Literature DB >> 33605883

Telehealth Demand Trends During the COVID-19 Pandemic in the Top 50 Most Affected Countries: Infodemiological Evaluation.

Mark Yu Zheng Wong1,2, Dinesh Visva Gunasekeran2,3, Simon Nusinovici2,4, Charumathi Sabanayagam2,4, Khung Keong Yeo4,5, Ching-Yu Cheng2,3,4, Yih-Chung Tham2,4.   

Abstract

BACKGROUND: The COVID-19 pandemic has led to urgent calls for the adoption of telehealth solutions. However, public interest and demand for telehealth during the pandemic remain unknown.
OBJECTIVE: We used an infodemiological approach to estimate the worldwide demand for telehealth services during COVID-19, focusing on the 50 most affected countries and comparing the demand for such services with the level of information and communications technology (ICT) infrastructure available.
METHODS: We used Google Trends, the Baidu Index (China), and Yandex Keyword Statistics (Russia) to extract data on worldwide and individual countries' telehealth-related internet searches from January 1 to July 7, 2020, presented as relative search volumes (RSV; range 0-100). Daily COVID-19 cases and deaths were retrieved from the World Health Organization. Individual countries' ICT infrastructure profiles were retrieved from the World Economic Forum Report.
RESULTS: Across the 50 countries, the mean RSV was 18.5 (SD 23.2), and the mean ICT index was 62.1 (SD 15.0). An overall spike in worldwide telehealth-related RSVs was observed from March 11, 2020 (RSV peaked to 76.0), which then tailed off in June-July 2020 (mean RSV for the period was 25.8), but remained higher than pre-March RSVs (mean 7.29). By country, 42 (84%) manifested increased RSVs over the evaluation period, with the highest observed in Canada (RSV=100) and the United States (RSV=96). When evaluating associations between RSV and the ICT index, both the United States and Canada demonstrated high RSVs and ICT scores (≥70.3). In contrast, European countries had relatively lower RSVs (range 3.4-19.5) despite high ICT index scores (mean 70.3). Several Latin American (Brazil, Chile, Colombia) and South Asian (India, Bangladesh, Pakistan) countries demonstrated relatively higher RSVs (range 13.8-73.3) but low ICT index scores (mean 44.6), indicating that the telehealth demand outstrips the current ICT infrastructure.
CONCLUSIONS: There is generally increased interest and demand for telehealth services across the 50 countries most affected by COVID-19, highlighting the need to scale up telehealth capabilities, during and beyond the pandemic. ©Mark Yu Zheng Wong, Dinesh Visva Gunasekeran, Simon Nusinovici, Charumathi Sabanayagam, Khung Keong Yeo, Ching-Yu Cheng, Yih-Chung Tham. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 19.02.2021.

Entities:  

Keywords:  COVID-19; infodemiology; internet; telehealth; telemedicine

Year:  2021        PMID: 33605883     DOI: 10.2196/24445

Source DB:  PubMed          Journal:  JMIR Public Health Surveill        ISSN: 2369-2960


  18 in total

1.  Telehealth Utilization in Response to the COVID-19 Pandemic: Current State of Medical Provider Training.

Authors:  Ragan DuBose-Morris; Christina Coleman; Sonja I Ziniel; Dana A Schinasi; S David McSwain
Journal:  Telemed J E Health       Date:  2021-12-30       Impact factor: 5.033

2.  Achieving Spread, Scale Up and Sustainability of Video Consulting Services During the COVID-19 Pandemic? Findings From a Comparative Case Study of Policy Implementation in England, Wales, Scotland and Northern Ireland.

Authors:  Sara E Shaw; Gemma Hughes; Joseph Wherton; Lucy Moore; Rebecca Rosen; Chrysanthi Papoutsi; Alex Rushforth; Joanne Morris; Gary W Wood; Stuart Faulkner; Trisha Greenhalgh
Journal:  Front Digit Health       Date:  2021-12-20

3.  Identification of Differentially Expressed Genes in COVID-19 and Integrated Bioinformatics Analysis of Signaling Pathways.

Authors:  Linjie Fang; Tingyu Tang; Mengqi Hu
Journal:  Genet Res (Camb)       Date:  2021-12-24       Impact factor: 1.588

4.  Expanding Video Consultation Services at Pace and Scale in Scotland During the COVID-19 Pandemic: National Mixed Methods Case Study.

Authors:  Joseph Wherton; Trisha Greenhalgh; Sara E Shaw
Journal:  J Med Internet Res       Date:  2021-10-07       Impact factor: 5.428

5.  Preparedness of Primary Health Care Leaders During COVID-19 Outbreak, Riyadh, Saudi Arabia: A Qualitative Study.

Authors:  Maha Alakeely; Arwa Almutari; Nazish Masud; Bader Altulaihi
Journal:  Risk Manag Healthc Policy       Date:  2021-10-19

6.  The Use of Helplines and Telehealth Support in Aotearoa/New Zealand During COVID-19 Pandemic Control Measures: A Mixed-Methods Study.

Authors:  Alina Pavlova; Katrina Witt; Bonnie Scarth; Theresa Fleming; Denise Kingi-Uluave; Vartika Sharma; Sarah Hetrick; Sarah Fortune
Journal:  Front Psychiatry       Date:  2022-01-27       Impact factor: 4.157

7.  Misinformation About and Interest in Chlorine Dioxide During the COVID-19 Pandemic in Mexico Identified Using Google Trends Data: Infodemiology Study.

Authors:  Jonathan Matias Chejfec-Ciociano; Juan Pablo Martínez-Herrera; Alexa Darianna Parra-Guerra; Ricardo Chejfec; Francisco José Barbosa-Camacho; Juan Carlos Ibarrola-Peña; Gabino Cervantes-Guevara; Guillermo Alonso Cervantes-Cardona; Clotilde Fuentes-Orozco; Enrique Cervantes-Pérez; Benjamín García-Reyna; Alejandro González-Ojeda
Journal:  JMIR Infodemiology       Date:  2022-01-27

8.  COVID-19 awareness, knowledge and perception towards digital health in an urban multi-ethnic Asian population.

Authors:  Cong Ling Teo; Miao Li Chee; Kai Hui Koh; Rachel Marjorie Wei Wen Tseng; Shivani Majithia; Sahil Thakur; Dinesh Visva Gunasekeran; Simon Nusinovici; Charumathi Sabanayagam; Tien Yin Wong; Yih-Chung Tham; Ching-Yu Cheng
Journal:  Sci Rep       Date:  2021-05-24       Impact factor: 4.379

9.  Lessons Learned during a Naturalistic Study of Online Treatment for Pediatric Rehabilitation.

Authors:  Naomi Gefen; Shoshana Steinhart; Maurit Beeri; Patrice L Weiss
Journal:  Int J Environ Res Public Health       Date:  2021-06-21       Impact factor: 3.390

10.  Social Media Big Data: The Good, The Bad, and the Ugly (Un)truths.

Authors:  Alton M K Chew; Dinesh Visva Gunasekeran
Journal:  Front Big Data       Date:  2021-06-01
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