Effects Of Public Health Policies Research Articles

Commodity market stability and sustainable development: The effect of public health policies

This study explores the influence of public health policies on commodity market volatility during public health emergencies, such as pandemics, using data from China and the US. We investigate how stringent public health measures can mitigate the effects of pandemics on the stability of commodity markets by stabilizing domestic demand and supply of natural resources. Our findings highlight the interconnectedness between commodity market stability and oil production, showing that firms increase their oil inventories in response to oil market volatility as a precautionary measure. This action, in turn, affects the amount of oil available for production, impacting oil consumption and extraction rates. We demonstrate that stability in the oil market significantly influences not only oil consumption but also has broader implications for sustainable development, green asset markets, and carbon emissions.

Trust as a catalyst: revealing the impact of government trust and professional trust on public health policy compliance during a pandemic.

Existing research has extensively explored the relationship between government trust and compliance behaviour, but significant controversies exist. Some studies suggest a strong positive correlation between the two. Other studies have found that government trust hinders compliance behaviour. However, during the pandemic, the effectiveness of public health policies largely depends on the public's compliance with these policies. To examine the aforementioned controversies, this study utilizes survey data on the Chinese population during the COVID-19 period to explore the relationship between compliance with public health policies and government trust. The study conducted a questionnaire survey of 1,395 individuals from 25 provinces in China from mid-November to mid-December 2022. Firstly, we categorized the public's compliance behaviour with public health policies based on the results of factor analysis. Subsequently, we examined the impact of government trust and professional trust on compliance behaviour with public health policies by constructing a structural equation model. Based on the results of factor analysis, we classified public adherence to public health policies into protective compliance and restrictive compliance. Results from the structural equation model show a positive correlation between the public's trust in the government and both protective and restrictive compliance, with a stronger influence on protective compliance. Government trust also exerts a positive impact on restrictive compliance behaviour through professional trust. Additionally, the study indicates a significant positive correlation between the public's professional trust and restrictive compliance, while it does not significantly affect protective compliance. Moreover, the public from rural areas demonstrates a greater willingness to adhere to both types of public health policies. Married individuals exhibit a stronger inclination toward protective compliance, while females show a stronger tendency toward restrictive compliance. The study revealed a significant positive impact of government trust and professional trust on compliance behaviour with public health policies during the COVID-19 pandemic, refuting any negative correlation between government trust and compliance behaviour. Normative motivations for compliance behaviour had a substantial impact on adherence. These findings offer valuable insights for future public health crisis management and public policy formulation.

Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission.

In this study, we investigate the COVID-19 epidemics in Brazilian cities, using early-time approximations of the SIR model in networks and combining the VAR (vector autoregressive) model with machine learning techniques. Different from other works, the underlying network was constructed by inputting real-world data on local COVID-19 cases reported by Brazilian cities into a regularized VAR model. This model estimates directional COVID-19 transmission channels (connections or links between nodes) of each pair of cities (vertices or nodes) using spectral network analysis. Despite the simple epidemiological model, our predictions align well with the real COVID-19 dynamics across Brazilian municipalities, using data only up until May 2020. Given the rising number of infectious people in Brazil-a possible indicator of a second wave-these early-time approximations could be valuable in gauging the magnitude of the next contagion peak. We further examine the effect of public health policies, including social isolation and mask usage, by creating counterfactual scenarios to quantify the human impact of these public health measures in reducing peak COVID-19 cases. We discover that the effectiveness of social isolation and mask usage varies significantly across cities. We hope our study will support the development of future public health measures.

Unpacking assertions made by the alcohol industry and how they make them: An analysis of submissions into Australia's National Alcohol Strategy.

