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Skip search results from other journals and go to results- 103 Journal of Medical Internet Research
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Beliefs that the specific localities where respondents are currently living are far away from coronavirus hot spot areas and that COVID-19 is not dangerous or exaggerated contributed to 14.2% (76/536) and 30.2% (162/536) of the false assurances, respectively.
JMIR Form Res 2025;9:e66751
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Telemedicine Booths for Screening Cardiovascular Risk Factors: Prospective Multicenter Study
coronavirus
JMIR Hum Factors 2025;12:e57032
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Assessing COVID-19 Mortality in Serbia’s Capital: Model-Based Analysis of Excess Deaths
Reference 16: Coronavirus questions that will not go away: interrogating urban and socio-spatial implicationscoronavirus
JMIR Public Health Surveill 2025;11:e56877
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The evolving nature of the coronavirus [75-77], coupled with the rapidly changing landscape of pandemic management policies [78-80], presented a constant need for flexibility and adaptability. The virus’s mutations necessitated continuous updates to the platform’s algorithms to ensure that users would have access to the most up-to-date information.
JMIR Form Res 2025;9:e53339
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Reference 16: Clinical features of patients infected with 2019 novel coronavirus in Wuhan, Chinacoronavirus
JMIR Form Res 2025;9:e66509
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A basic search was conducted with phrases such as “coronavirus,” “SARS-Co V-2,” and “COVID-19” on Twitter. Using an iterative method, keywords were added and removed in order to find the most suitable for the data search. The final list of 10 keywords for data extraction included “COVID-19,” “pandemic,” “SARS-Co V-2,” “coronavirus,” “SARS-Co V-2 virus,” “social distancing,” “self-isolation,” “self-quarantine,” “quarantine,” and “new variant.” The total number of tweets extracted totaled 867,485.
JMIR Form Res 2025;9:e59687
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Citywide testing data came from the NYC coronavirus data repository [10].
We initially sought to run a Poisson regression analysis comparing counts of tests and positive test results to demographic variables while using population as an offset; however, we found the data to be overdispersed and chose to use negative binomial regressions.
JMIR Public Health Surveill 2025;11:e52972
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Reference 6: Management of pediatric rheumatic patients in Kazakhstan during the coronavirus diseasecoronavirusTheme Issue: Digital Approaches for Pediatric Healthcare Delivery During the Coronavirus (Covid-19) Pandemic
JMIR Pediatr Parent 2025;8:e65751
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