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2.
Front Public Health ; 10: 904971, 2022.
Article in English | MEDLINE | ID: covidwho-2154832

ABSTRACT

Tobacco is both toxic and addictive. Mounting evidence shows that tobacco use has a detrimental impact on almost every aspect of human health, causing or worsening deadly public health crises from the cancer epidemic to the COVID-19 pandemic. However, while tobacco use is a threat to both personal and public health, it continues to surge across the world, especially in China and other low- and middle-income countries. To this end, this article argues in favor of using a ban on the sale of all tobacco products as a practical solution to the global tobacco use epidemic. It is our hope that insights provided by our work will inspire swift policy actions in countries such as China and beyond to curb the tide of rising tobacco consumption, so that populations around the world could be better shielded from the pervasive and long-lasting damage that tobacco products cause or compound.


Subject(s)
COVID-19 , Tobacco Products , Humans , Pandemics , Smoking/epidemiology , COVID-19/epidemiology , Commerce
3.
BMJ ; 379: o2815, 2022 11 22.
Article in English | MEDLINE | ID: covidwho-2152958
4.
Addiction ; 117(12): 3069-3078, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2152576

ABSTRACT

AIMS: Government alcohol sales data were used to examine whether age 15+ per-capita alcohol consumption (PCAC) (i) changed during COVID-19 and (ii) predicted COVID-19 infections 2-5 weeks later. DESIGN: Interrupted time-series analyses were applied to panels of data before and after COVID-19 restrictions were introduced in Canada. SETTING AND PARTICIPANTS: The populations, aged 15+, of the provinces of Ontario (ON), British Columbia (BC) and Nova Scotia (NS), Canada. INTERVENTION: Expansion of home delivery options and hours of trading for liquor stores while restrictions on travel, social and economic activities were imposed by governments during COVID-19 from 17 March 2020 until 29 March 2021. MEASUREMENTS: Weekly estimates of (i) age 15+ PCAC using sales data supplied by provincial government alcohol distributors for liquor stores, bars and restaurants, (ii) stringency of public health measures assessed by the Public Health Agency of Canada (PHAC) and (iii) new COVID-19 infections reported by PHAC. FINDINGS: PCAC increased by 7.10% (P = 0.013) during the pandemic versus previous years, with increased private liquor store sales partly offset by reduced bar/restaurant sales. Consumption was positively associated with stringency of public health measures. Weekly PCAC was positively associated with new COVID-19 infections 2 weeks later (+6.34% for a one drink/week increase, P < 0.001). Lagged associations with COVID-19 infections 2 or 3 weeks later were observed for PCAC from all sales channels, with larger effect sizes per standard drink/person/week increase for on-premise outlets (+77.27% week 2, P = 0.009) than government liquor stores (+6.49%, week 2, P < 0.001) or private liquor stores (+7.13%, week 4, P < 0.001). CONCLUSIONS: Alcohol consumption increased in three Canadian provinces during COVID-19 to degrees corresponding to the extent of the strictness of measures imposed to prevent viral spread. Increased consumption of alcohol was associated with increased COVID-19 infection rates 2 weeks later.


Subject(s)
COVID-19 , Humans , Alcoholic Beverages , Commerce , Alcohol Drinking , British Columbia
5.
PLoS One ; 17(11): e0277924, 2022.
Article in English | MEDLINE | ID: covidwho-2140674

ABSTRACT

Interactions between stock and cryptocurrency markets have experienced shifts and changes in their dynamics. In this paper, we study the connection between S&P500 and Bitcoin in higher-order moments, specifically up to the fourth conditional moment, utilizing the time-scale perspective of the wavelet coherence analysis. Using data from 19 August 2011 to 14 January 2022, the results show that the co-movement between Bitcoin and S&P500 is moment-dependent and varies across time and frequency. There is very weak or even non-existent connection between the two markets before 2018. Starting 2018, but mostly 2019 onwards, the interconnections emerge. The co-movements between the volatility of Bitcoin and S&P500 intensified around the COVID-19 outbreak, especially at mid-term scales. For skewness and kurtosis, the co-movement is stronger and more significant at mid- and long-term scales. A partial-wavelet coherence analysis underlines the intermediating role of economic policy uncertainty (EPU) in provoking the Bitcoin-S&P500 nexus. These results reflect the co-movement between US stock and Bitcoin markets beyond the second moment of return distribution and across time scales, suggesting the relevance and importance of considering fat tails and return asymmetry when jointly considering US equity-Bitcoin trading or investments and the policy formulation for the sake of US market stability.


