A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern.
Pei-Ying KobresJean-Paul ChretienMichael A JohanssonJeffrey J MorganPai-Yei WhungHarshini MukundanSara Y Del ValleBrett M ForsheyTalia M QuandelacyMatthew BiggerstaffCecile ViboudSimon PollettPublished in: PLoS neglected tropical diseases (2019)
Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.
Keyphrases
- zika virus
- public health
- dengue virus
- sars cov
- coronavirus disease
- infectious diseases
- aedes aegypti
- electronic health record
- global health
- meta analyses
- current status
- emergency department
- social media
- big data
- randomized controlled trial
- liquid chromatography
- systematic review
- machine learning
- artificial intelligence
- deep learning