4.7 Article

Reconciling Egg- and Antigen-Based Estimates of Schistosoma mansoni Clearance and Reinfection: A Modeling Study

Journal

CLINICAL INFECTIOUS DISEASES
Volume 74, Issue 9, Pages 1557-1563

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/ciab679

Keywords

Diagnostics; temporal dynamics; POC-CCA; G-Score; Kato-Katz

Funding

  1. European Research Council [SCHISTO_PERSIST_680088]
  2. Wellcome [204820/Z/16/Z]
  3. Engineering and Physical Sciences Research Council [EP/T003618/1, EP/R01437X/1]
  4. Medical Research Council [MR/P025447/1]
  5. Wellcome Trust [204820/Z/16/Z] Funding Source: Wellcome Trust

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The impact of treatment for schistosomiasis in high-endemicity settings is short-lived due to less efficacy than expected and rapid reinfection. Current surveillance methods may underestimate infection prevalence, and improved diagnostics such as POC-CCA+ test may provide more accurate estimates of reinfection rate but face interpretation challenges. Frequent sampling is necessary to understand the clearance and reinfection dynamics post-treatment.
The impact of treatment for schistosomiasis in high-endemicity settings is short-lived because treatment is far less efficacious than the World Health Organization-recommended Kato-Katz method would suggest, and reinfection occurs more rapidly than is detected by current surveillance time frames. Background Despite decades of interventions, 240 million people have schistosomiasis. Infections cannot be directly observed, and egg-based Kato-Katz thick smears lack sensitivity, affected treatment efficacy and reinfection rate estimates. The point-of-care circulating cathodic antigen (referred to from here as POC-CCA+) test is advocated as an improvement on the Kato-Katz method, but improved estimates are limited by ambiguities in the interpretation of trace results. Method We collected repeated Kato-Katz egg counts from 210 school-aged children and scored POC-CCA tests according to the manufacturer's guidelines (referred to from here as POC-CCA+) and the externally developed G score. We used hidden Markov models parameterized with Kato-Katz; Kato-Katz and POC-CCA+; and Kato-Katz and G-Scores, inferring latent clearance and reinfection probabilities at four timepoints over six-months through a more formal statistical reconciliation of these diagnostics than previously conducted. Our approach required minimal but robust assumptions regarding trace interpretations. Results Antigen-based models estimated higher infection prevalence across all timepoints compared with the Kato-Katz model, corresponding to lower clearance and higher reinfection estimates. Specifically, pre-treatment prevalence estimates were 85% (Kato-Katz; 95% CI: 79%-92%), 99% (POC-CCA+; 97%-100%) and 98% (G-Score; 95%-100%). Post-treatment, 93% (Kato-Katz; 88%-96%), 72% (POC-CCA+; 64%-79%) and 65% (G-Score; 57%-73%) of those infected were estimated to clear infection. Of those who cleared infection, 35% (Kato-Katz; 27%-42%), 51% (POC-CCA+; 41%-62%) and 44% (G-Score; 33%-55%) were estimated to have been reinfected by 9-weeks. Conclusions Treatment impact was shorter-lived than Kato-Katz-based estimates alone suggested, with lower clearance and rapid reinfection. At 3 weeks after treatment, longer-term clearance dynamics are captured. At 9 weeks after treatment, reinfection was captured, but failed clearance could not be distinguished from rapid reinfection. Therefore, frequent sampling is required to understand these important epidemiological dynamics.

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