vk3rrj5

Property	Value
?:abstract	Study Objectives: Public interest in diseases during outbreaks has been previously studied by examining internet activity via Google Trends (Google, Mountain View, California), a tool that measures the popularity of internet searches longitudinally and geographically Recently, Google Trends has been used as a surveillance and retrospective epidemiological tool to study the impact of COVID-19 in China, Taiwan, France, and Iran However, studies that focus on the United States are significantly lacking Using Google Trends, our aim in this study was to assess the extent of the public’s perceived exposure to COVID-19 as it relates to disease prevalence during the early phase of the pandemic in the United States Methods: We utilized Google Trends to determine the search activity for: “Do I have coronavirus,” “How to get tested for coronavirus,” “What is coronavirus,” “Signs and symptoms of coronavirus” and “How is coronavirus spread ” We collected four weeks of Search Volume Index (SVI) data between February 17th and March 16th, 2020 The mean SVIs for the 5 states with the highest and lowest number of COVID-19 confirmed cases (as of March 16, 2020) were calculated for each query To obtain the number of confirmed COVID-19 cases in the United States, we referred to a tracker provided by Johns Hopkins University Scatterplots were then created to compare SVI and number of COVID-19 cases on a state level Pearson correlations were determined to examine the association between SVI and the number of COVID-19 confirmed cases as of March 16, 2020 Results: Peak SVI for all queries took place on March 12, just a day prior to the U S declaration of national emergency “Do I have coronavirus” (p=0 005), “How to get tested for coronavirus” (p=0 01), and “Signs and symptoms of coronavirus” (p=0 05) were identified as having statistically significant differences in mean SVI between states with the highest and lowest number of COVID-19 cases (Table 1) Mean SVI for “Do I have coronavirus” and “How to get tested for coronavirus” was higher in the states with the most COVID-19 cases compared to the bottom 5 states with the least cases However, mean SVI for “Signs and symptoms of coronavirus” was higher in the bottom 5 states compared to the top 5 states There were no statistically significant differences in mean SVI for the remaining queries: “What is coronavirus” (p=0 48) and “How is coronavirus spread” (p=0 21) When looking at all 50 states and the District of Columbia, we found that SVI also positively correlated with the number of confirmed COVID-19 cases for “Do I have coronavirus” and “How to get tested for coronavirus” (R= 387, p=0 005;R=0 367, p=0 008) No statistically significant correlations were found for “How is coronavirus spread” (p=0 45), “What is coronavirus” (p=0 39), and “Signs and symptoms of coronavirus” (p=0 22) Conclusion: Non-generic queries in Google Trends may yield better insights into health information-seeking behavior Specifically, queries formatted as “How to get tested for ____” and “Do I have _____” could reflect perceived exposure to a communicable disease on a population level To our knowledge, our study is the first to use Google Trends to distinguish queries that reflect perceived exposure to COVID-19 from those that are borne out by general interest in the United States Early access to population health data is crucial and potentially life-saving during outbreaks Digital tools such as Google Trends may help bridge the gap in knowledge and transparency [Formula presented]
is ?:annotates of	<https://research.tib.eu/covid-19/entity/3vk3rrj5_hasAnnotation_C1825598>
?:creator	<https://research.tib.eu/covid-19/entity/Pascual%2C_K._J.%3B_Pourmand%2C_A.>
?:journal	Annals_of_Emergency_Medicine
?:license	unk
?:publication_isRelatedTo_Disease	<https://research.tib.eu/covid-19/entity/COVID-19>
is ?:relation_isRelatedTo_publication of	<https://research.tib.eu/covid-19/entity/3vk3rrj5_HAS_C2744535_AFFECTS_C5203670>
?:source	WHO
?:title	283 Using Google Trends to Determine Perceived Viral Exposure during the Early Phase of the COVID-19 Pandemic in the United States
?:type	<https://research.tib.eu/covid-19/vocab/Publication>
?:who_covidence_id	#898437
?:year	2020

Property

Value

?:abstract

Study Objectives: Public interest in diseases during outbreaks has been previously studied by examining internet activity via Google Trends (Google, Mountain View, California), a tool that measures the popularity of internet searches longitudinally and geographically Recently, Google Trends has been used as a surveillance and retrospective epidemiological tool to study the impact of COVID-19 in China, Taiwan, France, and Iran However, studies that focus on the United States are significantly lacking Using Google Trends, our aim in this study was to assess the extent of the public’s perceived exposure to COVID-19 as it relates to disease prevalence during the early phase of the pandemic in the United States Methods: We utilized Google Trends to determine the search activity for: “Do I have coronavirus,” “How to get tested for coronavirus,” “What is coronavirus,” “Signs and symptoms of coronavirus” and “How is coronavirus spread ” We collected four weeks of Search Volume Index (SVI) data between February 17th and March 16th, 2020 The mean SVIs for the 5 states with the highest and lowest number of COVID-19 confirmed cases (as of March 16, 2020) were calculated for each query To obtain the number of confirmed COVID-19 cases in the United States, we referred to a tracker provided by Johns Hopkins University Scatterplots were then created to compare SVI and number of COVID-19 cases on a state level Pearson correlations were determined to examine the association between SVI and the number of COVID-19 confirmed cases as of March 16, 2020 Results: Peak SVI for all queries took place on March 12, just a day prior to the U S declaration of national emergency “Do I have coronavirus” (p=0 005), “How to get tested for coronavirus” (p=0 01), and “Signs and symptoms of coronavirus” (p=0 05) were identified as having statistically significant differences in mean SVI between states with the highest and lowest number of COVID-19 cases (Table 1) Mean SVI for “Do I have coronavirus” and “How to get tested for coronavirus” was higher in the states with the most COVID-19 cases compared to the bottom 5 states with the least cases However, mean SVI for “Signs and symptoms of coronavirus” was higher in the bottom 5 states compared to the top 5 states There were no statistically significant differences in mean SVI for the remaining queries: “What is coronavirus” (p=0 48) and “How is coronavirus spread” (p=0 21) When looking at all 50 states and the District of Columbia, we found that SVI also positively correlated with the number of confirmed COVID-19 cases for “Do I have coronavirus” and “How to get tested for coronavirus” (R= 387, p=0 005;R=0 367, p=0 008) No statistically significant correlations were found for “How is coronavirus spread” (p=0 45), “What is coronavirus” (p=0 39), and “Signs and symptoms of coronavirus” (p=0 22) Conclusion: Non-generic queries in Google Trends may yield better insights into health information-seeking behavior Specifically, queries formatted as “How to get tested for ____” and “Do I have _____” could reflect perceived exposure to a communicable disease on a population level To our knowledge, our study is the first to use Google Trends to distinguish queries that reflect perceived exposure to COVID-19 from those that are borne out by general interest in the United States Early access to population health data is crucial and potentially life-saving during outbreaks Digital tools such as Google Trends may help bridge the gap in knowledge and transparency [Formula presented]

is ?:annotates of