Subject(s)
COVID-19 , Models, Economic , Humans , Commerce , COVID-19/epidemiology , Investments , Records
6.
PLoS One ; 17(11): e0276853, 2022.
Article in English | MEDLINE | ID: covidwho-2140614

ABSTRACT

The risks perceived by consumers in online shopping can negatively affect the acceptance of electronic commerce, however, the perceived risks are a cultural aspect that can affect consumers differently in different countries. This research examines what dimensions of perceived risk affect the acceptance of electronic commerce in Bolivia, a developing country. The design is quantitative, the TAM model is used with the variables: risk of misuse of information, risk of not obtaining the benefits of the product and risk of inefficiency of the functionality. The results show that the three risks examined do not affect the acceptance of electronic commerce, and that the variables perceived usefulness and ease of use have a positive effect on the acceptance of electronic commerce. The theoretical implications of this study provide empirical evidence from Bolivia, which shows strong variables of perceived usefulness and ease of use, which mitigates the effect of risk´s perception by the consumer, the results are explained in the context of the COVID-19 pandemic that accelerated the rapid acceptance of electronic commerce, increasing the perception of usefulness and ease of use of online shopping. As practical implications, this research provides managers and administrators of online businesses with knowledge about the effect of risk variables perceived by consumers.


Subject(s)
COVID-19 , Pandemics , Humans , Bolivia , COVID-19/epidemiology , Electronics , Commerce
8.
Vaccine ; 40(50): 7288-7304, 2022 Nov 28.
Article in English | MEDLINE | ID: covidwho-2132597

ABSTRACT

The sustainable manufacturing of vaccines in developing countries is critical to increasing equitable access to vaccines and pandemic preparedness globally. Sustainable manufacturing requires that organizations engaged in the development, production and supply of vaccines have viable business models and incentives to manufacture vaccine products. The expanding manufacturing capabilities and capacities of developing countries vaccine manufacturers (DCVMs) are increasingly positioning these organizations to meet the national and regional public health needs in developing countries; however, key industry challenges such as regulatory barriers, low prices and demand uncertainty for vaccine products, and limited R&D funding threaten the long-term viability of vaccine manufacturers. This study assesses the technical capabilities, manufacturing capacities, and aspirational plans of DCVMs, exemplifying the business models and strategies undertaken to sustainably manufacture vaccines in developing countries. The public health importance of a healthy vaccine industry which enables manufacturers is discussed throughout. Vaccine manufacturers reported diverse product portfolios and R&D pipelines and utilized an array of vaccine technology platforms. Large manufacturing capacities were reported, a critical factor in manufacturers achieving economies of scale and supplying large volumes of vaccine doses to the world's most populous regions. Partnerships and collaboration within the industry and with international organizations along the vaccine value-chain were cited with high frequency. Manufacturers also reported aspirational plans to enter new markets, acquire new technologies and invest in the development of novel and improved vaccines. As DCVMs aim to have an increasing impact on the global vaccine ecosystem, a coordinated multi-stakeholder approach is required alleviate critical industry barriers to ensure that all efforts produce vaccines are sustainable and enable developing countries to realize the public health benefit of vaccines.


Subject(s)
Developing Countries , Vaccines , Ecosystem , Income , Commerce
9.
N C Med J ; 83(6): 445-447, 2022.
Article in English | MEDLINE | ID: covidwho-2111225

ABSTRACT

North Carolina faces a significant health workforce shortage exacerbated by the COVID-19 pandemic. To meet this challenge, the Department of Commerce and the Department of Health and Human Services are prioritizing equity, creativity, and collaboration.


