Trust predicts compliance with COVID-19 containment policies: Evidence from ten countries using big data.

Econ Hum Biol

School of Social Science & Public Policy, Auckland University of Technology, New Zealand; School of Economics, University of Johannesburg, South Africa. Electronic address:

Published: August 2024

AI Article Synopsis

  • The study explores the link between trust and compliance with COVID-19 restrictions across ten European countries from March 2020 to January 2021, using data from Twitter, Google mobility, and Oxford policy.
  • It challenges previous assumptions by introducing a novel, time-sensitive measure of compliance, assessing how mobility behavior relates to containment policies.
  • Findings reveal that compliance fluctuates over time and that higher trust in others is associated with greater compliance levels, emphasizing the need to foster trust within communities.

Article Abstract

We use Twitter, Google mobility, and Oxford policy data to study the relationship between trust and compliance over the period March 2020 to January 2021 in ten, mostly European, countries. Trust has been shown to be an important correlate of compliance with COVID-19 containment policies. However, the previous findings depend upon two assumptions: first, that compliance is time invariant, and second, that compliance can be measured using self reports or mobility measures alone. We relax these assumptions by calculating a new time-varying measure of compliance as the association between containment policies and people's mobility behavior. Additionally, we develop measures of trust in others and national institutions by applying emotion analysis to Twitter data. Results from various panel estimation techniques demonstrate that compliance changes over time and that increasing (decreasing) trust in others predicts increasing (decreasing) compliance. This evidence indicates that compliance changes over time, and further confirms the importance of cultivating trust in others.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ehb.2024.101412DOI Listing

Publication Analysis

Top Keywords

containment policies
12
compliance
9
trust predicts
8
compliance covid-19
8
covid-19 containment
8
compliance changes
8
changes time
8
increasing decreasing
8
trust
6
predicts compliance
4

Similar Publications

Lessons from COVID-19 in Taiwan's long-term care facilities: A narrative review.

J Formos Med Assoc

January 2025

Department of Internal Medicine, National Taiwan University Hospital, No.7, Chung Shan S. Rd.(Zhongshan S. Rd.), Zhongzheng Dist., Taipei City, 100225, Taiwan, ROC; College of Medicine, National Taiwan University, No.1 Jen Ai road section 1, Taipei 100, Taiwan, ROC. Electronic address:

The coronavirus Disease 2019 (COVID-19) pandemic has disproportionately impacted long-term care facilities (LTCFs), revealing vulnerabilities due to residents' advanced age, comorbidities, and facility infrastructures. In Taiwan, the Central Epidemic Control Center implemented a range of strategies to protect LTCF residents. These included early containment measures to allow time for preparing pharmaceutical intervention, the establishment of infection prevention and control guidelines, the implementation of comprehensive screening and testing protocols, the prioritization of vaccination for both residents and staff, and the expansion of the national stockpile of oral antiviral agents.

View Article and Find Full Text PDF

Introduction: : There is a need to assess the delivery of interventions to improve substance use disorder (SUD) treatment, as measured by the Healthcare Effectiveness Data and Information Set (HEDIS®) metrics. The goal was to characterize published articles reporting HEDIS® SUD measures and recommend future work on applying and investigating SUD HEDIS® metrics and their effect on SUD treatments.

Materials And Methods: The PRISMA-ScR scoping review protocol was used to find published work and investigate the most common reported baseline characteristics, HEDIS® metric outcomes, and knowledge gaps.

View Article and Find Full Text PDF
Article Synopsis
  • The paper reviews various cost containment policies aimed at controlling pharmaceutical spending by either regulating the industry or influencing consumer demand.
  • A narrative literature review highlights that governments have adopted diverse strategies like cost-sharing, value-based pricing, and the promotion of generics, but their effectiveness varies between healthcare systems and can negatively affect patients.
  • The conclusion emphasizes the need for thorough evaluation of these policies to ensure their success, as many lack strong evidence of cost-effectiveness and suggest that further research is essential to create tailored solutions that maintain affordability, fairness, and sustainability in healthcare.
View Article and Find Full Text PDF

Art reveals core human emotions during catastrophes like epidemics, allowing people to narrate their coping stories. This review examines smallpox's historical evolution and treatment in Japan, integrating visual art with medical history. It provides chronological insights from smallpox's arrival and traditional remedies to the era of vaccination and public health measures leading to eventual eradication.

View Article and Find Full Text PDF

Systematic review of evidence for the impact and effectiveness of the 1-3-7 strategy for malaria elimination.

Malar J

December 2024

Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand.

Background: The 1-3-7 approach to eliminate malaria was first implemented in China in 2012. It has since been expanded to multiple countries, but no systematic review has examined the evidence for its use. A systematic review was conducted aiming to evaluate the impact and effectiveness of the strategy and identify key challenges and variations in its implementation across different countries.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!