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Modeling COVID-19 Latent Prevalence to Assess a Public Health Intervention at a State and Regional Scale: Retrospective Cohort Study

Modeling COVID-19 Latent Prevalence to Assess a Public Health Intervention at a State and Regional Scale: Retrospective Cohort Study

For the sake of brevity moving forward, we use the terms “latent prevalence” and “prevalence” interchangeably.In addition to North Carolina, interest also lay in the subpopulation served by Atrium Health’s greater Charlotte market.

Philip J Turk, Shih-Hsiung Chou, Marc A Kowalkowski, Pooja P Palmer, Jennifer S Priem, Melanie D Spencer, Yhenneko J Taylor, Andrew D McWilliams

JMIR Public Health Surveill 2020;6(2):e19353


Patient and Family Engagement in the Design of a Mobile Health Solution for Pediatric Asthma: Development and Feasibility Study

Patient and Family Engagement in the Design of a Mobile Health Solution for Pediatric Asthma: Development and Feasibility Study

As we set out to create a digital app for pediatric asthma SDM, we aimed to develop a design process that truly engaged the diverse cast of users involved in caring for a pediatric asthma patient.

Andrew McWilliams, Kelly Reeves, Lindsay Shade, Elizabeth Burton, Hazel Tapp, Cheryl Courtlandt, Andrew Gunter, Michael F Dulin

JMIR Mhealth Uhealth 2018;6(3):e68


Perceptions and Experiences of Internet-Based Testing for Sexually Transmitted Infections: Systematic Review and Synthesis of Qualitative Research

Perceptions and Experiences of Internet-Based Testing for Sexually Transmitted Infections: Systematic Review and Synthesis of Qualitative Research

Friedman and Bloodgood [36] reported one participant stating that they liked the idea of internet-based testing, as it meant:I don’t have to…have this long talk with a professional about sexual education.Ahmed-Little et al [35] and Gaydos et al [37] both reported

Tommer Spence, Inès Kander, Julia Walsh, Frances Griffiths, Jonathan Ross

J Med Internet Res 2020;22(8):e17667


Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

Time series analysis is a versatile and powerful modeling framework to link Web-based discussion and reveal the disease dynamics, as demonstrated by the extant research on various epidemics [16-18].The 2016 Zika epidemic provides a great opportunity to investigate

Shi Chen, Qian Xu, John Buchenberger, Arunkumar Bagavathi, Gabriel Fair, Samira Shaikh, Siddharth Krishnan

JMIR Public Health Surveill 2018;4(4):e10827


The Effects of Positive Affect and Episodic Future Thinking on Temporal Discounting and Healthy Food Demand and Choice Among Overweight and Obese Individuals: Protocol for a Pilot 2×2 Factorial Randomized Controlled Study

The Effects of Positive Affect and Episodic Future Thinking on Temporal Discounting and Healthy Food Demand and Choice Among Overweight and Obese Individuals: Protocol for a Pilot 2×2 Factorial Randomized Controlled Study

PosA: positive affect; EFT: episodic future thinking; ERT: episodic recent thinking.Participants and SettingParticipants will be recruited from the Charlotte, North Carolina, area community and asked to attend 2 in-person lab sessions separated by 5 days of

Sara M Levens, Sara J Sagui-Henson, Meagan Padro, Laura E Martin, Elisa M Trucco, Nina A Cooperman, Austin S Baldwin, Angelos P Kassianos, Noreen D Mdege

JMIR Res Protoc 2019;8(3):e12265


A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis

A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis

There were around 4 million Weibo posts acquired and archived.The tweets were acquired directly from Twitter via a contract between the School of Data Science, the University of North Carolina at Charlotte, and Twitter.

Shi Chen, Lina Zhou, Yunya Song, Qian Xu, Ping Wang, Kanlun Wang, Yaorong Ge, Daniel Janies

J Med Internet Res 2021;23(1):e24889