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This study estimated population normalized mass loads (PNML) of quaternary ammonium compounds (QACs) including alkyltrimethylammonium chloride (ATMAC), benzylalkyldimethylammonium chloride (BAC), and dialkyldimethylammonium chloride (DADMAC) and assessed their associations with COVID-19 containment policies. We collected daily sludge specimens from five wastewater treatment plants in Beijing from July 2020 to May 2022. Using liquid chromatography-tandem mass spectrometry, we determined QAC concentrations and backward-estimated their PNML. We used COVID-19 Oxford Stringency Index and its metrics to measure containment policies. We analysed the relationship between QACs and containment measures using linear regression models. Among QACs categories, ΣBAC had median PNML of 94.54 μg/person/day, ΣDADMAC had 282.36 μg/person/day, and ΣATMAC had 802.55 μg/person/day. The ΣQACs median PNML was 1186.12 μg/person/day. The PNML of QACs appeared to have general increasing trend over time and were significantly different across seasons. PNML increased on average by 11 μg/person/day (95 % CI: 3.2, 19) for ΣBAC per 10-unit increase in Stringency Index score. Notably, higher stringency levels in three index indicators — workplace closures, internal movement restrictions, and public gathering restriction were positively associated with higher ΣQACs PNML. Sludge derived QACs may reflect the magnitude of disinfectant use at different stages of pandemic control response.

Abstract This research investigates the factors influencing GDP over the short-term using dynamic panel data across income groups in 71 countries, with a focus on the role of proxy COVID-19 vaccination. The analysis utilizes quarterly data spanning seven quarters from 2021Q1 to 2022Q3, employing the System Generalized Method of Moments (Sys-GMM) model developed by Blundell-Bond to assess the short-term impact of vaccination, investment, government consumption ratio, stringency index, trade openness and inflation on GDP. The findings reveal that vaccination and economic investments have a significant positive short-term effect on GDP, while the government consumption ratio and stringency index exert a strong negative influence. Conversely, trade openness and inflation do not significantly affect GDP. The study provides valuable insights for policymakers, economists, and analysts, highlighting that during the pandemic, factors such as public health measures and investments have a more critical role in economic performance of countries.

This research investigates the factors influencing GDP over the short-term using dynamic panel data across income groups in 71 countries, with a focus on the role of proxy COVID-19 vaccination. The analysis utilizes quarterly data spanning seven quarters from 2021Q1 to 2022Q3, employing the System Generalized Method of Moments (Sys-GMM) model developed by Blundell-Bond to assess the short-term impact of vaccination, investment, government consumption ratio, stringency index, trade openness and inflation on GDP. The findings reveal that vaccination and economic investments have a significant positive short-term effect on GDP, while the government consumption ratio and stringency index exert a strong negative influence. Conversely, trade openness and inflation do not significantly affect GDP. The study provides valuable insights for policymakers, economists, and analysts, highlighting that during the pandemic, factors such as public health measures and investments have a more critical role in economic performance of countries. [ABSTRACT FROM AUTHOR]

Purpose: This study has aimed to analyse the role of innovation-sharing collaboration in the large-scale manufacturing of Covid-19 vaccination across the globe and its impact on the mortality rate of the countries where the pharmaceutical manufacturers received such innovation. Design/methodology/approach: The authors have relied upon the difference-in-difference (DID) approach by utilizing the data available on public platforms such as World Health Organization (WHO) databank, organization for economic co-operation and development (OECD) data bank, istat, Indian bureau of statistics and European centre for disease prevention and control (ecdc) from 2020 to 2021 to establish the empirical inference of the analysis. Findings: This study's results present that after the invention and commercialization of the vaccine, the Covid-19 impact was still intact and people were dying continuously. However, it was impossible to fulfil the demand of the 7 billion population in a short time. In the light of these facts, the WHO encouraged sharing vaccine innovation with other countries to enhance production capacity. The authors found that after vaccine innovation sharing, Covid-19's devastation slowed: the fatality rate was marginally reduced, and economic conditions started their recovery journey. Originality/value: This study's findings present that the Covid-19 vaccine played a pivotal role in tackling the Covid-19's devastating impact on the entire world. It emphasizes the role of innovation-sharing collaborations in curtailing hazardous consequences, including the mortality rate during a crisis, and such collaborations' impact on the countries where institutions involved in them reside. [ABSTRACT FROM AUTHOR]

Abstract Objective: To investigate the relationship between US containment measures during the COVID-19 pandemic and household food insecurity. Design: To investigate these relationships, we developed a framework linking COVID-19-related containment policies with different domains of food security and then used multilevel random effects models to examine associations between state-level containment policies and household food security. Our framework depicts theorised linkages between stringency policies and five domains of food security (availability, physical access, economic access, acceptability in meeting preferences and agency, which includes both self-efficacy and infrastructure). We used US national data from a representative survey data from the National Food Access and COVID research Team that was fielded in July–August 2020 and April 2021. Containment policy measures came from the Oxford Stringency Index and included policies such as stay-at-home orders, closing of public transit and workplace closures. Setting: The USA. Participants: 3071 adult individuals from the National Food Access and COVID research Team survey. Results: We found no significant associations between state-level containment policies and overall food insecurity at the state level or any of the individual domains of food insecurity. Conclusions: This research suggests that while food insecurity across all domains was a significant problem during the studied phases of the pandemic, it was not associated with these containment measures. Therefore, impacts may have been successfully mitigated, likely through a suite of policies aimed at maintaining food security, including the declaration of food workers as essential and the expansion of federal nutrition programmes.

