Dataset Information

Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.

ABSTRACT: This study hypothesized that national population health literacy might reflect on their keywords searching. We applied Google searches for "wash hands" and "face mask" during January 19 to February 18 as a surrogate of national population health literacy among 21 countries, and examine whether google searches for "wash hands" and "face masks" would protect from increased numbers of confirmed cases of among 21 countries We found the increased google searches for "wash hands" from January 19 to February 18, 2020, correlated with a lower spreading speed of COVID-19 from February 19 to March 10, 2020 among 21 countries (Pearson's correlation coefficient of -0.70, P < 0.001). The result highlights the importance of public awareness of hand washing in preventing COVID-19 disease spreading.

SUBMITTER: Lin YH

PROVIDER: S-EPMC7151250 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.

Lin Yu-Hsuan YH Liu Chun-Hao CH Chiu Yu-Chuan YC

Brain, behavior, and immunity 20200410

This study hypothesized that national population health literacy might reflect on their keywords searching. We applied Google searches for "wash hands" and "face mask" during January 19 to February 18 as a surrogate of national population health literacy among 21 countries, and examine whether google searches for "wash hands" and "face masks" would protect from increased numbers of confirmed cases of among 21 countries We found the increased google searches for "wash hands" from January 19 to Fe ...[more]

PMID: 32283286

Similar Datasets

Project description:PURPOSE:Epidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data. DESIGN:Search data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity. PARTICIPANTS:Populations by country that searched Google's search engine using our study terms. MAIN OUTCOME MEASURES:Percent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches. RESULTS:We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P = 0.40). CONCLUSIONS:Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.

Dataset Information

Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.

Publications

Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets