<p>The top panel plots the Mastitis series for the year 2010. Detection scores for each algorithm are shown as vertical bars, stacked to give a final alarm score which scale is shown in the secondary axis. The gray rectangle is used to mark the limit in the secondary axis which corresponds to the reporting threshold – here 7. The bottom panel shows a similar graph for the BLV series.</p
To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA sig...
<p>Alarm periods (defined by 2 alarm signals (black dots) within the lag period) successfully detect...
We present a simple, fast, and easily interpretable procedure that results in faster detection of ou...
<p>The table rows and graph nodes show different final alarm scores used as the reporting threshold....
Background Syndromic surveillance research has focused on two main themes: the search for data sour...
Syndromic surveillance research has focused on two main themes: the search for data sources that can...
<p>Panel A shows the sensitivity of detection compared to false alarms rate when all three algorithm...
BACKGROUND: Syndromic surveillance research has focused on two main themes: the search for data sour...
<p>The top table shows the detection score for the three algorithms used, in the last 5 days. Next t...
This paper aims to explore early outbreak detection methods for measles. Two methods adapted from st...
BACKGROUND: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter ...
AbstractThe threat of bioterrorism has stimulated interest in enhancing public health surveillance t...
Background: Syndromic surveillance research has focused on two main themes: the search for data sour...
<p>Patient criterion: control chart based on the number of infected patients; incidence patient crit...
One of the main areas of public health surveillance is infectious disease surveillance. With infecti...
To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA sig...
<p>Alarm periods (defined by 2 alarm signals (black dots) within the lag period) successfully detect...
We present a simple, fast, and easily interpretable procedure that results in faster detection of ou...
<p>The table rows and graph nodes show different final alarm scores used as the reporting threshold....
Background Syndromic surveillance research has focused on two main themes: the search for data sour...
Syndromic surveillance research has focused on two main themes: the search for data sources that can...
<p>Panel A shows the sensitivity of detection compared to false alarms rate when all three algorithm...
BACKGROUND: Syndromic surveillance research has focused on two main themes: the search for data sour...
<p>The top table shows the detection score for the three algorithms used, in the last 5 days. Next t...
This paper aims to explore early outbreak detection methods for measles. Two methods adapted from st...
BACKGROUND: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter ...
AbstractThe threat of bioterrorism has stimulated interest in enhancing public health surveillance t...
Background: Syndromic surveillance research has focused on two main themes: the search for data sour...
<p>Patient criterion: control chart based on the number of infected patients; incidence patient crit...
One of the main areas of public health surveillance is infectious disease surveillance. With infecti...
To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA sig...
<p>Alarm periods (defined by 2 alarm signals (black dots) within the lag period) successfully detect...
We present a simple, fast, and easily interpretable procedure that results in faster detection of ou...