Comparison of means between high and low risk clusters of ORO incidence in 2024 (t-test, two samples assuming different variance). The number in parentheses indicates the standard deviation. *Per 10,000 inhabitants.

Comparison of means between high and low risk clusters of ORO incidence in 2024 (t-test, two samples assuming different variance). The number in parentheses indicates the standard deviation. *Per 10,000 inhabitants.

<p>Comparison of means between high and low risk clusters of ORO incidence in 2024 (t-test, two samples assuming different variance). The number in parentheses indicates the standard deviation. *Per 10,000 inhabitants.</p>

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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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