Subject(s)
COVID-19 , Pandemics , Humans , North Carolina , COVID-19/epidemiology , Workforce , Commerce
10.
Health Promot Pract ; 23(1_suppl): 86S-95S, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2117048

ABSTRACT

On April 8, 2020, the Navajo Nation issued an administrative order limiting business operations. Facing high coronavirus disease 2019 (COVID-19) rates and limited food infrastructure, a survey was conducted among Navajo Nation store managers to assess: (1) COVID-19 adaptations; (2) challenges; (3) changes in customer volume and purchasing; and (4) suggestions for additional support. Purposive sampling identified 29 stores in Navajo communities. Representatives from 20 stores (19 store managers/owners, 1 other; 7 grocery, and 13 convenience/other stores) were interviewed by phone or in-person to reach saturation (new information threshold < 5%). Responses were coded using frequencies and inductive thematic analysis. All 20 stores implemented COVID-19 guidelines (Centers for Disease Control and Prevention [CDC]/Navajo Nation) and most received orientation/support from local chapters, community organizations, or health centers. Stores implemented staff policies (50%, handwashing, vaccinations, protective personal equipment (PPE), sick leave, temperature checks), environmental changes (50%, hand sanitizer, checkout dividers), customer protocols (40%, limit customers, mask requirements, closed restrooms), and deep cleaning (40%). Most stores (65%) reported challenges including stress/anxiety, changing guidelines, supply chain and customer compliance; 30% reported infection or loss of staff. Weekday customer volume was slightly higher vs. pre-COVID, but weekend lower. Stores reported consistent or more healthy food purchases (50%), more nonfood essentials (20%), or shelf-stable foods (10%). Desired support included further orientation (30%), leadership support (20%), overtime/time to learn guidelines (20%), and signage/handouts (15%). Despite a high COVID-19 burden and limited food store infrastructure, Navajo Nation stores adapted by implementing staff, environmental and customer policies. Local support, staffing, and small store offerings were key factors in healthy food access.


Subject(s)
COVID-19 , Pandemics , Humans , Pandemics/prevention & control , COVID-19/prevention & control , Food Supply , Consumer Behavior , Food , Commerce
11.
PLoS One ; 17(11): e0275288, 2022.
Article in English | MEDLINE | ID: covidwho-2116493

ABSTRACT

Early analyses revealed that dark web marketplaces (DWMs) started offering COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the COVID-19 pandemic started, when these goods were in shortage in the traditional economy. Here, we broaden the scope and depth of previous investigations by considering how DWMs responded to an ongoing pandemic after the initial shock. Our dataset contains listings from 194 DWMs collected until July 2021. We start by focusing on vaccines. We find 248 listings offering approved vaccines, like Pfizer/BioNTech and AstraZeneca, as well as vendors offering fabricated proofs of vaccination and COVID-19 passports. Then, we consider COVID-19 related products. We show that, as the regular economy has become able to satisfy the demand of these goods, DWMs have decreased their offer. Next, we analyse the profile of vendors of COVID-19 related products and vaccines. We find that most of them are specialized in a single type of listings and are willing to ship worldwide. Finally, we consider a broader set of listings mentioning COVID-19, in order to assess the general impact of the pandemic on the broader activity of DWMs. Among 10,330 such listings, we show that recreational drugs are the most affected among traditional DWMs product, with COVID-19 mentions steadily increasing since March 2020. We anticipate that our results will be of interest to researchers, practitioners, and law enforcement agencies focused on the study and safeguard of public health.


