Data revision patterns for different indicators.

Data revision patterns for different indicators.

<p>(A) Mean percentage of counts reported relative to the values revised 300 days later, averaged over all reference dates and plotted by reporting lag for Massachusetts. Shaded bands represent the 10th to 90th percentile interval. (B) Mean values of COVID-19-related fractions normalized by th...

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Bibliographic Details
Main Author: Jingjing Tang (419372) (author)
Other Authors: Aaron Rumack (4592206) (author), Bryan Wilder (747661) (author), Roni Rosenfeld (19137) (author)
Published: 2025
Subjects:
Medicine
Neuroscience
Biotechnology
Developmental Biology
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tentative surveillance values
public health reporting
improves computational efficiency
given estimation date
generates distributional forecasts
finalized surveillance values
early reporting stages
weekly dengue
time forecasting
situational awareness
seriously degrade
scalable solution
rf ),
like illness
insurance claims
forecasting accuracy
existing methods
data revisions
daily covid
confirmed cases
available revisions
antigen tests
19 data
100x compared
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Summary:<p>(A) Mean percentage of counts reported relative to the values revised 300 days later, averaged over all reference dates and plotted by reporting lag for Massachusetts. Shaded bands represent the 10th to 90th percentile interval. (B) Mean values of COVID-19-related fractions normalized by their corresponding revised values after 300 days, also averaged over all reference dates and plotted by lag for Massachusetts.</p>

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