Alcohol is a leading cause of morbidity and mortality globally. One significant barrier to the implementation of evidence-based alcohol policy is alcohol industry opposition. Making submissions to national policy processes is one way in which the industry exert influence. The aim of this study was to analyse alcohol industry submissions into Australia's National Alcohol Strategy to determine key assertions made by the alcohol industry and the ways in which they use evidence and refute the effectiveness of public health policies to make their claims. Submissions made by alcohol industry actors (n = 12) were analysed using content analysis to determine key industry assertions. A pre-existing framework on alcohol industry use of evidence was then applied to analyse the evidentiary practices used to make these assertions. Five common industry assertions were identified: 'Drinking alcohol in moderation has health benefits'; 'Alcohol isn't the cause of violence'; 'Targeted initiatives, not population level alcohol policies, are needed'; 'Strong alcohol advertising regulations are not necessary'; and 'Minimum unit price and pricing and taxation policies more broadly are not needed'. The industry systematically manipulated, misused and ignored evidence throughout their submissions. The alcohol industry is misusing evidence in their submissions to government consultations to make their assertions about alcohol policy. It is therefore essential that industry submissions are scrutinised and not accepted on face value. Additionally, it is suggested that the alcohol industry requires a distinct model of governance similarly to that which regulates the tobacco industry to prevent their attempts to undermine evidence-based public health policy.

Substance Use From Social Distancing and Isolation by US Nativity During the Time of COVID-19: Cross-sectional Study.

The COVID-19 pandemic had many unprecedented secondary outcomes resulting in various mental health issues leading to substance use as a coping behavior. The extent of changes in substance use in a US sample by nativity has not been previously described. This study aimed to design a web-based survey to assess the social distancing and isolation issues exacerbated by the COVID-19 pandemic to describe substance use as a coping behavior by comparing substance use changes before and during the pandemic. A comprehensive 116-item survey was designed to understand the impact of COVID-19 and social distancing on physical and psychosocial mental health and chronic diseases. Approximately 10,000 web-based surveys were distributed by Qualtrics LLC between May 13, 2021, and January 09, 2022, across the United States (ie, continental United States, Hawaii, Alaska, and territories) to adults aged ≥18 years. We oversampled low-income and rural adults among non-Hispanic White, non-Hispanic Black, Hispanic or Latino, and foreign-born participants. Of the 5938 surveys returned, 5413 (91.16%) surveys were used after proprietary expert review fraud detection (Qualtrics) and detailed assessments of the completion rate and the timing to complete the survey. Participant demographics, substance use coping behaviors, and substance use before and during the pandemic are described by the overall US resident sample, followed by US-born and foreign-born self-reports. Substance use included the use of tobacco, e-cigarettes or nicotine vapes, alcohol, marijuana, and other illicit substances. Marginal homogeneity based on the Stuart-Maxwell test was used to assess changes in self-reported substance use before and during the pandemic. The sample mostly included White (2182/5413, 40.31%) and women participants (3369/5406, 62.32%) who identified as straight or heterosexual (4805/5406, 88.88%), reported making ≥US $75,000 (1405/5355, 26.23%), and had vocational or technical training (1746/5404, 32.31%). Similarities were observed between the US-born and the foreign-born participants on increased alcohol consumption: from no alcohol consumption before the pandemic to consuming alcohol once to several times a month and from once to several times per week to every day to several times per day. Although significant changes were observed from no prior alcohol use to some level of increased use, the opposite was also observed and was more pronounced among foreign-born participants. That is, there was a 5.1% overall change in some level of alcohol use before the pandemic to no alcohol use during the pandemic among foreign-born individuals, compared with a 4.3% change among US-born individuals. To better prepare for the inadvertent effects of public health policies meant to protect individuals, we must understand the mental health burdens that can precipitate into substance use coping mechanisms that not only have a deleterious effect on physical and mental health but also exacerbate morbidity and mortality in a disease like COVID-19.

Improving the health of adolescents: the Nordic countries can help fill the evidence gap.

While in the Nordic countries we have well-developed welfare policies and several structural, statutory measures in place aiming to promote public health, studies from these countries are often absent from systematic reviews of research literature assessing the effects of policy measures designed to promote health. Using adolescent health promotion and efforts related to primary prevention of obesity as an example, this short commentary aims to illustrate the paucity of well-designed studies investigating the effects of public health policies affecting adolescents. This paper argues that the Nordic research community is in a good position to help fill this gap, and to contribute more widely to the international literature on evaluation of policy interventions.

