Spatial analysis clusters with high and low incidences of ORO according to relative risk (RR) during 2024 period.

<p>(A) High-risk cluster in Bahia State (B) High-risk clusters in Espírito Santo State. Data obtained from SatScan software version 10.0. The maps were built using ArcGIS version 9.1. Source of map base layers: IBGE: <a href="https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapas-est...

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Bibliographic Details
Main Author:	Camila Lorenz (3481175) (author)
Other Authors:	Thiago Salomão de Azevedo (16406703) (author), Maria Anice Mureb Sallum (7866398) (author), Francisco Chiaravalloti-Neto (3481184) (author)
Published:	2025
Subjects:	Biotechnology Ecology Cancer Science Policy Infectious Diseases Virology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified south america since providing valuable insights machine learning algorithm borne virus responsible risk spatial clusters risk clusters tended country &# 8217 socioenvironmental factors contributing key factors behind orov differed markedly oropouche fever outbreak confirmed human cases species distribution modeling 258 oro cases history </ p key factors oropouche fever risk regions socioenvironmental variables serologically confirmed modeling study entire country use change soybean plantations sharper increase satscan software restricted access primarily confined orov circulation oro distribution largest epidemic including poverty identify areas highest incidence amazon region
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Spatial analysis clusters with high and low incidences of ORO according to relative risk (RR) during 2024 period.

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