Following the spread of the Covid-19 virus at the end of 2019, governments have used a series of strict policies and non-pharmaceutical interventions (NPI) such as social distancing and mandatory quarantines to deal with the increasing spread of this virus, and therefore the trading process of global markets, Including the stock market, it was severely affected. In the following, the start of public vaccination affected various industries and groups and led to changes in stock market transactions of countries, including the Tehran Stock Exchange. The present study, by applying the Smooth transmission regression (STR) nonlinear model and daily data during the period of the Covid-19 epidemic (30 February 2018 to 10 January 2018), investigates the role of public vaccination in the relationship between the interventionist policies of the government and the stock market. In the present study, relying on tests to detect nonlinear behavior, the existence of a nonlinear relationship between government interventions and the stock market index was confirmed, the variable of the number of vaccinated people was selected as a suitable transition variable, and the nonlinear smooth transition regression model with a two-regime logistic transfer function With one transfer (LSTR1) was considered as the proposed model for this relationship. The results of the estimation of the research model show that the increase of strict measures of the government in the form of a two-regime structure with a threshold level of 20857, the number of vaccinated people in the first regime (that is, when the number of vaccinated people is less than the threshold value (20857)) had a positive and significant effect on the stock market index, but after crossing the threshold level and entering the second regime (that is, when the number of vaccinated people is greater than its threshold value (20857)), the mentioned variable had a negative and significant impact on the stock market index. [ABSTRACT FROM AUTHOR]

In recent decades, the issue of violence against women has increasingly drawn the attention of international and national legislators and policymakers. The term "femicide" became widespread in the early 2000s and was incorporated into the criminal codes of several countries. The onset of the COVID-19 pandemic and the subsequent social distancing measures raised significant concerns about their impact on women's safety. This study examines the effect of COVID-19 confinement measures on femicide trends in Italy, a country which adopted stringent COVID-19 confinement measures and, since 2019, implemented new legislation to counteract violence against women. Using two data sets—one from the Italian Ministry of Interior containing 1,382 cases of female homicides (2013–2022) and another from Italian NGOs detailing 1,253 femicides according to media coverage (2012–2022)—the study employs autoregressive integrated moving average (ARIMA) analysis to assess monthly trends alongside the stringency index for COVID-19 containment efforts. The findings reveal that, although overall femicide rates remained stable during lockdowns, there was a significant shift in victim–perpetrator relationships. Specifically, from March to May 2020, there was a decline in femicides by former partners, offset by an increase in those by cohabiting partners. These results underscore the complexity of femicide and the need for further research on various facets of violence against women. This includes the potential escalation of physical and psychological violence during lockdowns, influenced by forced proximity and substance abuse in domestic environments. [ABSTRACT FROM AUTHOR]

Government measures to limit the spread of COVID-19 affected crime opportunities and criminal justice systems, resulting in changes in crime trends. This article explores the effects of restrictions (lockdowns) on the number of femicides. The monthly data on femicides from 2017 to 2021 were collected in five Central and South-eastern European countries: Croatia, Hungary, Montenegro, North Macedonia, and Slovenia. The total number of femicides from 2017 to 2021 decreased in all observed countries. Increases were detected in Croatia and Slovenia in 2020. However, they presented an exception to the general trend. The monthly distribution of femicides showed that there was no common point peak month(s) among observed countries. Analyzing the effects of the level of restrictions using the Stringency Index on the number of femicides confirmed the initial observation that the number of femicides was not dependent on lockdown measures. In general, the findings show that restriction measures had no effect on the number of femicides in the studied countries. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: The aim of this study was to determine whether BMI in early childhood was affected by the COVID-19 pandemic and containment measures, and whether it was associated with the risk for islet autoimmunity. Methods: Between February 2018 and May 2023, data on BMI and islet autoimmunity were collected from 1050 children enrolled in the Primary Oral Insulin Trial, aged from 4.0 months to 5.5 years of age. The start of the COVID-19 pandemic was defined as 18 March 2020, and a stringency index was used to assess the stringency of containment measures. Islet autoimmunity was defined as either the development of persistent confirmed multiple islet autoantibodies, or the development of one or more islet autoantibodies and type 1 diabetes. Multivariate linear mixed-effect, linear and logistic regression methods were applied to assess the effect of the COVID-19 pandemic and the stringency index on early-childhood BMI measurements (BMI as a time-varying variable, BMI at 9 months of age and overweight risk at 9 months of age), and Cox proportional hazard models were used to assess the effect of BMI measurements on islet autoimmunity risk. Results: The COVID-19 pandemic was associated with increased time-varying BMI (β = 0.39; 95% CI 0.30, 0.47) and overweight risk at 9 months (β = 0.44; 95% CI 0.03, 0.84). During the COVID-19 pandemic, a higher stringency index was positively associated with time-varying BMI (β = 0.02; 95% CI 0.00, 0.04 per 10 units increase), BMI at 9 months (β = 0.13; 95% CI 0.01, 0.25) and overweight risk at 9 months (β = 0.23; 95% CI 0.03, 0.43). A higher age-corrected BMI and overweight risk at 9 months were associated with increased risk for developing islet autoimmunity up to 5.5 years of age (HR 1.16; 95% CI 1.01, 1.32 and HR 1.68, 95% CI 1.00, 2.82, respectively). Conclusions/interpretation: Early-childhood BMI increased during the COVID-19 pandemic, and was influenced by the level of restrictions during the pandemic. Controlling for the COVID-19 pandemic, elevated BMI during early childhood was associated with increased risk for childhood islet autoimmunity in children with genetic susceptibility to type 1 diabetes. [ABSTRACT FROM AUTHOR]