P09-02 Risks assessment related to physical activity and sedentary lifestyle profiles among French children and adolescents

IntroductionBased on Anses's report (2016)[1][1], the French Public Health Policy emphasizes on health status improvement by acting on physical activity and sedentary behaviors. Since 2016, many countries have collected results of large epidemiological studies providing new insights into the effect of physical activity- and mainly sedentary-related behaviors on health. To date, behaviors inducing the highest risks are not identified. In this context, based on the data from the most recent French Food Consumption Survey “(Inca3 2017)”[1][2], Anses aims at characterizing the overweight and obesity risks related to physical fitness regarding the levels of physical activity (PA) and sedentary (SED) daily duration of children and adolescents.MethodsFor 11–17 year-old children, the PA and SED behavior were collected using an adapted Youth Risk Behavior Survey questionnaire. Physical activity and sedentary duration were compared to the thresholds considered as safe (Anses 2016): PA > 60 min/day and SED 20 min/day and SED >4h30/day) were set to disaggregate the population that does not reach these benchmarks, allowing to define nine profiles regarding the associated risks identified and updated in the literature. Profiles were compared according to BMI and age using Pearson chi-square tests. All statistical analysis were performed taking into account the survey complex sampling frame design and the individual weighting.ResultsThe preliminary results show nine risk-based profiles of children and adolescents (n = 1285) related to the risk thresholds that can be identified. The most at risk profiles represented almost 50% of the 11-17 years old and were associated with the highest BMI. The highest sedentary (>4h30) profiles were observed in the oldest adolescents. However, among them, regarding the updated literature, those having a high physical activity level were considered as at lower risk.ConclusionFinally, definition of profiles based on risk thresholds, >60 min/day and >20 min/day for PA and allows to characterize the children and adolescents the most a risk in order to enhance the effectiveness of public health policy. The risk assessment could be further refined using accelerometer real time measurement of physical activity and sedentary behavior.

Progress in research on redistribution methods for garbage codes in causes of death data

The existence of garbage codes in death cause surveillance data sets could influence the accuracy of the death cause statistics, and subsequently affect the precision and effectiveness of public health policy making. International and domestic researchers have studied the characteristics of garbage codes in various death cause data sets from different countries or regions in the world. They proposed several approaches for redistributing garbage codes, such as expert consultancy, fixed proportional reassignment, using the information about death cause chain, building statistical models, and so on. This paper summarizes and compares the principles, applications and limitation of application scenarios of currently common methods for garbage code redistribution in order to provide some references for improving the accuracy and usefulness of the death cause data in China.

Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron.

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers () between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high . The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed.

Compulsory licensing and COVID-19: between the effectiveness of public health policies and the perspectives of international policy

Compulsory licensing and COVID-19: between the effectiveness of public health policies and the perspectives of international policy

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave. For this purpose, we took into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. We estimated the growth of the first and second wave across countries by fitting a logistic model to daily-reported case numbers, up to the first and second epidemic peaks. We estimated the basic and effective (second wave) reproduction numbers across countries. Next, we used a random forest algorithm to study the association between the growth rate of the second wave and NPIs as well as pre-existing country-specific characteristics. Lastly, we compared the growth rate of the first and second waves of COVID-19. The top three factors associated with the growth of the second wave were body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times, and restrictions on gatherings of 10 people or less. Artificial intelligence techniques can help scholars as well as decision and policy-makers estimate the effectiveness of public health policies, and implement “smart” interventions, which are as efficacious as stringent ones.

A JUDICIALIZAÇÃO DO DIREITO À SAÚDE: COM A PALAVRA O SUPREMO TRIBUNAL FEDERAL

The article aims to analyze the phenomenon of judicialization of the right to health from the perspective of the decisions rendered by Brazilian courts, especially the Federal Supreme Court (STF), in light of the 1988 Federal Constitution (FC) and the rules governing the Unified Health System (SUS). It aims to analyze the effective access of citizens to the fundamental right to health based on the judicial decisions handed down by Brazilian magistrates in the face of the inertia and ineffectiveness of the state entities responsible for implementing public health policy, without disregarding the division of administrative powers described in the Federal Constitution and in infra-constitutional norms. It also intends to provide an analysis of the phenomenon of judicialization of the right to health and the decisions handed down by the Supreme Court to conclude that these are not obstacles to the effectiveness of public health policy in Brazil. The research was built based on the finding of the need for clarification of the phenomenon (qualitative method). As for the methodology, the study was developed by means of bibliographic and documental research, so that, during the course of this work, case studies related to the decisions handed down by the Supreme Federal Court were carried out based on the specialized literature review. Using the deductive method, it is possible to understand how the effective action of the Judiciary has provided citizens with access to health care, without hindering the implementation of other public policies by the state entities or violating the division of competencies described in the Federal Constitution.

