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Application of time series methods for dengue cases in North India (Chandigarh)

  • Kumar ShashvatEmail author
  • Rikmantra Basu
  • Amol P. Bhondekar
Original Article
  • 30 Downloads

Abstract

Background and aim

Time series study is of paramount importance especially in developing countries such as India. The objective of this study is to forecast the number of dengue cases by applying time series models. Furthermore, this study also aims to uncover the correlation of ecological variables with dengue cases using a p value test. The ecological variables considered are the rainfall (with a 2-month lag period) and average relative humidity. An evaluation of host factors such as age and gender is done with the number of cases to determine the most affected strata.

Materials and methods

Monthly data on dengue cases from 2014 to 2017 are taken from the integrated disease surveillance programme, Government of India, and data on ecological variables, humidity and rainfall are taken from www.Indiastat.com. A 2-month lag period is considered for rainfall.

Results

These data were analysed by the autoregressive integrated moving average (ARIMA) and exponential smoothing model (ES). Predictive performance of these techniques was assessed by evaluation parameters such as the Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute error and mean absolute scaled error. Applying time series models was useful in the prediction. There were many more males than females according to the data for 2014–2017. The Akaike information criterion (AIC), Bayesian information criterion (BIC) and mean absolute scaled error for ARIMA are 48.6526, 448.333333, 449.30008, 453.08 and 0.507826, respectively.

Conclusions

Based on model indices such as the Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute error and mean absolute scaled error, the ARIMA performed better than the ES model. Rainfall at the 2-month lag was correlated with the number of cases.

Keywords

Time series Forecast ARIMA Exponential smoothing Dengue cases 

Notes

Compliance with ethical standards

Ethics and consent

The data used in this manuscript were sourced from the Integrated Diseases Surveillance Programme, Government of India, with permission no. E-151913.

Conflict of interest

The authors declare no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Kumar Shashvat
    • 1
    Email author
  • Rikmantra Basu
    • 1
  • Amol P. Bhondekar
    • 2
  1. 1.Department of Computer Science & EngineeringNational Institute of TechnologyDelhiIndia
  2. 2.Central Scientific Instruments OrganizationChandigarhIndia

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