This paper is in the following e-collection/theme issue:

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Infodemiology and Infoveillance (1369) Machine Learning (1501) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Innovative Methods in Public Health and Surveillance (336) Outbreak and Pandemic Preparedness and Management (1743) JMIR Theme Issue: COVID-19 Special Issue (2461) Behavioural Surveillance for Public Health (235) Public (e)Health, Digital Epidemiology and Public Health Informatics (750) Hygiene and Infection Prevention (325) Infectious Diseases (non-STD/STI) (1592)

Published on in Vol 7, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22880, first published .
The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis

The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis

The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis

Authors of this article:

Milad Asgari Mehrabadi1 Author Orcid Image ;   Nikil Dutt1, 2, 3 Author Orcid Image ;   Amir M Rahmani1, 2, 4, 5 Author Orcid Image
Article Authors Cited by (5) Tweetations (6) Metrics

Journals

  1. Rovetta A. The Impact of COVID-19 on Conspiracy Hypotheses and Risk Perception in Italy: Infodemiological Survey Study Using Google Trends. JMIR Infodemiology 2021;1(1):e29929 View
  2. Imamura T, Watanabe A, Serizawa Y, Nakashita M, Saito M, Okada M, Ogawa A, Tabei Y, Soumura Y, Nadaoka Y, Nakatsubo N, Chiba T, Sadamasu K, Yoshimura K, Noda Y, Iwashita Y, Ishimaru Y, Seki N, Otani K, Imamura T, Griffith M, DeToy K, Suzuki M, Yoshida M, Tanaka A, Yauchi M, Shimada T, Oshitani H. Transmission of COVID-19 in Nightlife, Household, and Health Care Settings in Tokyo, Japan, in 2020. JAMA Network Open 2023;6(2):e230589 View
  3. Nascimento D, Pimentel B, Souza R, Costa L, Gonçalves S, Louzada F. Dynamic graph in a symbolic data framework: An account of the causal relation using COVID-19 reports and some reflections on the financial world. Chaos, Solitons & Fractals 2021;153:111440 View
  4. Imamura T, Watanabe A, Serizawa Y, Nakashita M, Saito M, Okada M, Ogawa A, Tabei Y, Soumura Y, Nadaoka Y, Nakatsubo N, Chiba T, Sadamasu K, Yoshimura K, Noda Y, Iwashita Y, Ishimaru Y, Seki N, Otani K, Imamura T, Griffith M, DeToy K, Suzuki M, Yoshida M, Tanaka A, Yauchi M, Shimada T, Oshitani H. The Role of Nightlife Settings in Sustained COVID-19 Transmission. SSRN Electronic Journal 2022 View
  5. Hoerger M, Kim S, Mossman B, Alonzi S, Xu K, Coward J, Whalen K, Nauman E, Miller J, De La Cerda T, Peyser T, Dunn A, Zapolin D, Rivera D, Murugesan N, Baker C. Cultivating community-based participatory research (CBPR) to respond to the COVID-19 pandemic: an illustrative example of partnership and topic prioritization in the food services industry. BMC Public Health 2023;23(1) View