This paper is in the following e-collection/theme issue:

Public Health Data Analytics (88)

Published on in Vol 6, No 1 (2014):

Autoregressive Integrated Moving Average (ARIMA) Modeling of Time Series of Local Telephone Triage Data for Syndromic Surveillance

Autoregressive Integrated Moving Average (ARIMA) Modeling of Time Series of Local Telephone Triage Data for Syndromic Surveillance

Autoregressive Integrated Moving Average (ARIMA) Modeling of Time Series of Local Telephone Triage Data for Syndromic Surveillance

Authors of this article:

Micael Widerström1 ;   Maria Omberg2 ;   Martin Ferm3 ;   Ann-Katrine Pettersson4 ;   Malin Rundvik Eriksson2 ;   Ingela Eckerdal4 ;   Johan Wiström5
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  1. Adnan M, Gao X, Bai X, Newbern E, Sherwood J, Jones N, Baker M, Wood T, Gao W. Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering. JMIR Public Health and Surveillance 2020;6(3):e18281 View
  2. Khan F, Gupta R. ARIMA and NAR based prediction model for time series analysis of COVID-19 cases in India. Journal of Safety Science and Resilience 2020;1(1):12 View