Subject(s)
COVID-19 , Vaccines , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Pandemics/prevention & control , Vaccination , Commerce
12.
Comput Intell Neurosci ; 2022: 7097044, 2022.
Article in English | MEDLINE | ID: covidwho-2108387

ABSTRACT

The unprecedented Corona Virus Disease (COVID-19) pandemic has put the world in peril and shifted global landscape in unanticipated ways. The SARSCoV2 virus, which caused the COVID-19 outbreak, first appeared in Wuhan, Hubei Province, China, in December 2019 and quickly spread around the world. This pandemic is not only a global health crisis, but it has caused the major global economic depression. As soon as the virus spread, stock market prices plummeted and volatility increased. Predicting the market during this outbreak has been of substantial importance and is the primary motivation to carry out this work. Given the nonlinearity and dynamic nature of stock data, the prediction of stock market is a challenging task. The machine learning models have proven to be a good choice for the development of effective and efficient prediction systems. In recent years, the application of hyperparameter optimization techniques for the development of highly accurate models has increased significantly. In this study, a customized neural network model is proposed and the power of hyperparameter optimization in modelling stock index prices is explored. A novel dataset is generated using nine standard technical indicators and COVID-19 data. In addition, the primary focus is on the importance of selection of optimal features and their preprocessing. The utilization of multiple feature ranking techniques combined with extensive hyperparameter optimization procedures is comprehensive for the prediction of stock index prices. Moreover, the model is evaluated by comparing it with other models, and results indicate that the proposed model outperforms other models. Given the detailed design methodology, preprocessing, exploratory feature analysis, and hyperparameter optimization procedures, this work gives a significant contribution to stock analysis research community during this pandemic.


Subject(s)
COVID-19 , Models, Economic , COVID-19/epidemiology , Commerce , Delivery of Health Care , Humans , Neural Networks, Computer , RNA, Viral , SARS-CoV-2
14.
Environ Sci Pollut Res Int ; 29(52): 79413-79433, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2085528

ABSTRACT

Numerous studies have been conducted to identify the effects of natural crises on supply chain performance. Conventional analysis methods are based on either manual filter methods or data-driven methods. The manual filter methods suffer from validation problems due to sampling limitations, and data-driven methods suffer from the nature of crisis data which are vague and complex. This study aims to present an intelligent analysis model to automatically identify the effects of natural crises such as the COVID-19 pandemic on the supply chain through metadata generated on social media. This paper presents a thematic analysis framework to extract knowledge under user steering. This framework uses a text-mining approach, including co-occurrence term analysis and knowledge map construction. As a case study to approve our proposed model, we retrieved, cleaned, and analyzed 1024 online textual reports on supply chain crises published during the COVID-19 pandemic in 2019-2021. We conducted a thematic analysis of the collected data and achieved a knowledge map on the impact of the COVID-19 crisis on the supply chain. The resultant knowledge map consists of five main areas (and related sub-areas), including (1) food retail, (2) food services, (3) manufacturing, (4) consumers, and (5) logistics. We checked and validated the analytical results with some field experts. This experiment achieved 53 crisis knowledge propositions classified from 25,272 sentences with 631,799 terms and 31,864 unique terms using just three user-system interaction steps, which shows the model's high performance. The results lead us to conclude that the proposed model could be used effectively and efficiently as a decision support system, especially for crises in the supply chain analysis.


Subject(s)
COVID-19 , Text Messaging , Humans , Pandemics , Data Mining , Commerce
15.
Work ; 73(s1): S177-S187, 2022.
Article in English | MEDLINE | ID: covidwho-2054930

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, the online sales industry experienced record-breaking growth. The number of businesses that decided to enter the e-commerce market for the first time was enormous. At the height of the quarantine, Brazil was registering a new virtual store every minute. This was an unanticipated and unplanned expansion. OBJECTIVE: This study aims to identify existing challenges in human interactions with e-commerce, such as the difficulties faced during the pandemic and improvements to ensure growth of, and confidence in, this type of business. METHODS: An exploratory study of e-commerce data and an online survey using the snowball non-probabilistic method were developed to research the growth of, and issues in, Brazilian users' interaction with e-commerce, comparing findings before and after the pandemic restrictions. RESULTS: Some businesses were not prepared, and the lack of experience among workers contributed to businesses not delivering on their promises. The acceleration of e-commerce demonstrates the need to guarantee that Brazil can effectively use e-commerce to capitalize on digital supply chain opportunities and enhance their role in its economic expansion, while remaining human-centered. CONCLUSIONS: For users' needs to be met, companies and online workers must understand people's needs and behaviors in order to provide excellent service.