This study examines the consequences of the pandemic on subjective well-being. First, we investigate to what extent regional and temporal differences in COVID-19 restrictions can explain individuals' life satisfaction in Germany. Second, we examine to what extent "subjective" evaluations of the pandemic are related to life satisfaction. Third, we examine whether these relationships vary with gender, parenthood, and partnership status, or whether relationships changed regarding specific sub-populations (i.e., mothers, fathers, childless women/ men). Merging representative survey data from the German Family Demography Panel Study (FReDA) and contextual data on COVID-19 restrictions (i.e., the stringency index), we analyze a sample of 32,258 individuals living in Germany in their regional settings on the NUTS-3 level during the "second lockdown" in spring 2021. Furthermore, we use the FReDA field period between April and June 2021 to assess temporal variations in COVID-19 restrictions and their association with life satisfaction. To answer our research questions, we compare aggregated means and use variance decomposition and multivariate regression models. Our results show strong regional and temporal differences in COVID-19 restrictions, but neither temporal nor regional differences in "subjective" perceived pandemic burden or in life satisfaction at the aggregated level. At the individual level, we find substantive negative associations between perceived pandemic burden and life satisfaction, which are particularly strong among mothers. Our study shows that individuals' negative perceptions of the pandemic are an important correlate to life satisfaction, whereas regional differences or temporal changes in COVID-19 restrictions appear to be irrelevant for the period under investigation. [ABSTRACT FROM AUTHOR]

Introduction: Execution of COVID-19 lockdown measures caused variations in air pollution worldwide. This paper investigates the impact of COVID-19 stringency measures on the spatio-temporal dynamics of air pollution in Mumbai, India, using a comprehensive two-and-a-half-year pandemic period dataset. Materials and methods: We classified the pandemic period into 7 phases and 21 sub-phases based on the severity of the Oxford COVID-19 Government Response Tracker (OxCGRT) Stringency Index (SI). Optimized Hotspot analysis (OHS) and Ordinary Least Square Regression models explored the spatio-temporal fluctuations and the effect of stringency measures on air quality. Results: The R2 value varied; with the best model R2 of 0.61 for Particulate Matters (PM10) and Nitrogen dioxide (NO2) and lowest of 0.23 for Sulfur dioxide (SO2). A 10-point increase in SI caused a 3-7% reduction in air pollutants. Substantial reduction in average PM10, PM2.5, NO2, and Carbon monoxide (CO) was observed throughout the COVID-19 phases. Meteorology and SI collectively caused maximum reduction of 82.6%, 72.7%, 53.8%, 52.2%, 49.1%, 28.4% for NO2, PM2.5, PM10, NH3, CO, and SO2 respectively, during complete or extreme lockdown phases. Except SO2, seasonality significantly influenced the pollutant concentrations. Winter was the worst period while monsoon was the best. OHS identified central Mumbai wards as hotspots and areas close to the national park as coldspots. Conclusion: PM10, NO2 and CO were more affected by SI measures than NH3 and SO2. For a rapid emergency response to high PM10, implementation of SI, very high (≥ 80 score) and above is advised. Findings of this study have significant public health policy implications, especially among global south nations.

Guiling Zhou,1 Stijn de Vos,1 Catharina CM Schuiling-Veninga,1 Jens Bos,1 Katrien Oude Rengerink,2 Anna Maria Gerdina Pasmooij,2 Peter GM Mol,2,3 Geertruida H de Bock,4 Eelko Hak1 1Unit of Pharmaco-Therapy, -Epidemiology and -Economics (PTEE), Department of Pharmacy, University of Groningen, Groningen, the Netherlands; 2Medicines Evaluation Board, Utrecht, the Netherlands; 3Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; 4Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the NetherlandsCorrespondence: Guiling Zhou, Unit of Pharmaco-Therapy, -Epidemiology and -Economics (PTEE), Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, Groningen, 9713 AV, the Netherlands, Tel +31 503638707, Fax +31 503632772, Email g.zhou@rug.nlBackground: Repurposing registered drugs could reduce coronavirus disease (COVID-19) burden before novel drugs are authorized. Little is known about how the pandemic and imposed restrictions changed their dispensing. We aimed to investigate the impact of COVID-19 pandemic on repurposed drugs dispensing in the Netherlands.Methods: We performed interrupted time-series study using University of Groningen prescription database IADB.nl to evaluate dispensing trends of 24 repurposed drugs before (2017-February 2020) and after (March 2020– 2021) the pandemic’ start. Primary outcomes were monthly prevalence and incidence rates. An autoregressive integrated moving average model assessed the effect of pandemic and stringency index (measuring strictness of government’s restriction policies).Results: Annual number of IADB.nl population ranged from 919,697 to 952,400. Generally, dispensing of common long-term-used drugs was not significantly affected by pandemic. The prevalence of antibacterials (− 4.20 users per 1000 people), antivirals (− 0.04), corticosteroids (− 1.29), prednisolone (− 1.32), calcium channel blocker (− 0.41), and diuretics (− 1.29) was lower than expected after the pandemic’s start, while the prevalence of ivermectin (0.07), sulfonylureas (0.15), sodium-glucose co-transporter-2 (SGLT2) inhibitor (0.17), and anticoagulants (1.95) was higher than expected. The pandemic was associated with statistically significant decreases in the incidence of antibacterials (− 1.21), corticosteroids (− 0.60), prednisolone (− 0.64) and anticoagulants (− 0.02), and increases in ivermectin (0.02), aggregated antidiabetic drugs (0.13), and SGLT2 inhibitors (0.06). These trends were positively associated with pandemic and negatively associated with stringency index.Conclusion: Dispensing of most drugs was not significantly associated with pandemic and government’s response. Despite some statistically significant disruptions, these were not necessarily clinically relevant due to small absolute differences observed.Keywords: COVID-19, drug utilization, repurposed drug, stringency index

