@article{95347,
  author = {Bhatia S and Lassmann B and Cohn E and Desai AN and Carrion M and Kraemer MUG and Herringer M and Brownstein J and Madoff L and Cori A and Nouvellet P},
  title = {Using digital surveillance tools for near real-time mapping of the risk of infectious disease spread},
  abstract = {<jats:title>Abstract</jats:title><jats:p>Data from digital disease surveillance tools such as ProMED and HealthMap can complement the field surveillance during ongoing outbreaks. Our aim was to investigate the use of data collected through ProMED and HealthMap in real-time outbreak analysis. We developed a flexible statistical model to quantify spatial heterogeneity in the risk of spread of an outbreak and to forecast short term incidence trends. The model was applied retrospectively to data collected by ProMED and HealthMap during the 2013–2016 West African Ebola epidemic and for comparison, to WHO data. Using ProMED and HealthMap data, the model was able to robustly quantify the risk of disease spread 1–4 weeks in advance and for countries at risk of case importations, quantify where this risk comes from. Our study highlights that ProMED and HealthMap data could be used in real-time to quantify the spatial heterogeneity in risk of spread of an outbreak.</jats:p>},
  year = {2021},
  journal = {npj Digital Medicine},
  volume = {4},
  publisher = {Springer Science and Business Media LLC},
  issn = {2398-6352},
  url = {https://www.nature.com/articles/s41746-021-00442-3.pdf},
  doi = {10.1038/s41746-021-00442-3},
  language = {eng},
}