Abstract
Background: Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis.
Methodology and principal findings: We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 19 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FEA-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animal hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03–0.48) with FEA-SD showing highest sensitivity (0.89, 95% CI: 0.65–1.00).
Conclusions/significance: Our findings suggest that the parasitologic technique FEA-SD and the molecular technique qPCR are the most promising techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.
| Original language | English |
|---|---|
| Article number | e0010389 |
| Pages (from-to) | e0010389 |
| Journal | PLoS Neglected Tropical Diseases |
| Volume | 16 |
| Issue number | 5 |
| Early online date | 6 May 2022 |
| DOIs | |
| Publication status | Published - 6 May 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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