ABSTRACT
Wearing masks reduces the spread of COVID-19, but compliance with mask mandates varies across individuals, time, and space. Accurate and continuous measures of mask wearing, as well as other health-related behaviors, are important for public health policies. This article presents a novel approach to estimate mask wearing using geotagged Twitter image data from March through September, 2020 in the United States. We validate our measure using public opinion survey data and extend the analysis to investigate county-level differences in mask wearing. We find a strong association between mask mandates and mask wearing-an average increase of 20%. Moreover, this association is greatest in Republican-leaning counties. The findings have important implications for understanding how governmental policies shape and monitor citizen responses to public health crises.
Subject(s)
COVID-19 , Humans , United States/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , Government , Public Health , Public Opinion , Public PolicyABSTRACT
Coronavirus disease 19 (COVID-19) is still a major public health concern in many nations today. COVID-19 transmission is now controlled mostly through early discovery, isolation, and therapy. Because of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the contributing factor to COVID-19, establishing timely, sensitive, accurate, simple, and budget detection technologies for the SARS-CoV-2 is urgent for epidemic prevention. Recently, several electrochemical DNA biosensors have been developed for the rapid monitoring and detection of SARS-CoV-2. This mini-review examines the latest improvements in the detection of SARS-COV-2 utilizing electrochemical DNA biosensors. Meanwhile, this mini-review summarizes the problems faced by the existing assays and puts an outlook on future trends in the development of new assays for SARS-CoV-2, to provide researchers with a borrowing role in the generation of different assays.
ABSTRACT
BACKGROUND: Diabetes is an independent risk factor for COVID-19 patients, and SARS-CoV-2 infection may in turn induce hyperglycemia. In this work, we will map the trends of global research of COVID-19 and diabetes by using the method of bibliometric analysis, help researchers quickly understand the research hotspots and find meaningful research directions. METHODS: Documents related to COVID-19 and diabetes were obtained from the database of Science Citation Index Expanded of Web of Science. We then analysed the data by country/organization coauthorship analysis, sources/documents citation analysis, and keywords co-occurrence analysis. VOSviewer was applied to map the global research trends and hotspots in this field. RESULTS: A total of 1,206 articles were retrieved, including a total of 101 countries, 2,595 organizations, 526 journals, and 3,405 keywords. China had the highest total citations, followed by the United States, while these two countries were reversed in terms of the number of documents. Half of the top 10 highly cited organizations were from China, including Capital Medical University, which had the highest citations, and Huazhong University of Science and Technology, which had the largest number of documents. Diabetes Research and Clinical Practice was the most productive journal. Journal of Medical Virology was the most highly cited journal. Zhou et al.'s article (The Lancet, 2020) was the most representative and widely cited. The keywords mainly focused on 3 categories, namely risk factors & clinical outcomes, receptor ACE2 & cytokine storm, as well as clinical characteristics & epidemiology. Among them, hyperglycemia, obesity, outcomes, and cytokine storm are the hotspots of recent concern. CONCLUSIONS: This research mapped the global research trends in COVID-19 and diabetes, which may help researchers identify relevant collaborators and discover current hotspots and potential research directions.