Subject(s)
COVID-19 , Pandemics , Humans , COVID-19/epidemiology , Commerce , Quarantine , Industry
16.
J Environ Public Health ; 2022: 7279233, 2022.
Article in English | MEDLINE | ID: covidwho-2053428

ABSTRACT

The sudden global pandemic of COVID-19 occurred in Malaysia at the beginning of new 2020, which increased the uncertainty of the economy. As a highly demanded industry during diseases, COVID-19-related news had a mixed influence on investors' confidence in the healthcare industry, so the short-term market reaction of the Malaysian healthcare industry is investigated during this unfolding event. This paper examines whether the "lockdown" suppressed the influence of COVID-19 pandemic on stock performance in 12 listed healthcare companies in Malaysia. We consider the "lockdown" order has different impacts on samples. The hardest hit among the four events is the first announcement of lockdown, whose cumulative average abnormal return (CAAR) is negative (CAAR<0), for its strict movement control. However, the impacts of the following three lockdown events are positive and less severe as the market gradually digest these kinds of news and the deregulation of movement control. Previous studies have justified the influence of disease outbreaks on the stock market; however, this study compensates for other studies by employing the event study methodology (ESM) approach to provide the first empirical evidence of the unprecedented influence of "lockdown" on Malaysian healthcare stock market. This study has practical implications for Malaysian financial markets that the lockdown orders matter for the Malaysian healthcare industry. The empirical results show that the stock market has positively affected the lockdown announcement after the first event. In turn, the policymakers could draw on these results related to stock performance to modify the regulations in the healthcare industry.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Commerce , Communicable Disease Control , Delivery of Health Care , Humans , Malaysia/epidemiology , Pandemics/prevention & control
17.
Soc Sci Med ; 312: 115386, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2042143

ABSTRACT

Access to medicines has become a major concern for countries worldwide during the COVID-19 pandemic, as pharmaceutical production and trade have been disrupted in the course of the crisis. Antibiotics are one group of medicines where worries about access have been raised. Access to the right antibiotic at the right time is important not only for curing infections of individual patients, but also for curbing antibiotic resistance globally. Reliable pharmaceutical supply is key to ensuring access to medicines. The global supply of generic medicines has over the last decades been transformed by the rise of India's pharmaceutical industry. In this paper, I trace the changing role of this industry for the global export of antibiotics, by mapping and describing changes in Indian antibiotic exports and discussing these in light of historical processes and events. The paper offers a novel approach to analyse global antibiotic trajectories by using international trade data from publicly available resources combined with a secondary literature review. I show that India's pharmaceutical industry today holds a key role as one of the world's biggest exporters of antibiotic medicines, but with an increasing dependency on China as a supplier of antibiotic ingredients. This produces both opportunities and concerns for access to antibiotics globally.


Subject(s)
COVID-19 , Pandemics , Anti-Bacterial Agents/therapeutic use , COVID-19/drug therapy , Commerce , Drug Industry , Drugs, Generic/therapeutic use , Humans , India , Internationality
18.
Nutrients ; 14(18)2022 Sep 14.
Article in English | MEDLINE | ID: covidwho-2033076

ABSTRACT

Online grocery shopping has expanded rapidly in the U.S., yet little is known about the retailer's perceptions of online grocery services, which can aid in the expansion of services. Furthermore, many barriers to online grocery utilization persist across geographic areas, especially among Supplemental Nutrition Assistance Program (SNAP)-authorized retailers. This study captured perceived barriers and facilitators of online grocery shopping for managers of SNAP-authorized retailers. Qualitative semi-structured interviews were conducted with managers (n = 23) of grocery stores/supermarkets in urban and rural areas across four different states: TN, KY, NC, and NY. Grocery store managers offering online ordering (n = 15) and managers from brick-and-mortar stores without online services (n = 8) participated in the interviews. Three primary themes emerged among managers offering online ordering: (1) order fulfillment challenges, (2) perceived customer barriers, and (3) perceived customer benefits. Among managers at brick-and-mortar locations without online services, four major themes emerged: (1) thoughts on implementing online shopping, (2) COVID-19 pandemic impacts, (3) competition with other stores, and (4) benefits of maintaining brick-and-mortar shopping. This study provides a deeper understanding of retailers' experience and perceptions of online grocery services among stores authorized to accept SNAP benefits. This perspective is necessary to inform policies and enhance the evolving virtual food marketplace for SNAP customers.


