Hepatitis E Virus (HEV) Infection in the Context of the One Health Approach: A Systematic Review
Bibliographic record
Abstract
Hepatitis E virus (HEV) is a pathogen that has caused various epidemics and sporadic localized cases. It is considered to be a public health problem worldwide. HEV is a small RNA virus with a significant genetic diversity, a broad host range, and a heterogeneous geographical distribution. HEV is mainly transmitted via the faecal–oral route. However, some animals are considered to be natural or potential reservoirs of HEV, thus elucidating the zoonotic route of transmission via the environment through contact with these animals or consumption of their by-products. Other routes of human-to-human transmission are not negligible. The various human–animal–environment entities, taken under one health approach, show the circulation and involvement of the different species (mainly Paslahepevirus balayani and Rocahepevirus ratti) and genotypes in the spreading of HEV infection. Regarding P. balayani, eight genotypes have been described, of which five genotypes (HEV-1 to 4 and HEV-7) are known to infect humans, while six have been reported to infect animals (HEV-3 to HEV-8). Furthermore, the C1 genotype of the rat HEV strain (HEV-C1) is known to be more frequently involved in human infections than the HEV-C2 genotype, which is known to infect mainly ferrets and minks. Contamination can occur during run-off, flooding, and poor sanitation, resulting in all of these genotypes being disseminated in the environment, contaminating both humans and animals. This systematic review followed the PRISMA guidelines and was registered in PROSPERO 2025 CRD420251071192. This research highlights the importance of investigating the transmission routes and major circulating HEV genotypes in order to adopt a holistic approach for controlling its emergence and preventing future outbreaks. In addition, this article outlines the knowledge of HEV in Africa, underlining the absence of large-scale studies at the environmental, human, and animal levels, which could improve HEV surveillance on the continent.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".