Identifying Locations with Possible Undetected Imported Severe Acute Respiratory Syndrome Coronavirus 2 Cases by Using Importation Predictions

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  De Salazar, Pablo Martinez ; Niehus, René ; Taylor, Aimee ; Buckee, Caroline O’Flaherty ; Lipsitch, Marc
• Description:
  Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exported from mainland China could lead to self-sustained outbreaks in other countries. By February 2020, several countries were reporting imported SARS-CoV-2 cases. To contain the virus, early detection of imported SARS-CoV-2 cases is critical. We used air travel volume estimates from Wuhan, China, to international destinations and a generalized linear regression model to identify locations that could have undetected imported cases. Our model can be adjusted to account for exportation of cases from other locations as the virus spreads and more information on importations and transmission becomes available. Early detection and appropriate control measures can reduce the risk for transmission in all locations.
• Subjects:
  Betacoronavirus Coronavirus Infections Covid-19 Humans Linear Models Pandemics Pneumonia, Viral Travel
• Source:
  Emerg Infect Dis. 26(7):1465-1469
• Pubmed ID:
  32207679
• Pubmed Central ID:
  PMC7323530
• Document Type:
  Journal Article
• Funding:
  R35 GM124715/GM/NIGMS NIH HHS/United States ; U54 GM088558/GM/NIGMS NIH HHS/United States
• Place as Subject:
  China
• Location:
  Asia
• Volume:
  26
• Issue:
  7
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:2c5fa188a9d87962f5774ff4ece463e4abf5c114b12d40061d4a8f8c45da83d3
• Download URL:
  https://stacks.cdc.gov/view/cdc/90192/cdc_90192_DS1.pdf
• File Type:
  [PDF - 1.62 MB ]