the fitted regression model with an asymptote of 0.87.

FIG. 3.

Relationship between parasite diversity (size of the var gene pool) and transmission rate (expressed as the average number of days between infections) and the time (years) required to develop clinical immunity (contours) in the absence of chemotherapy.

FIG. 4.

Comparison of the number of infections without a fever (untreated population; dotted line) and the number not requiring treatment (treated population; solid line) for an infection rate of one infection every 60 days and a population of 1,000 var genes.