| Download | - View final version: Detecting outbreaks in time-series data with RecentMax (PDF, 554 KiB)
|
|---|
| DOI | Resolve DOI: https://doi.org/10.5210/ojphi.v7i1.5779 |
|---|
| Author | Search for: Carter, Dave1; Search for: Martin, Joel D.1 |
|---|
| Affiliation | - National Research Council of Canada. Information and Communication Technologies
|
|---|
| Format | Text, Abstract |
|---|
| Conference | 2014 ISDS Conference: International Society for Disease Surveillance, December 9 - 11, 2014, Philadelphia, PA, USA |
|---|
| Subject | aberration detection; algorithm; outbreak detection; surveillance; situational awareness |
|---|
| Abstract | The RecentMax algorithm seeks to detect typical outbreaks of transmissible disease (particularly influenza-like illness) in time-series data better than existing algorithms like CDC EARS C1/C2/C3. |
|---|
| Publication date | 2015 |
|---|
| In | |
|---|
| Language | English |
|---|
| Peer reviewed | Yes |
|---|
| NPARC number | 23000531 |
|---|
| Export citation | Export as RIS |
|---|
| Report a correction | Report a correction (opens in a new tab) |
|---|
| Record identifier | 26726661-96b6-4580-8d40-2327b5070cd1 |
|---|
| Record created | 2016-07-28 |
|---|
| Record modified | 2020-06-02 |
|---|