This article presents a study conducted in Turkey that examines the relationship between nonpharmaceutical interventions (NPIs) and COVID-19 cases and deaths. The study analyzes daily data from March 11, 2020, to March 8, 2022, and uses the Toda and Yamamoto causality analysis to determine the causal relationship between the stringency index (SI) and new cases and deaths. The results show that an increase in new cases and deaths leads to an increase in the stringency level, but the stringency level does not significantly affect new cases and deaths. However, increases in the stringency level do lead to a significant reduction in COVID-19 incidence in the subsequent 28 days. The findings suggest that there is a one-way causal relationship between NPIs and COVID-19 cases and deaths in Turkey, emphasizing the importance of considering the lagged effect of the stringency index on the number of cases and deaths. This research can help decision-makers understand the consequences of pandemic interventions and develop appropriate strategies. [Extracted from the article]

This article investigates the impact of Government's response measures to new COVID-19 cases. This is proxied by a stringency index of 50 countries from April 2020 to March 2022. Our World in Data COVID-19 dataset was utilised employing several panel econometrics methods. This article fills a gap in empirical research by employing a range of econometric methods over an extended period and countries. The article provides the basis for the formulation and implementation of government response measures or policies to other major public health events that may occur in the future. The research found a positive association between Government's response measures and new cases initially and in the long term and a significant short-term error correction component. This indicates an incremental and repeatable implementation approach, proposing a cyclical or lagged relationship where response measures reach a level of stringency after some time, then induce a decline in new cases. The timing, speed, and stringency of implementation of the government policy response measures are crucial in our understanding of the relationship or link between the government policy response measures and new COVID-19 cases. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, along with oppressive government interventions, placed a heavy burden on mental health. Suicide mortality is an outcome that may have been affected by the stringency of these lockdown measures. The aim of this study is to examine the association between lockdown intensity, measured by the Stringency Index, and suicide mortality rates in US states from March 2020 to December 2021. To this end, Bayesian methods were used for the estimation of the association for the total population, as well as by gender, and by race. Results show a small negative association between lockdown intensity and suicide mortality rates which applies to most of the examined populations. Future research will determine if this relationship remains the same after the pandemic.

OBJECTIVE: Studies have investigated the effects of lockdowns on air quality around the world and found that fine particulate matter and nitrogen dioxide concentrations decreased due to reduced human activity, while ozone concentrations increased. In this study, we aimed to evaluate the correlation between daily stringency index values of our country and daily PM10, nitrogen dioxide, and ozone measurements in different districts of Istanbul between March 1, 2020, and February 28, 2022. MATERIAL AND METHODS: Ministry of Environment and Urbanization and National Air Quality Monitoring Network data on Istanbul air quality monitoring stations were used. The analysis included 15 stations that can monitor at least 75% of the days in a year. PM10, nitrogen dioxide, and ozone were the main pollutants analyzed. RESULTS: There was negative correlation between daily PM10 measurements and daily stringency index values in 3 stations; there was positive correlation in 6 stations. Between daily stringency index values and daily nitrogen dioxide measurements, there was a negative correlation in 3 stations and a positive correlation in 1 station. The daily measurements of 1 station showed a negative correlation with the daily values of stringency index for both PM10 and nitrogen dioxide. In 1 station, while PM10 measures were negatively correlated with stringency index, nitrogen dioxide measurements were positively correlated. CONCLUSION: This study showed that pandemic limitations could not improve Istanbul's air quality everywhere. For adequate evaluation of impact of the limitations on air quality, it may be more relevant to study the socioeconomic infrastructure of each living area, the sociospatial inequality, industrial employment, the number of households, the density of employee class, and so on with all influencing factors that could have contributed to these various changes. [ABSTRACT FROM AUTHOR]

Purpose: Late in 2019, the corona virus outbreak caused complex economic issues and substantially impacted the global economy. Governments resorted to nonpharmaceutical interventions, such as social isolation and mandatory quarantines to combat the ever-increasing spread of this virus. These restrictions, which are referred to as a non-vaccine intervention, have been criticized by some economists, and this led to the formation of the topic of the government's actions against the spread of the virus. What effect has it had on the economy and especially macro–variables? In the economic cycle, the imposition of restrictions and quarantine and measures like these have caused a decrease in the supply of labor, a decrease in the activity of enterprises, their production and the gross domestic production. Considering the possibility of the economic costs of these interventions imposed on the economies of countries, the current research attempts to investigate the economic effects of non-pharmacological measures taken during the period of the COVID-19 spread in a number of developed and developing nations. Methodology: This study aims to examine the impact of non-pharmaceutical government interventions on the gross domestic production (GDP) of developing and developed nations during the period of 2020 to 2022. This is done with seasonal data, and, for each country, the panel generalized moments model (Panel GMM) is utilized. Therefore, the following model is estimated for each group of countries: 𝐿n 𝐺𝑑𝑝𝑖𝑡 = 𝛽1𝐿𝑛𝐺𝑑𝑝𝑖𝑡−1 + 𝛽2𝐿𝑛𝑂𝑝𝑒𝑛𝑖𝑡 + 𝛽3𝐿𝑛𝑇𝑜𝑢𝑟𝑖𝑠𝑚𝑖𝑡 + 𝛽4𝐿𝑛𝑆𝑡𝑟𝑖𝑛𝑖𝑡 + 𝛽5𝐿𝑛𝑁𝑒𝑤𝑐𝑖𝑡 + 𝜀𝑖𝑡, where Gdp represents 𝐺𝐷𝑃 at constant prices in 2015, 𝑂𝑝𝑒𝑛 represents the degree of trade openness, 𝑇𝑜𝑢𝑟𝑖𝑠𝑚 represents the number of tourists, 𝑆𝑡𝑟𝑖𝑛 represents the government stringency index, and 𝑁𝑒𝑤𝑐 represents the number of new COVID cases. Findings and Discussion: The results of the panel GMM estimation indicate that the previous-period GDP had a positive and significant effect on the current-period GDP in both developed and developing countries. The degree of trade openness has a positive and significant effect on the GDP in both developed and developing countries, such that a one-percent increase in the trade openness raises the GDP by 0.026% in developed countries and by 0.634% in developing countries. The results from both categories of the studied countries indicate that the number of tourists entering the country had a positive and statistically significant effect on the GDP. In developed countries, a one-percent increase in the number of incoming tourists results in a 0.107% increase in the GDP, while, in developing countries, it results in a 0.03% increase in the GDP. The government austerity index, which is used to evaluate the economic costs of non-pharmaceutical interventions during the COVID-19 pandemic, has had a negative and significant impact on the GDP of both developed and developing countries. This indicates that government austerity has a negative and significant effect on economic growth. It is that non-medicinal government interventions to control the epidemic have resulted in a decline in the gross domestic production of countries. The findings indicate that a one-percent increase in the government austerity index decreases the GDP by 0.03 percent in established nations and by 0.001 percent in developing ones. This difference in the estimated coefficient indicates that the austerity index had a greater negative impact on the GDP of developed nations. The variable coefficient for the number of newly infected individuals differs in developed and developing nations. In developed nations, this coefficient is negative and statistically significant. The number obtained for this coefficient in this group of countries indicates that, as predicted, a one-percent increase in the number of new cases of COVID-19 has resulted in a 0.001% decrease in the GDP, whereas, in developing countries, a one-percent increase in the number of new cases of the disease has resulted in a 0.009% increase in the GDP. Conclusion and Policy Implications: Due to the rapid global spread of COVID-19, the government's role in controlling and overcoming this situation has been undeniable and indispensable. Therefore, it is recommended that governments stimulate aggregate demand and increase their expenditure (G) through various monetary and financial channels, such as lowering interest rates, providing packages and support facilities, and reducing taxes. Since effective vaccines were not yet discovered at the beginning of the spread of this virus and, therefore, it was necessary and natural for governments to adopt preventative austerity measures, it is suggested that, in such critical times, governments could be warned to increase information regarding the economic cost and negative effects of non-pharmaceutical measures on the country. The results of this research provide policymakers with the possibility of future epidemics of comparable or even greater magnitude than COVID-19. This index measures the economic costs incurred by the government during these times. It suggests that, by understanding and analyzing such costs in similar circumstances, organizations can modify their strategies or develop support mechanisms to reduce the cost and external effects of such actions. [ABSTRACT FROM AUTHOR]