Cohort cholecystectomies in the Brazilian public system: is access to laparoscopy universal after three decades?

videosurgery in Brazil started in 1990 with the performance of laparoscopic cholecystectomy, being included by the public health system in 2008. We evaluated the current situation of the use of this technology in the Unified Health System (SUS - Sistema Único de Saúde). from 2013 to 2019, 1,406,654 patients registered at the SUS Informatics Department (DATASUS) were analyzed to calculate the rate of laparoscopic cholecystectomies (LC) in relation to open cholecystectomies (OC). Patient characteristics, disease presentation and postoperative mortality were evaluated. the LC rate reached 41.5% (growth of 68%) with no decrease in the absolute number of OC. In University Hospitals (UH), the LC rate reached 91.96%. The open technique in emergencies was more associated with male patients, aged 60 years or older, with prolonged hospitalization and in the ICU. Those undergoing LC were less predisposed to postoperative death, both electively (OR 0.49; 95% CI 0.42 - 0.56; NNT=20) and urgently (OR 0.23; 95% CI 0.20 - 0.25; NNT ≅1), providing a protective effect. despite the increase in the indication of LC, the open technique during the years studied remained stable and the most used in the public health system in Brazil. The effectiveness of public health policies to shorten the complete implementation of videosurgery in SUS needs to be investigated in future epidemiological studies, as well as its impact on postoperative morbidity and mortality.

The Impacts of Temporary and Permanent Public Health Policies on HRQOL in a Small Open Economy

Considering that people can invest in their health-related quality of life (HRQOL), we investigate the effects of public health policies (i.e., a health investment subsidy policy and the direct distribution of health-related goods) on HRQOL in a small open economy. We find that when the government makes public investment in HRQOL temporarily, HRQOL deteriorates or does not improve at least. On the contrary, when public investment is enforced permanently, it improves in the long run.

The immediate and subsequent effects of public health interventions for COVID-19 on the leisure and recreation industry.

Public health interventions to combat COVID-19 can be viewed as an exogenous shock to the economy, especially for industries—such as leisure, recreation, and tourism—that rely heavily on human mobility. This study investigates whether and how exactly the economic impact of government public health policies varies over time. Focusing on the leisure and recreation industry, we use data for 131 countries/regions from February to May 2020 and employ generalized difference-in-differences models to investigate the short- and longer-term effects of public health policies. We find that stricter policies lead, on average, to an immediate 9.2–percentage-point drop in leisure and recreation participation. Even so, that industry recovers in about seven weeks after a COVID-19 outbreak in countries/regions that undertake active interventions. After thirteen weeks, leisure and recreation involvement recovers to 70% of pre-pandemic levels in a place that actively intervened but stagnates at about 40% in one that did not.

Age-sex population adjusted analysis of disease severity\xa0in epidemics as a tool to devise public health policies for COVID-19

Governments continue to update social intervention strategies to contain COVID-19 infections. However, investigation of COVID-19 severity indicators across the population might help to design more precise strategies, balancing the need to keep people safe and to reduce the socio-economic burden of generalized restriction precedures. Here, we propose a method for age-sex population-adjusted analysis of disease severity in epidemics that has the advantage to use simple and repeatable variables, which are daily or weekly available. This allows to monitor the effect of public health policies in short term, and to repeat these calculations over time to surveille epidemic dynamics and impact. Our method can help to define a risk-categorization of likeliness to develop a severe COVID-19 disease which requires intensive care or is indicative of a higher risk of dying. Indeed, analysis of suitable open-access COVID-19 data in three European countries indicates that individuals in the 0–40 age interval and females under 60 are significantly less likely to develop a severe condition and die, whereas males equal or above 60 are more likely at risk of severe disease and death. Hence, a combination of age-adaptive and sex-balanced guidelines for social interventions could represent key public health management tools for policymakers.

