1-D marginal posterior distributions to Bernalillo (left column), Santa Fe (middle column), and Valencia (right column).

1-D marginal posterior distributions to Bernalillo (left column), Santa Fe (middle column), and Valencia (right column).

<p>Top row: PDFs for <i>t</i><sub>0,<i>r</i></sub>. <i>t</i><sub>0,<i>r</i></sub> values are negative as it is measured from June , 2020, and the PDFs imply that infections for the Summer wave started in late May. Second r...

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Bibliographic Details
Main Author: Cosmin Safta (11105442) (author)
Other Authors: Jaideep Ray (11105439) (author), Wyatt Bridgman (21865902) (author)
Published: 2025
Subjects:
Biotechnology
Ecology
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
three adjacent counties
simple anomaly detector
anomaly detector based
accommodate multiple units
various areal units
model parameters condition
calibrated epidemic model
single areal unit
div >< p
detecting outbreaks using
data comprises time
areal unit
epidemiological model
symptomatic patients
results suggest
relies solely
rates outperforms
posterior distribution
originally designed
new mexico
high variance
framed within
findings show
field estimation
field </
epidemiological dynamics
count data
conventional algorithm
bayesian context
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Description
Summary:<p>Top row: PDFs for <i>t</i><sub>0,<i>r</i></sub>. <i>t</i><sub>0,<i>r</i></sub> values are negative as it is measured from June , 2020, and the PDFs imply that infections for the Summer wave started in late May. Second row: PDFs for <i>N</i><sub><i>r</i></sub>. Third row: PDFs for <i>k</i>. Bottom row: PDFs for .</p>

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