The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.

Journal: Journal of biomedical informatics
PMID: 29496631

Abstract

INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response.

Authors

  • Yirong Chen
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, 117549, Singapore.
  • Collins Wenhan Chu
    Genome Institute of Singapore, 60 Biopolis Street, Genome, 138672, Singapore.
  • Mark I C Chen
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, 117549, Singapore; Department of Clinical Epidemiology, Communicable Disease Centre, Tan Tock Seng Hospital, Singapore, Moulmein Road, 308433, Singapore.
  • Alex R Cook
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, 117549, Singapore. Electronic address: alex.richard.cook@gmail.com.

Keywords

External Resources

Popular Topics
Recent Journals