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Background: Residents' adoption of preventive behaviours proved beneficial in preventing the large-scale transmission of the virus during the early stages of the COVID-19 outbreak. It is critical to investigate how social media triggers residents' preventive behaviour decisions during the COVID-19 outbreak. Methods: This paper selected online shopping as a specific preventive behaviour for empirical investigation. An online cross-sectional survey was conducted through the Sojump website from 1 to 15 March 2020, and a total of 1,289 valid questionnaires were collected from China. This paper uses multiple regression analysis to investigate the heterogeneous impacts of different information sources on residents' online shopping willingness and online shopping behaviour and the heterogeneous impacts of different information content in social media on the transformation of residents' online shopping willingness and online shopping behaviour. Results: The findings indicate that both official-media and self-media positively promote residents' online shopping willingness and behaviour, with official-media having a stronger promotional effect than self-media. Furthermore, official-media and self-media can collaboratively promote residents' online shopping willingness and online shopping behaviour. The ease-of-use and usefulness of information significantly promoted the transformation of residents' online shopping willingness. Conclusions: This study analyses the heterogeneous impacts of social media on residents' preventive behaviours from the perspectives of information source differentiation and information content differentiation, which enriches related studies and provides feasible paths for promoting residents' preventive behaviours. [ABSTRACT FROM AUTHOR]

Background: Human communities suffered a vast socioeconomic burden in dealing with the pandemic of coronavirus disease 2019 (COVID-19) globally. Real-word data about these burdens can inform governments about evidence-based resource allocation and prioritization. The aim of this scoping review was to map the cost-of-illness (CoI) studies associated with COVID-19. Methods: This scoping review was conducted from January 2019 to December 2021. We searched cost-of-illness papers published in English within Web of Sciences, PubMed, Google Scholar, Scopus, Science Direct and ProQuest. For each eligible study, extracted data included country, publication year, study period, study design, epidemiological approach, costing method, cost type, cost identification, sensitivity analysis, estimated unit cost and national burden. All of the analyses were applied in Excel software. Results: 2352 records were found after the search strategy application, finally 28 articles met the inclusion criteria and were included in the review. Most of the studies were done in the United States, Turkey, and China. The prevalence-based approach was the most common in the studies, and most of studies also used Hospital Information System data (HIS). There were noticeable differences in the costing methods and the cost identification. The average cost of hospitalization per patient per day ranged from 101$ in Turkey to 2,364$ in the United States. Among the studies, 82.1% estimated particularly direct medical costs, 3.6% only indirect costs, and 14.3% both direct and indirect costs. Conclusion: The economic burden of COVID-19 varies from country to country. The majority of CoI studies estimated direct medical costs associated with COVID-19 and there is a paucity of evidence for direct non-medical, indirect, and intangible costs, which we recommend for future studies. To create homogeneity in CoI studies, we suggest researchers follow a conceptual framework and critical appraisal checklist of cost-of-illness (CoI) studies. [ABSTRACT FROM AUTHOR]