Subject(s)
COVID-19 , Food Assistance , Commerce , Food Supply , Humans , Pandemics , Supermarkets
19.
Int J Environ Res Public Health ; 19(17)2022 Sep 05.
Article in English | MEDLINE | ID: covidwho-2023725

ABSTRACT

The importance of sustainability in supply chain management is growing worldwide. It is possible to find reasons for this using various phenomena that negatively affect humanity, e.g., climate change, scarce materials, supply disruptions, and complex fossil fuel dependency. Because of that, is extremely important to constantly look for new ways to systematically increase sustainability in enterprises and their logistics and supply chain processes by considering different stakeholders and influential factors. Therefore, this paper explores how different types of organizational culture and normative commitment impact sustainability and each other in business logistics and supply chains and develops a conceptual model to manage this challenge. Gaining new insights is valuable especially for managers to obtain better information on how to improve sustainability not just by integrating green technologies but mainly by changing culture, attitude, and perception in their enterprises. The research is focused on employees from global logistics or related branches in micro, small, medium, and large enterprises with the primary activity mostly related to manufacturing, transport, and storage. The findings are based on the questionnaire which was sent directly to 1576 employees from 528 enterprises. A total of 516 employees from enterprises that are mostly located in 34 countries responded to requests for participation. The results reveal statistically significant positive and negative impacts, e.g., clan culture has a positive statistically significant impact on the sustainable development of supply chains. Most of the connections to the eighth Sustainable Development Goal by the United Nations (decent work and economic growth) were also found, which was the enterprise's highest priority with a share of 52.99%. A contribution to the theory development is gained using the developed model that considers both positive and negative statistically significant impacts studied.


Subject(s)
Organizational Culture , Sustainable Development , Commerce , Economic Development , Humans , Models, Theoretical
20.
Biomed Res Int ; 2022: 7728596, 2022.
Article in English | MEDLINE | ID: covidwho-2020532

ABSTRACT

The sudden arrival of the new crown epidemic has had a significant and long-lasting impact on the division's economic environment as well as the production and operation activities of businesses. As far as the financial management is concerned, opportunities and difficulties are faced by enterprises of all types. With reference to the available research data, enterprises have an important contribution to GDP and jobs, but they still face a series of difficulties and challenges in their development in the context of the normalization of the epidemic. By analyzing the impact of the new crown pneumonia epidemic on the financial management work of enterprises, this paper proposes an artificial neural network-based enterprise financial forecasting and early warning method to provide an effective method for enterprise financial management. For the time-series characteristics of enterprise finances, a prediction model based on long- and short-term memory networks is developed which acknowledges the necessity of combining the temporal dimension with the spatial dimension for forecasting. This model incorporates time qualities into the data to the existing forecasting model. It also considers both working and nonworking day data and thoroughly considers the factors influencing corporate finance. Then, using BP neural network for financial risk prediction, nonfinancial index factors should be added to the financial early warning model thus eliminating the limitations of the financial early warning model. At the same time, the accuracy of the prediction can be improved which is more suitable for enterprises to apply in practice. The experimental results demonstrate that the financial prediction model built by multilayer feed forward neural networks and recurrent neural networks based on error back propagation training is inferior to the prediction model built by long- and short-term memory network. Regardless of the degree of fitting or prediction accuracy, the BP neural network model outperforms the conventional model for enterprise financial warning. Under the normalization of the pandemic, the combined use of both can offer an efficient technique for enterprise management.


Subject(s)
Epidemics , Financial Management , Commerce , Forecasting , Neural Networks, Computer
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