ArticleInternational journal of health policy and management2022
The Effect of Governmental Health Measures on Public Behaviour During the COVID-19 Pandemic Outbreak.
Article in International journal of health policy and management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Estimating time-dependent contact: a multi-strain epidemiological model of SARS-CoV-2 on the island of Ireland.Global epidemiology · 2023Article
- Breast Cancer Screening Should Embrace Precision Medicine: Evidence by Reviewing Economic Evaluations in China.Advances in therapy · 2023Review
- Article
- Configurations for positive public behaviors in response to the COVID-19 pandemic: a fuzzy set qualitative comparative analysis.BMC public health · 2022Article
Corrections and comments
- Comment on
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe coronavirus disease 2019 (COVID-19) pandemic resulted in radical changes in many aspects of life. To deal with this, each country has implemented continuous health measures from the beginning of the outbreak. Discovering how governmental actions impacted public behaviour during the outbreak stage is the purpose of this study.
methodsThis study uses a hybrid large-scale data visualisation method to analyse public behaviour (epidemic concerns, self-protection, and mobility trends), using the data provided by multiple authorities. Meanwhile, a content analysis method is used to qualitatively code the health measures of three countries with severe early epidemic outbreaks from different continents, namely China, Italy, and the United States. Eight dimensions are coded to rate the mobility restrictions implemented in the above countries.
results(1) Governmental measures did not immediately persuade the public to change their behaviours during the COVID-19 epidemic. Instead, the public behaviour proceeded in a three-phase rule, which is typically witnessed in an epidemic outbreak, namely the wait-and-see phase, the surge phase and the slow-release phase. (2) The strictness of the mobility restrictions of the three countries can be ranked as follows: Hubei Province in China (with an average score of 8.5 out of 10), Lombardy in Italy (7.125), and New York State in the United States (5.375). Strict mobility restrictions are more likely to cause a surge of population outflow from the epidemic area in the short term, whereas the effect of mobility restrictions is positively related to the stringency of policies in the long term.
conclusionThe public showed generally lawful behaviour during regional epidemic outbreaks and blockades. Meanwhile public behaviour was deeply affected by the actions of local governments, rather than the global pandemic situation. The contextual differences between the various countries are important factors that influence the effects of the different governments' health measures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.