The initial outbreak of COVID-19 during late December 2019 and the subsequent global pandemic markedly changed consumer mobility patterns worldwide, largely in response to government-ordered non-pharmaceutical interventions (NPIs). In this study, we investigate these changes as they relate to the initial spread of COVID-19 within two states-Massachusetts and Michigan. Specifically, we use linear and generalized linear mixed-effects models to quantify the relationship between four NPIs and individuals' point-of-sale (POS) credit card transactions, as well as the relationship between subsequent changes in POS transactions and county-level COVID-19 case growth rates. Our analysis reveals a significant negative association between NPIs and daily POS transactions, particularly a dose-response relationship, in which stringent workplace closures, stay-at-home requirements, and gathering restrictions were all associated with decreased POS transactions. We also uncover a significant positive association between 12-day lagged changes in POS transactions compared to pre-pandemic baselines and county-level COVID-19 case growth rates. Overall, our study supports previous findings that early NPIs reduced human mobility and COVID-19 transmission in the US, providing policymakers with quantitative evidence concerning the effectiveness of NPIs.
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http://dx.doi.org/10.3390/ijerph21010067 | DOI Listing |
Anal Chim Acta
May 2024
Postgraduate Programme in Metrology, Pontifical Catholic University of Rio de Janeiro, Marquês de São Vicente Street, 225, Gávea, Rio de Janeiro, RJ, Brazil; Logistics, Land Transportation and Storage, Measurement and Product Inventory Management PETROBRAS S.A., Av. Henrique Valadares 28, 20231-030, Rio de Janeiro, Brazil. Electronic address:
Background: Increasingly, measurement uncertainty has been used by pure and applied analytical chemistry to ensure decision-making in commercial transactions and technical-scientific applications. Until recently, it was considered that measurement uncertainty boiled down to analytical uncertainty; however, over the last two decades, uncertainty arising from sampling has also been considered. However, the second version of the EURACHEM guide, published in 2019, assumes that the frequency distribution is approximately normal or can be normalized through logarithmic transformations, without treating data that deviate from the normality.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
April 2024
Innovative Bioresearch Ltd, 20-22 Wenlock Road, N1 7GU, London, United Kingdom.
Background: A blockchain can be described as a distributed ledger database where, under a consensus mechanism, data are permanently stored in records, called blocks, linked together with cryptography. Each block contains a cryptographic hash function of the previous block, a timestamp, and transaction data, which are permanently stored in thousands of nodes and never altered. This provides a potential real-world application for generating a permanent, decentralized record of scientific data, taking advantage of blockchain features such as timestamping and immutability.
View Article and Find Full Text PDFSci Rep
April 2024
School of Digital Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, BE1410, Brunei.
Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we use a lightweight consensus algorithm to cater to these problems.
View Article and Find Full Text PDFInt J Environ Res Public Health
January 2024
Department of Statistics, Harvard University, Cambridge, MA 02139, USA.
The initial outbreak of COVID-19 during late December 2019 and the subsequent global pandemic markedly changed consumer mobility patterns worldwide, largely in response to government-ordered non-pharmaceutical interventions (NPIs). In this study, we investigate these changes as they relate to the initial spread of COVID-19 within two states-Massachusetts and Michigan. Specifically, we use linear and generalized linear mixed-effects models to quantify the relationship between four NPIs and individuals' point-of-sale (POS) credit card transactions, as well as the relationship between subsequent changes in POS transactions and county-level COVID-19 case growth rates.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
July 2023
Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853.
The world is facing a formidable climate predicament due to elevated greenhouse gas (GHG) emissions from fossil fuels. The preceding decade has also witnessed a dramatic surge in blockchain-based applications, constituting yet another substantial energy consumer. Nonfungible tokens (NFTs) are one such application traded on Ethereum (ETH) marketplaces that have raised concerns about their climate impacts.
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