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Assessing and Improving Data Integrity in Web-Based Surveys: Comparison of Fraud Detection Systems in a COVID-19 Study

Assessing and Improving Data Integrity in Web-Based Surveys: Comparison of Fraud Detection Systems in a COVID-19 Study

We collected data from November 2021 through February 2022 for the Philly CEAL Common Survey, a cross-sectional study using a web-based survey to assess how the COVID-19 pandemic and response have impacted individuals, neighborhoods, and communities across the city of Philadelphia, Pennsylvania. The Checklist for Reporting Results on Internet E-Surveys was used to guide the reporting of our methods and results (Multimedia Appendix 1) [26].

Stephen Bonett, Willey Lin, Patrina Sexton Topper, James Wolfe, Jesse Golinkoff, Aayushi Deshpande, Antonia Villarruel, José Bauermeister

JMIR Form Res 2024;8:e47091

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Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Entering 2021, the metropolitan areas with the largest persistence were New York City (1.83), Miami (1.00), Philadelphia (1.61), Tampa (1.08), Charlotte (1.29), and Orlando (1.04). These areas are at high risk for increased COVID-19 caseloads during the first full week of January, with a potential for explosive growth.

Theresa B Ann Oehmke, Lori A Post, Charles B Moss, Tariq Z Issa, Michael J Boctor, Sarah B Welch, James F Oehmke

J Med Internet Res 2021;23(2):e26081

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