Exploring the factors influencing medical waste generation is vital for proper management due to its hazardous nature. Improper treatment would cause secondary environmental pollution, especially related to public health emergencies. However, there is not enough research on exploring COVID-19-associated factors with medical waste generation, and there is a lack of basic understanding of implementing governmental policies related to the pandemic. The medical waste generated due to COVID-19 is directly or indirectly influenced by government policies. The aim of this study is to explore the factors associated with COVID-19 that impact the amount of medical waste in Bahrain. Data about the quantities of COVID-19 waste (CW) from February 2020 to May 2022 were obtained from Bahrain Waste Treatment Company BWTC. Data about predictors related to COVID-19 were obtained from the public domain. The structural equation modeling SEM technique was applied using AMOS software to identify the driving forces. The model results revealed that the vaccination and newly infected cases are statistically significant predictors for waste generation during the pandemic, with standardized coefficients of 0.77 and 0.20, respectively. But the factors, number of tests, and deaths are not statistically significant. Moreover, the stringency index factor moderates the relationship between the CW and the two predictors, vaccination and new cases. In dealing with this sudden increase in medical waste, the incineration facility has been outstripped and faced immense pressure over handling medical waste generated during COVID-19. Therefore, this study recommends increasing the number of medical waste facilities. [ABSTRACT FROM AUTHOR]

The article shows the relationships between the COVID and non‑COVID deaths during the first year of the pandemic, compared with the stringency of restrictions imposed and the compulsory spending on healthcare. We compare these relationships among European countries, analysing weekly data and applying cointegration models. Regarding the pandemic’s intensity, we split the period into two: March – August 2020 and September 2020 – February 2021. We find that, most often, if there was a relationship between the stringency index and COVID or non‑COVID mortality, it was usually positive and mortality driven. That suggests that although the governments tailored the restrictions to the growing mortality rate, they were unable to control the pandemic. No relationships, or negative ones, were most often found in these countries where the spending on healthcare was the highest (i.e., Northern and Western European countries). The biggest weekly changes in non‑COVID deaths during the second sub‑period were observed in the Central and Eastern European countries, where government healthcare expenditures per capita are the lowest.

Copyright of Share: Journal of Islamic Economics & Finance / Jurnal Ekonomi dan Keuangan Islam is the property of Share Jurnal Ekonomi dan Keuangan Islam and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The pandemics in the history of world health organization have always left memorable hallmarks, on the health care systems and on the economy of highly effected areas. The ongoing pandemic is one of the most harmful pandemics and is threatening due to its transformation to more contiguous variants. Here in this manuscript, we will first outline the variants and then their impact on the associated health issues. The deep learning algorithms are useful in developing models, from a higher dimensional problem/ dataset, but these algorithms fail to provide insight during the training process and do not generalize the conditions. Transfer learning, a new subfield of machine learning has acquired fame due to its ability to exploit the information/learning gained from a previous process to improve generalization for the next. In short, transfer learning is the optimization of the stored knowledge. With the aid of transfer learning, we will show that the stringency index and cardiovascular death rates were the most important and appropriate predictors to develop the model for the forecasting of the COVID-19 death rates. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the impact of a sudden shock from the COVID-19 epidemic on the behavioral bias of investors in the stock market of Iran as a developing country. The study also examines whether the government response to the COVID-19 pandemic can reduce investor herding behavior. We have used the Cross-sectional absolute deviation (CSAD) to measure securities dispersion from market returns. The studied period includes the cross-sectional data of the top 50 companies listed on the stock exchange during 2381 working days of the market (from March 1, 2012, to March 1, 2022). Furthermore, we use the semi-parametric estimator of the quantile regression for the data on the Iranian government response during the COVID-19 epidemic taken from the Oxford COVID-19 Government Response Tracker (OxCGRT). The main findings are in order. First, results show that the COVID-19 pandemic caused the formation of herding behavior aggravated by market volatility. Second, we document that the government response stringency index is unsuccessful in reducing investor herding behavior in the Iranian stock market. Finally, given the evidence that herding behavior, as a form of behavioral distortion, can drive security prices away from equilibrium values supported by fundamentals and cause price bubbles, our findings have important implications for policymakers and investors to mitigate herding effects and mis valuations.

