| Property | Value |
|---|
|
?:abstract
|
-
OBJECTIVES: Rapid detection and surveillance of COVID-19 is essential to reducing spread of the virus. Inadequate screening capacity has hampered COVID-19 detection, while traditional infectious disease response has been delayed due to significant demands for healthcare resources, time and personnel. This study investigated whether an online health decision-support tool could supplement COVID-19 surveillance and detection in China and the USA. SETTING: Daily website traffic to Thermia was collected from China and the USA, and cross-correlation analyses were used to assess the designated lag time between the daily time series of Thermia sessions and COVID-19 case counts from 22 January to 23 April 2020. PARTICIPANTS: Thermia is a validated health decision-support tool that was modified to include content aimed at educating users about Centers for Disease Control and Prevention recommendations on COVID-19 symptoms. An advertising campaign was released on Microsoft Advertising to refer searches for COVID-19 symptoms to Thermia. RESULTS: The lead times observed for Thermia sessions to COVID-19 case reports was 3 days in China and 19 days in the USA. We found negative cross-correlation between the number of Thermia sessions and rates of influenza A and B, possibly due to the decreasing prevalence of influenza and the lack of specificity of the system for identification of COVID-19. CONCLUSION: This study suggests that early deployment of an online campaign and modified health decision-support tool may support identification of emerging infectious diseases like COVID-19. Researchers and public health officials should deploy web campaigns as early as possible in an epidemic to detect, identify and engage those potentially at risk to help prevent transmission of the disease.
|
|
is
?:annotates
of
|
|
|
?:creator
|
|
|
?:journal
|
|
|
?:license
|
|
|
?:publication_isRelatedTo_Disease
|
|
|
?:source
|
|
|
?:title
|
-
Early detection of COVID-19 in China and the USA: summary of the implementation of a digital decision-support and disease surveillance tool
|
|
?:type
|
|
|
?:who_covidence_id
|
|
|
?:year
|
|
![[This page as RDF]](https://research.tib.eu/covid-19/static/rdf-icon.gif){kind=icon}