Serological and viral prevalence of Oropouche virus (OROV): A systematic review and meta-analysis from 2000-2024 including human, animal, and vector surveillance studies
Notice bibliographique
Résumé
Abstract Background Oropouche virus (OROV) is an emerging arbovirus primarily transmitted by biting midges and is increasingly recognized as a public health threat in Central and South America. With over 11,000 confirmed cases reported in 2024, a ten-fold increase from the previous year, its transmission dynamics and true burden remain poorly understood due to diagnostic challenges and fragmented surveillance systems. Objective This systematic review and meta-analysis (SRMA) synthesizes OROV prevalence data in humans and summarizes the available data for vectors and non-human hosts sampled between 2000 and 2024 to provide updated estimates and identify key surveillance gaps. Methods We systematically searched Web of Science, PubMed, Embase, Medline, and LILACS for OROV seroprevalence and viral prevalence studies in human, insect, and animal populations, published up to September 12, 2024. The review protocol was registered with PROSPERO (CRD42024551000). Studies were extracted in duplicate, and data were meta-analyzed using generalized linear mixed-effects models. Risk of bias was appraised using a modified Joanna Briggs Institute checklist. Results We included 71 articles reporting serological or viral prevalence of OROV across nine countries. Between 2000–2024, pooled human seroprevalence among individuals with febrile illness or suspected of Oropouche infection was 12.6% [95% CI 5.3-26.9%] across four South American countries and seroprevalence of 1.1% [95% CI 0.5-2.3%] was observed in asymptomatic groups. Viral prevalence among individuals with febrile illness or suspected of Oropouche infection was 1.5% [0.8-3.0%] across seven South American countries and Haiti. Most studies used convenience sampling and RT-PCR or hemagglutination assays. In vector populations, positive OROV prevalence in Aedes aegypti and Culex quinquefasciatus was reported in two of 18 sources, while 10.0% and 7.5% animal host prevalence was reported in dogs and cattle, respectively. We found high risk of bias in 11.3% of studies in our critical appraisal, with most animal, human, and vector studies falling in the moderate risk of bias range. Conclusions Despite rising numbers of OROV reported cases, prevalence estimates remain limited by sparse surveillance and variable methodology. This review highlights the urgent need for standardized serological assays, community-based studies, and expanded surveillance in animal and vector reservoirs. A One Health approach is essential to monitor OROV transmission and inform regional preparedness efforts. Author summary Oropouche virus is a pathogen carried by biting midges and some other insect vectors that causes fever and flu-like illness in people, and it can also be carried by animals. Cases of Oropouche virus have been rising in Central and South America, with approximately 11,000 confirmed cases in 2024 – a ten-times increase from the previous year. Despite the growing outbreaks, we still know little about how many people and animals have been infected; studies testing at-risk populations for viral infection or the presence of antibodies are valuable tools in filling these knowledge gaps. To address this, we reviewed such studies published from 2000 to 2024 that tested people, animals, and insects for Oropouche virus, and produced estimates of the virus’ prevalence in these populations to better understand its spread and detection. We found that in humans with suspected infection in four South American countries, i.e. with fever and related symptoms, 12.6% of them had antibodies for Oropouche – indicating a history of infection. The prevalence of active viral infections in similar populations was 1.5%. In asymptomatic people, the prevalence of antibodies was lower, at 1.1%. We also found small presence of the virus in insect vectors and animals, namely dogs and cattle. Overall, the studies had varying methods especially with regards to diagnostic tests, and the number of studies is still very limited, especially in animals and insects. Our findings highlight the urgent need for better tools, standardized research methods, and an increase in community surveillance studies across species to better understand Oropouche, prevent future outbreaks, and best respond to the health needs of affected communities.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,019 | 0,037 |
| Bibliométrie | 0,012 | 0,013 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».