This study analysed the consequences of COVID-19 on Ghanaian financial markets and further profiled and assessed the effectiveness of government policy interventions to contain its incidence. Using a qualitative documentary analytic approach combined with available time series data from financial market regulators between 2015 and 2021, empirical evidence shows that key profitability (ROA and ROE) measures of banks, gross insurance premium and capital market indicators were negatively affected. The containment and stringency of government policies in the wake of the pandemic do not match in equal potency with the rise in occurrences. Policy recommendations were provided. [ABSTRACT FROM AUTHOR]

This study investigates the impact of government policy responses of COVID‐19 pandemic on stock market liquidity for listed Australian companies and for 11 different industries separately. A quantitative deductive approach is used for a sample of 1,452 companies with a total of 292,164 firm‐day observations over a period from January 25, 2020 to December 31, 2020 during the outbreak of COVID‐19. Univariate and multivariate (two‐way cluster‐robust panel regression) analysis were conducted. Data were collected from the Oxford COVID‐19 Government Response Tracker, Worldmeter, Refinitiv Workspace and Datastream. Our findings indicate that the influences of the six out of seven stringency policy responses reduced Australian equity market liquidity. However, public information campaigns enhanced market liquidity and hence trading activity. Among the 11 industries, our analysis shows that the non‐pharmaceutical interventions by the Australian government have significant and positive effects on four industries: Consumer non‐cyclicals, healthcare, financial and technology. However, the worse effects were depicted in the industrial (transportation) and energy industries. This study is important for investors, policymakers and regulators to understand the diverse effects of government policy responses of COVID‐19 on stock market liquidity to enhance financial stability. Moreover, understanding this effect is particularly important to decision‐makers such as portfolio and fund managers to manage their portfolios and trading activities during extreme turbulence times, such as COVID‐19. Unlike previous studies that focus on country analysis, this study examines on firm basis the impact of government interventions on stock market liquidity in a well developed Australian stock market. [ABSTRACT FROM AUTHOR]

Background: Many studies have examined the effectiveness of non-pharmaceutical interventions (NPIs) on SARS-CoV-2 transmission worldwide. However, less attention has been devoted to understanding the limits of NPIs across the course of the pandemic and along a continuum of their stringency. In this study, we explore the relationship between the growth of SARS-CoV-2 cases and an NPI stringency index across Canada before the accelerated vaccine roll-out. Methods: We conducted an ecological time-series study of daily SARS-CoV-2 case growth in Canada from February 2020 to February 2021. Our outcome was a back-projected version of the daily growth ratio in a stringency period (i.e., a 10-point range of the stringency index) relative to the last day of the previous period. We examined the trends in case growth using a linear mixed-effects model accounting for stringency period, province, and mobility in public domains. Results: Case growth declined rapidly by 20–60% and plateaued within the first month of the first wave, irrespective of the starting values of the stringency index. When stringency periods increased, changes in case growth were not immediate and were faster in the first wave than in the second. In the first wave, the largest decreasing trends from our mixed effects model occurred in both early and late stringency periods, depending on the province, at a geometric mean index value of 30⋅1 out of 100. When compared with the first wave, the stringency periods in the second wave possessed little association with case growth. Conclusions: The minimal association in the first wave, and the lack thereof in the second, is compatible with the hypothesis that NPIs do not, per se, lead to a decline in case growth. Instead, the correlations we observed might be better explained by a combination of underlying behaviors of the populations in each province and the natural dynamics of SARS-CoV-2. Although there exist alternative explanations for the equivocal relationship between NPIs and case growth, the onus of providing evidence shifts to demonstrating how NPIs can consistently have flat association, despite incrementally high stringency.

BackgroundWe estimated the association between the level of restriction in nine different fields of activity and SARS-CoV-2 transmissibility in Spain, from 15 September 2020 to 9 May 2021.MethodsA stringency index (0–1) was created for each Spanish province (n = 50) daily. A hierarchical multiplicative model was fitted. The median of coefficients across provinces (95% bootstrap confidence intervals) quantified the effect of increasing one standard deviation in the stringency index over the logarithmic return of the weekly percentage variation of the 7-days SARS-CoV-2 cumulative incidence, lagged 12 days.ResultsOverall, increasing restrictions reduced SARS-CoV-2 transmission by 22% (RR = 0.78; one-sided 95%CI: 0, 0.82) in 1 week, with highest effects for culture and leisure 14% (0.86; 0, 0.98), social distancing 13% (0.87; 0, 0.95), indoor restaurants 10% (0.90; 0, 0.95) and indoor sports 6% (0.94; 0, 0.98). In a reduced model with seven fields, culture and leisure no longer had a significant effect while ceremonies decreased transmission by 5% (0.95; 0, 0.96). Models R2 was around 70%.ConclusionIncreased restrictions decreased COVID-19 transmission. Limitations include remaining collinearity between fields, and somewhat artificial quantification of qualitative restrictions, so the exact attribution of the effect to specific areas must be done with caution.

