The in-vivo dynamics of Plasmodium falciparum HRP2: implications for the use of rapid diagnostic tests in malaria elimination

Background Rapid diagnostic tests (RDTs) that rely on the detection of Plasmodium falciparum histidine-rich protein 2 (PfHRP2) have become key tools for diagnosing P. falciparum infection. The utility of RDTs can be limited by PfHRP2 persistence, however it can be a potential benefit in low transmission settings where detection of persistent PfHRP2 using newer ultra-sensitive PfHRP2 based RDTs can serve as a surveillance tool to identify recent exposure. Better understanding of the dynamics of PfHRP2 over the course of a malaria infection can inform optimal use of RDTs. Methods A previously published mathematical model was refined to mimic the production and decay of PfHRP2 during a malaria infection. Data from 15 individuals from volunteer infection studies were used to update the original model and estimate key model parameters. The refined model was applied to a cohort of patients from Namibia who received treatment for clinical malaria infection for whom longitudinal PfHRP2 concentrations were measured. Results The refinement of the PfHRP2 dynamic model indicated that in malaria naïve hosts, P. falciparum parasites of the 3D7 strain produce 33.6 × 10−15 g (95% CI 25.0–42.1 × 10−15 g) of PfHRP2 in vivo per parasite replication cycle, with an elimination half-life of 1.67 days (95% CI 1.11–3.40 days). The refined model included these updated parameters and incorporated individualized body fluid volume calculations, which improved predictive accuracy when compared to the original model. The performance of the model in predicting clearance of PfHRP2 post treatment in clinical samples from six adults with P. falciparum infection in Namibia improved when using a longer elimination half-life of 4.5 days, with 14% to 67% of observations for each individual within the predicted range. Conclusions The updated mathematical model can predict the growth and clearance of PfHRP2 during the production and decay of a mono-infection with P. falciparum, increasing the understanding of PfHRP2 antigen dynamics. This model can guide the optimal use of PfHRP2-based RDTs for reliable diagnosis of P. falciparum infection and re-infection in endemic settings, but also for malaria surveillance and elimination programmes in low transmission areas. Supplementary Information The online version contains supplementary material available at 10.1186/s12936-022-04245-z.


This additional file contains:
Material S1: Anti-malarial treatment details for IBSM individuals Table S1: Antimalarial treatment given for the 15 IBSM individuals from four different studies, as identified with the clinical trial name and clinical trial ID. The antimalarial and dose given at day of treatment on Day 7 is detailed for each subject.
Material S2: Methods to fit PfHRP2 model to the 6 individuals from the Namibia longitudinal cohort study Performance measures were the number (%) of PfHRP2 observations within the range of the predicted minimum and maximum PfHRP2 concentrations, the residual sum of squares (RSS) and the residual mean sum of square (RMSE).     Parasitemia was monitored by twice daily blood sampling from Day 4 until treatment on Day 7.
Subjects were admitted to the clinical unit, treated with an antimalarial agent as detailed in Table S1.

Methodology to simulate parasitemia dynamics
The parasitemia growth and clearance were simulated for each of the six individuals from the study in Namibia. The parasite growth was simulated from a sine-wave growth model (4) with parameter estimates derived from Equation S1 applied to 177 IBSM subjects inoculated with 3D7 as detailed in Wockner et al. 2020 (5). Parasitemia growth for individual and time , denoted (parasites/mL), was simulated as: log 10 (Y ij ) = ( + 0 ) + ( + 1 ) × + × sin ( 2 + ( + 2 )) Equation S1 where is days from initial infection and it is assumed that = y-intercept set to 0, = parasite growth rate per day set to 0.758, = sine-wave amplitude set to 0.645, = sine-wave phase shift set to 6.34 following Wockner et al. 2020 (5), and = duration of the parasite life-cycle set to 2 days.
Individual level random effects for , and denoted by 0 , 1 and 2 , respectively, were assumed to follow a multivariate normal distribution with zero mean and variance-covariance given by the following matrix: The parasitemia growth model was used to simulate parasitemia until the value of the parasitemia recorded at time of study enrolment. Antimalarial treatment was administered at study enrolment and it was assumed that parasite clearance immediately commenced, which followed a first-order exponential decay with a constant clearance rate of 0.3 log10 parasites/mL per day. The simulated parasitemia growth and clearance for each individual with the observed parasitemia densities are shown in Figure S2. The replicating parasites, assumed to occur at the observed peaks during the growth phase and every two days during the clearance phase as represented by open circles in Figure S2, were used as the parasitemia input into the PfHRP2 model.

Methodology to impute body weights
The body weights of the study individuals were not available, and were imputed from an estimated gender-and-age specific weight curve for Namibia individuals (Figure 2, (6) Table 3 and were used to estimate the individualised blood volume and extracellular fluid volume as input in the PfHRP2 model.