Improving Spatial Estimates for COVID-19 Using Surveillance Data in Philadelphia

Lignende værker

• A Bayesian approach to improving spatial estimates of prevalence of COVID-19 after accounting for misclassification bias in surveillance data in Philadelphia, PA
  af: Goldstein, Neal D., et al.
  Udgivet: (2021)
• Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA
  af: Igor Burstyn, et al.
  Udgivet: (2020-06-01)
• Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA
  af: Burstyn, Igor, et al.
  Udgivet: (2020)
• Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA
  af: Burstyn, Igor, et al.
  Udgivet: (2020)
• Spatial inequities in COVID-19 vaccination in Philadelphia by race and income
  af: Angela D'Adamo, et al.
  Udgivet: (2025-06-01)