IntroductionContainment and closure policies are effective measures used in the early stages of a highly transmissible global pandemic such as COVID-19 to mitigate the spread and reduce transmissions. However, these policies can have negative impacts on the economy and personal freedom. Governments must carefully consider the necessity of increasing their stringency. Local contexts and priorities regarding domestic disease outbreaks and the risk of imported cases from other countries may vary among different countries, and could influence the decision to increase containment measures. Thus, this study aimed to differentiate the impacts of these affecting factors on the stringency of governmental containment measures through cross-continental comparisons.MethodsThis study utilized a zero/one inflated beta (ZOIB) regression model to investigate how domestic epidemic, imported risk, and local context affect government responses to a pandemic. We used a country’s weekly confirmed case and death numbers as a measure of its domestic threat. The imported risk was measured using a combination of weekly new cases in each country and the air passenger traffic between countries.ResultsThe findings indicate that domestic case numbers are a primary concern for governments when deciding to increase policy stringency. Countries with higher development levels tend to implement stricter policies as they can better handle the negative impacts. Additionally, there is an interaction between case numbers and development level, with countries at the second or third highest development level focusing more on domestic outbreaks than imported risks, while those at the highest level have similar concerns for both.ConclusionsWe concluded that most countries adjust policies’ stringency majorly based on the variation of domestic case number rather than the other pandemic factors and the countries with a high development level tend to implement strict policies since their socio-economical condition could afford such policies. These insights can aid policymakers in improving containment and closure policies for future pandemics.

The aim of the study was to estimate the effect of the COVID- 19 pandemic and response policies on the psychiatric ward admissions in the hospitals referring to the ASST Lariana (province of Como, Italy) and the Hospital of Mendrisio (Canton of Ticino, Switzerland), two similar territories that belong to countries that dealt differently with the pandemic. We compared the two territories for type of admission (voluntary vs. compulsory), the Stringency Index (SI) and the country’s number of admission in Intensive Care Units (ICU). We found a significant reduction in the psychiatric ward admission in the lockdown period in both territories, even in periods with milder lockdown measures. The admission rate’s reduction in the ASST Lariana was significantly associated with the ICU admissions (p

Background: Biliary atresia (BA) is a rare cholangiopathy where one of the proposed aetiological mechanisms is an infectious viral trigger. Coronavirus disease-19 (COVID) lockdown restrictions were implemented to reduce the transmission of infections. Strictness of lockdown varied across European countries. This study aimed to investigate if there was an association between strictness of lockdown and change in isolated BA (IBA) incidence in Europe. Methods: We approached European centres involved in the European Reference Network RARE-LIVER. We included IBA patients born between 2015 and June 2020. We calculated the number of IBA patients born per centre per month. The Stringency Index (SI) was used as lockdown strictness indicator. The association between percentage change of mean number of IBA patients born per month and the SI was assessed. Results: We included 412 IBA patients from thirteen different centres. The median number of patients per month did not change: 6 (1–15) pre-lockdown and 7 (6–9) during lockdown (p = 0.34). There was an inverse association between SI and percentage change in IBA (B = -0.73, p = 0.03). Median age at Kasai portoenterostomy (days) did not differ between time periods (51 (9–179) vs. 53 (19–126), p = 0.73). Conclusion: In this European study, a stricter COVID-lockdown was seemingly accompanied by a simultaneous larger decrease in the number of IBA patients born per month in the lockdown. Results should be interpreted with caution due to the assumptions and limitations of the analysis. [ABSTRACT FROM AUTHOR]

Due to the pandemic situation caused by COVID-19 disease, there have been tremendous efforts worldwide to keep the spread of the virus under control and protect the functioning of health systems. Although governments take many actions in fighting this pandemic, it is well known that health systems play an undeniable role in this fight. This study aimed to investigate the role of health systems and government responses in fighting COVID-19. By purposively sampling Finland, Denmark, the UK, and Italy and analyzing their health systems' performances, governments' stringency indexes, and COVID-19 spread variables, this study showed that high-performing health systems were the main power of states in managing pandemic environments. This study also measured relations between short and medium-term measures and COVID-19 case and death numbers in all study countries. It showed that medium-term measures had significant effects on death numbers. [ABSTRACT FROM AUTHOR]

The study aims to determine whether government policies to control population mobility have been successful in the fight against the coronavirus disease 2019 (COVID-19) pandemic. Policies implemented by governments for controlling population mobility are identified with the Stringency Index prepared by Oxford University. Population mobility is observed through data provided by Google Community Mobility Report. The success of countries in the fight against the COVID-19 pandemic is measured by the Reproduction Rate. The intersection of valid data covering 104 countries is gathered from databases of relevant official websites for the period between the date of reaching the 100th cumulative case and the date 360 days later. The data is analyzed by conducting panel data analysis method to test the hypothesis. Results show that the Stringency Index demonstrating the stringency of government policies implemented by countries to prevent the spreading of pandemic affected human mobility dimensions significantly and reversely. Human mobility dimensions have a reverse and significant impact on staying at home at different levels at the 95% confidence interval. Furthermore, a significant relationship with a very small bi value (-0.00008) emerges between staying at home and the Reproduction Rate in the reverse direction. [ABSTRACT FROM AUTHOR]