Epidemiological observations on breaking COVID-19 transmission: from the experience of Taiwan

With almost no community-transmitted cases and without any complete lockdown throughout 2020, Taiwan is one of very few countries worldwide that has recorded minimal impact from the COVID-19 pandemic attack....

Effect of the COVID-19 pandemic first wave and public policy on elective and emergency surgery provision in Southern Queensland.

BackgroundSeveral public health initiatives in Australia were implemented in March 2020 to contain the spread of COVID‐19. The effect of these initiatives on surgical provision is unknown. The primary objective was to determine the effect of public health policies and surgical society guidelines implemented during the pandemic on elective and emergency caseload of surgical specialities operating within South East Queensland.MethodsThis observational study utilized non re‐identifiable electronic data to quantify the caseload of surgical specialities across five secondary and tertiary referral hospitals in South East Queensland prior to and during the implementation of such initiatives. All patients undergoing a surgical procedure between 1 March and 24 April 2019 and the same period in 2020 were included. Participants' demographic and clinical information, such as age, the American Society of Anesthesiologists score, surgical date and location, surgical subspecialty and procedure name, was included.ResultsDuring the 2020 time period, there were 2991 elective cases compared to 4422 surgeries occurring in the same period in 2019 (32.4% reduction). Meanwhile, 2082 emergency surgeries were performed in the 2020 period compared to 2362 in 2019 (12.0% decrease). Ophthalmology and dental/ear, nose and throat/maxillofacial surgery experienced the largest reduction in elective surgeries, whereas emergency caseload increased for vascular and cardiothoracic services, and only slightly decreased for plastics and urology.ConclusionThe public health initiatives and guidance implemented during the COVID‐19 pandemic reduced surgical specialties' elective caseload. However, emergency caseload was not affected to the same extent. This insight helps to guide resource allocation in future waves of the pandemic.

Using a COVID-19 Model in Various Classroom Settings to Assess Effects of Interventions

ABSTRACT The COVID-19 pandemic has made mathematical epidemiology a topic of critical importance, providing mathematics educators with an unparalleled opportunity. This opportunity is accompanied by a challenge: how do mathematics educators, some of whom have little personal experience with mathematical modeling, teach mathematical epidemiology to their students in courses ranging from precalculus to differential equations, and do so in a way that builds understanding of epidemic disease dynamics as well as mathematical methods? We address this issue with a collection of materials that allow students to conduct virtual experiments with a COVID-19 model to assess the effects of public health policies and community behavior. The materials are designed to require only a bare minimum of coding by students so as to focus students' efforts on interpretation of results.

The Impact of Non-Pharmaceutical Interventions on the Second Wave of COVID-19: Insights from an Artificial Intelligence-Based, Cross-Country Study

Objective: To determine the relative influences of various non-pharmaceutical interventions (NPIs) put in place during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave, taking into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. Methods: We first estimate the growth of the first and second wave across countries by fitting a logistic model to reported daily case numbers, up to the first and second epidemic peaks. Using the growth rate, we estimate the basic and effective reproduction number (second wave) Re across countries. Next, we use Random Forest, an “off-the-shelf” machine learning algorithm, to study the association between the growth rate of the second wave of COVID-19 and NPIs as well as pre-existing country characteristics (climatic, environmental, clinical, health, economic, pollution, social, and demographic factors). Lastly, we compare the growth rate of the first and second waves of COVID-19. Findings: Our findings reveal that the mean R0 and Re were respectively 2.02 (S.D 1.09) and 1.07 (S.D. 0.41). R0 has the highest value in Israel (R0 = 6.93) and lowest in Senegal (R0 = 1.13) whereas Re (second wave) had the highest value in Mexico ( Re = 3.08) and lowest in Bangladesh (Re = 1.07). The top three factors associated with the growth of the second wave are body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times regardless of location or presence of other people in some areas, and restrictions on gatherings of 10 people or less. We found a statistically significant difference between the means of the first and second waves. Conclusion: Artificial intelligence techniques can enable scholars as well as public health decision- and policy-makers to estimate the effectiveness of public health policies and mitigation strategies to counteract the toll of the outbreak in terms of infections and deaths, enforcing and implementing “smart” interventions, which are as efficacious as drastic and stringent ones.