Malaria Journal (Sep 2020)

Ultra-sensitive RDT performance and antigen dynamics in a high-transmission Plasmodium falciparum setting in Mali

  • Emily N. Reichert,
  • Jen C. C. Hume,
  • Issaka Sagara,
  • Sara A. Healy,
  • Mahamadoun H. Assadou,
  • Merepen A. Guindo,
  • Rebecca Barney,
  • Andy Rashid,
  • Ihn Kyung Yang,
  • Allison Golden,
  • Gonzalo J. Domingo,
  • Patrick E. Duffy,
  • Hannah C. Slater

DOI
https://doi.org/10.1186/s12936-020-03389-0
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 10

Abstract

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Abstract Background The recent expansion of tools designed to accurately quantify malaria parasite-produced antigens has enabled us to evaluate the performance of rapid diagnostic tests (RDTs) as a function of the antigens they detect—typically histidine rich protein 2 (HRP2) or lactate dehydrogenase (LDH). Methods For this analysis, whole blood specimens from a longitudinal study in Bancoumana, Mali were used to evaluate the performance of the ultra-sensitive HRP2-based Alere™ Malaria Ag P.f RDT (uRDT). The samples were collected as part of a transmission-blocking vaccine trial in a high transmission region for Plasmodium falciparum malaria. Furthermore, antigen dynamics after successful anti-malarial drug treatment were evaluated in these samples using the Q-Plex Human Malaria Array (4-Plex) to quantify antigen concentrations. Results The uRDT had a 50% probability of a positive result at 207 pg/mL HRP2 [95% credible interval (CrI) 160–268]. Individuals with symptomatic infection remained positive by uRDT for a median of 33 days [95% confidence interval (CI) 28–47] post anti-malarial drug treatment. Biphasic exponential decay models accurately captured the population level post-treatment dynamics of both HRP2 and Plasmodium LDH (pLDH), with the latter decaying more rapidly. Motivated by these differences in rates of decay, a novel algorithm that used HRP2:pLDH ratios to predict if an individual had active versus recently cleared P. falciparum infection was developed. The algorithm had 77.5% accuracy in correctly classifying antigen-positive individuals as those with and without active infection. Conclusions These results characterize the performance of the ultra-sensitive RDT and demonstrate the potential for emerging antigen-quantifying technologies in the field of malaria diagnostics to be helpful tools in distinguishing between active versus recently cleared malaria infections.

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