The objective of this paper is to provide an insight on effect of stringency in Covid-19 spread in India especially in Chennai, a city were more lockdown, and restrictions was imposed to control the infection. Even though the restriction was imposed in the country by the end of March 2020, the growth reduction was seen in the mid of June as the awareness was increased. The average Covid-19 case growth was got reduce from 3.43 to 2.62% by July mid. To analysis the impact of stringency, a detailed analysis was done on Chennai city which was imposed with more repeated lockdowns to flatten the curve. We tried to fit a regression line with three difference scenario of data. The results show a promising R-squared and p value, with a right skewed distribution normal probability plot. The impact of lockdown in people's lives in different sectors were also discussed in this paper. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Sociales (13159518) is the property of Revista de Ciencias Sociales de la Universidad del Zulia Venezuela and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of the study was to estimate the effect of the COVID-19 pandemic and response policies on the psychiatric ward admissions in the hospitals referring to the ASST Lariana (province of Como, Italy) and the Hospital of Mendrisio (Canton of Ticino, Switzerland), two similar territories that belong to countries that dealt differently with the pandemic. We compared the two territories for type of admission (voluntary vs. compulsory), the Stringency Index (SI) and the country's number of admission in Intensive Care Units (ICU). We found a significant reduction in the psychiatric ward admission in the lockdown period in both territories, even in periods with milder lockdown measures. The admission rate's reduction in the ASST Lariana was significantly associated with the ICU admissions (p<0.001). In the Hospital of Mendrisio, admissions included a weekly seasonality, were significantly correlated with SI (p=0.001) and period (pre-pandemic and pandemic; p<0.001) and we observed also a significant reduction of compulsory admission that is influenced both by the stringency index (p<0.001) and period (p<0.001). The differences between the two territories seem influenced by the different mental health systems. [ABSTRACT FROM AUTHOR]

Copyright of Comparative Economic Research is the property of Wydawnictwo Uniwersytetu Lodzkiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The goal of the study here is to analyze and assess whether strict containment policies to cope with Coronavirus Disease 2019 (COVID-19) pandemic crisis are effective interventions to reduce high numbers of infections and deaths. A homogenous sample of 31 countries is categorized in two sets: countries with high or low strictness of public policy to cope with COVID-19 pandemic crisis. The findings here suggest that countries with a low intensity of strictness have average confirmed cases and fatality rates related to COVID-19 lower than countries with high strictness in containment policies (confirmed cases are 24.69% vs. 26.06% and fatality rates are 74.33% vs. 76.38%, respectively, in countries with low and high strictness of COVID-19 public policies of containment). What this study adds is that high levels of strict restriction policies may not be useful measures of control in containing the spread and negative impact of pandemics similar to COVID-19 and additionally a high strictness in containment policies generates substantial social and economic costs. These findings can be explained with manifold socioeconomic and environmental factors that support transmission dynamics and circulation of COVID-19 pandemic. Hence, high levels of strictness in public policy (and also a high share of administering new vaccines) seem to have low effectiveness to stop pandemics similar to COVID-19 driven by mutant viral agents. These results here suggest that the design of effective health policies for prevention and preparedness of future pandemics should be underpinned in a good governance of countries and adoption of new technology, rather than strict and generalized health polices having ambiguous effects of containment in society. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of the Covid-19 pandemic on stock market returns and their volatility in the case of the G20 countries. In contrast to the existing empirical literature, which typically focuses only on either Covid-19 deaths or lockdown policies, our analysis is based on a comprehensive dynamic panel model accounting for the effects of both the epidemiological situation and restrictive measures as well as of fiscal and monetary responses; moreover, instead of Covid-19 deaths it uses a far more sophisticated Covid-19 index based on a Balanced Worth (BW) methodology, and it also takes into account heterogeneity by providing additional estimates for the G7 and the remaining countries (non-G7) separately. We find that the stock markets of the G7 are affected negatively by government restrictions more than the Covid-19 pandemic itself. By contrast, in the non-G7 countries both variables have a negative impact. Further, lockdowns during periods with particularly severe Covid-19 conditions decrease returns in the non-G7 countries whilst increase volatility in the G7 ones. Fiscal and monetary policy (the latter measured by the shadow short rate) have positive and negative effects, respectively, on the stock markets of the G7 countries but not of non-G7 ones. In brief, our evidence suggests that restrictions and other policy measures play a more important role in the G7 countries whilst the Covid-19 pandemic itself is a key determinant in the case the non-G7 stock markets. [ABSTRACT FROM AUTHOR]

We examine the asymmetric effect of COVID-19 government interventions on global stock markets using a sample of 61 countries over the period of January 2020 to December 2021, applying Quantile ARDL (QARDL) and panel threshold regressions. The QARDL results show a heterogenous effect of government interventions on stock markets which varies along with country income level and stock market size. Additionally, the panel threshold regression reveals a positive effect before and a negative effect after the threshold level of government interventions. Our findings can assist policymakers to formulate intervention plans in limiting financial turbulence. [ABSTRACT FROM AUTHOR]

The pandemic of COVID-19 has affected human patterns since December 2019. Since the very beginning, most countries imposed strict measures such as lockdowns and the suspension of all nonessential movements to reduce the spread of the pandemic. Therefore, mobility, road safety, and travel behavior were also significantly affected. At present, many studies tried to investigate travel or mobility behavior changes taking into account all possible transportation modes, but very few studies investigated driving behavior. This study aims to investigate driving behavior and its correlation with the strictness of COVID-19 response measures. Four neural network autoregression (NNAR) models with an external regressor were developed in order to forecast three different future stringency scenarios. NNAR models were employed as the forecasting performance was superior when comparing with statistical autoregressive integrated moving average (ARIMA) models. The NNAR models were developed using driving behavior-related variables (i.e., driving speed, speeding, speeding duration percentage, and mobile use percentage), derived from a smartphone application that has been developed by OSeven Telematics. The NNAR models were trained on 2020 data and three different scenarios were predicted for 2021 by providing three different constant stringency indices (i.e., 0, 55, 85). In particular, normal conditions without restrictions were simulated with zero stringency index, whereas moderate restrictions were simulated with 55 and finally, fully restrictions were simulated with 85. The NNAR modeling results showed that with higher stringency index, mobile use and driving speed tend to increase, whereas speeding duration demonstrates higher peaks. Interestingly, with stricter response measures, lower values were forecasted for speeding. Taking into account the modeling outcomes, there is a direct effect of the COVID-19 response measures on driving behavior. Nevertheless, a wider time frame for data collection as well as the use of more sophisticated techniques to control for the interrelationship between COVID-19 spread and driving behavior might be useful for future studies. [ABSTRACT FROM AUTHOR]