tropicalmed-07-00111-v2

Citation Details

• Authors: Sciancalepore, S., Schneider, M.C., Kim, J., Galan, D.I., Riviere-Cinnamond, A.

• Title: Presence and Multi-Species Spatial Distribution of Oropouche Virus in Brazil within the One Health Framework

• Journal: Tropical Medicine and Infectious Disease

• Year: 2022

• Volume: 7

• Article: 111

• DOI: 10.3390/tropicalmed7060111

• Received: 29 April 2022

• Accepted: 17 June 2022

• Published: 20 June 2022

• License: Creative Commons Attribution (CC BY)

Abstract

• Oropouche Virus (OROV): An emerging vector-borne arbovirus with epidemic potential, infecting over 500,000 people.

• Transmission: Primarily through midge and mosquito vectors, with wildlife reservoirs in non-human primates and sloths.

• Goal: To document OROV's presence in Brazil using a One Health approach and geospatial techniques.

• Literature Review: Scoping review from 2000 to 2021; 14 out of 27 states reported OROV presence across 67 municipalities, mainly in northern Brazil.

• Findings: Identified in various species (humans, vectors, non-human primates, sloth). Environmental and socioeconomic factors influencing OROV’s spread warrant further investigation.

Introduction

• History: OROV identified in Trinidad (1955), first in Brazil (1960) in Pará.

• Epidemiology: Major epidemics in urban centers such as Pará, Amapá, and Amazonas.

• Impact: Responsible for approximately 500,000 infections in Latin America, with ongoing geographical spread.

OROV Outbreaks in Brazil

• Historical Cases (1961-2006): 131,000 cases in Pará; similar outbreaks in Amazonas and Rondonia.

• Current Status: OROV is the second most common arbovirus in the Brazilian Amazon after dengue viral infections.

Table 1: Major Outbreaks of OROV in Brazil

Infection and Symptoms

• Transmission: Animal to human spillover through bites from infected vectors.

• Clinical Symptoms: Fever, chills, photophobia, skin rashes, dizziness, potential for serious complications (e.g., meningitis).

• Natural Maintenance Cycles: Includes both urban (via insect vectors) and sylvatic cycles (involving mammals such as non-human primates and sloths).

One Health Framework

• Definition: An interdisciplinary approach to optimal health for humans, animals, and the environment, focusing on their interconnections.

• Purpose: Document OROV in Brazil utilizing One Health and geospatial techniques, predict spillover occurrences and environmental/socioeconomic drivers, and strengthen surveillance efforts.

Study Methodology

• Data Collection: Involves articles from 2000 to 2021 across multiple databases.

• Scoping Review: 117 articles reviewed, 41 identified natural cases in Brazil, totaling 458 individual cases.

• Geocoding: Data stratified by species and geographic municipality to visualize OROV's prevalence.

• GIS Tools: Utilized to create visual maps indicating OROV's distribution by location and case reports.

Results

• Geographical Distribution: OROV detected in 14 of Brazil’s 27 states, predominantly in the Amazon region.

• Biomes and Cases: Tropical and subtropical moist broadleaf forests and dry broadleaf forests as primary biomes for OROV cases.

Table 2: OROV Presence by Species, Biome and GDP per Capita

(Example from provided data)

Discussion

4.1 Drivers Associated with the Occurrence of Outbreaks

• Environmental Factors: Presence of vector/hosts; habitat degradation; biome adaptation.

• Social Factors: Human development activities, migration, living conditions, and public health access significantly influence OROV spread.

4.2 Expansion of Cases in Brazil

• Emerging Areas: Reported cases now identified in non-traditional habitats outside the Amazon.

• Potential for Urban Transmission: Increased risk of OROV becoming entrenched in urban environments due to vector species adaptability.

4.3 Limitations to This Study

• Secondary Data Issues: Possible inaccuracies in reporting and lab testing variations impacting results.

• Undermethodology: Limitations due to reliance on prior studies’ data, public health policy effects on case counting.

Conclusion

• One Health Integration: Advocates for comprehensive OROV control across human, animal, and environmental sectors.

• Surveillance Needs: Emphasizes the importance of spatial data in informing public health policy and best practices for outbreak prevention and response.

• Call for Further Research: Encourages future studies on socio-environmental determinants of OROV incidence.