tropicalmed-06-00143-v2

1. Overview of Oropouche Virus and Its Vector

• Oropouche Virus (OROV): An arthropod-borne virus (arbovirus) causing disease in humans and animals.

  • Belongs to the Orthobunyavirus genus.

  • Primary vector: Culicoides paraensis (biting midge).

  • Secondary vectors include Culex quinquefasciatus, Culex venezuelensis, and Aedes serratus mosquitoes.

2. Objectives of the Study

• To characterize ecological and environmental features associated with OROV presence and its vector.

• Conducted a systematic review of published literature on OROV and vectors, leading to data synthesis and analysis.

3. Methodology

3.1 Search Process

• Databases Used: PubMed and Google Scholar.

  • PubMed Search: "Oropouche" returning 143 records.

  • Google Scholar Search: "Oropouche Virus" AND "South America" returning 598 records.

• Additional entomological studies sourced from Google Scholar using "Culicoides paraensis" AND "South America" returning 173 records.

3.2 Inclusion and Exclusion Criteria

• Inclusion Criteria: Studies with molecular/serologic detection and epidemiological data.

• Exclusion Criteria: Review articles, studies without primary data, duplicates, and inaccessible studies.

3.3 Data Extraction

• Analyzed records on study features including location, detection methods, ecological settings, and vector abundance.

4. Findings

4.1 Detection of OROV

• 56 articles focused on OROV detection showed varying host species tested (humans, non-human primates, etc.).

• Common detection methods included:

  • Serological methods: ELISA, IFA, CF.

  • Molecular methods: RT-PCR, qRT-PCR.

• 84% of studies found evidence of OROV (antibodies/nucleic acid).

4.2 Presence of the Vector

• Culicoides paraensis was located in at least 18 studies (52.9%).

• Common land use observed where the vector was detected included crop cultivation and livestock rearing.

4.3 Ecological and Environmental Features

• Presence of water bodies (rivers, streams) correlated with both OROV and vector detection.

• Primary forest environments showed a significant association with vector presence.

  • Land cover observations: undisturbed forests were commonly noted in OROV surveys.

5. Statistical Models and Analysis

5.1 Odds of Detecting OROV

• Logistic regression was performed to identify eco-environmental predictors for detecting OROV but did not yield significant predictors across multiple models

5.2 Correlation Analysis

• Found a significant correlation between acute infections and the presence of restingas (p = 0.0398).

6. Discussion and Conclusions

• Despite findings indicating common ecological aspects (land use, water source), no significant predictors emerged, highlighting data limitations.

• Continued research is essential to characterize environmental factors contributing to OROV transmission and vector dynamics.

7. Author Contributions

• Conceptualization by R.C.C. and C.E.S.W.; data curation, formal analysis, and writing by all authors with collaborative inputs.

8. References

• Notable references cited, including prior studies on OROV detection and vector dynamics.