Genetic Characterization of Plasmodium falciparum Histidine-Rich Protein 2 Deletions and Their Impact on Malaria Interventions in Odisha, India
Bibliographic record
Abstract
Diagnostic escape via Plasmodium falciparum (P. falciparum) histidine-rich protein 2 (pfhrp2) gene deletions is a major potential hurdle for global malaria elimination efforts. We investigated the prevalence of pfhrp2 gene deletions in 15 malaria-endemic villages in the state of Odisha, India, and modeled their impact on an ongoing in-country malaria intervention program. We found that 61.6% of subpatent P. falciparum infections (i.e., rapid diagnostic test [RDT]-negative and positive by polymerase chain reaction [PCR]) had pfhrp2 gene deletions, which were predominantly located in the exon 2 region (96.2%) and largely identified in samples from febrile individuals (82.6%). DNA sequencing and protein diversity features were characterized in a subset of samples from individuals with subpatent infections carrying intact pfhrp2 exon 2 loci. Our analyses revealed novel amino acid repeat motifs (231-293 amino acids), and these variant repeat sequences differed from those of RDT+/PCR+ samples. We also evaluated the state-sponsored mass screening and treatment intervention in the context of pfhrp2 gene deletions. We found that mass screening and treatment conducted alongside additional interventions (e.g., long-lasting insecticidal net distribution, indoor residual spraying) reduced the relative risk of infection for both P. falciparum parasites harboring a pfhrp2 deletion (adjusted relative risk ratio [aRRR] = 0.3; 95% CI = 0.1-1.0) and P. falciparum parasites with intact pfhrp2 genes (aRRR = 0.4; 95% CI = 0.2-1.1) when compared with the use of mass screening and treatment by RDT alone. Combined, our findings highlight the need for alternative diagnostic targets and tools as India moves toward its goal of malaria elimination by 2030.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".