scholarly journals Benefits of Paid Sick Leave During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Alison Thompson ◽  
Nathan M. Stall ◽  
Karen B. Born ◽  
Jennifer L. Gibson ◽  
Upton Allen ◽  
...  
Keyword(s):  
Public Health ◽  
Sick Leave ◽  
The United States ◽  
Sickness Benefit ◽  
Model Program ◽  
Health Measures ◽  
Paid Sick Leave ◽  
Sick Leave Policies ◽  
Spread Of Infection ◽  
Staying At Home

Multiple jurisdictions have adopted or adapted paid sick leave policies to reduce the likelihood of employees infected with SARS-CoV-2 presenting to work, which can lead to the spread of infection in workplaces. During the COVID-19 pandemic, paid sick leave has been associated with an increased likelihood of workers staying at home when symptomatic. Paid sick leave can support essential workers in following public health measures. This includes paid time off for essential workers when they are sick, have been exposed, need to self-isolate, need time off to get tested, when it is their turn to get vaccinated, and when their workplace closes due to an outbreak. In the United States, the introduction of a temporary paid sick leave, resulted in an estimated 50% reduction in the number of COVID-19 cases per state per day. The existing Canada Recovery Sickness Benefit (CRSB) cannot financially protect essential workers in following all public health measures, places the administrative burden of applying for the benefit on essential workers, and neither provides sufficient, nor timely payments. Table 1 lists the characteristics of a model paid sick leave program as compared with the CRSB. Implementation of the model program should be done in a way that is easy to navigate and quick for employers.

Educating Restaurant Workers About Paid Sick Leave: A Pilot Study From New York City

2018 ◽  
Vol 28 (2) ◽  
pp. 358-377
Author(s):  
Emma K. Tsui ◽  
Madeline Duffy ◽  
Sherry Baron
Keyword(s):  
New York ◽  
New York City ◽  
Sick Leave ◽  
York City ◽  
The United States ◽  
Lessons Learned ◽  
Coalition Building ◽  
The Public ◽  
Paid Sick Leave ◽  
Sick Leave Policies

Across the United States, cities, states, and counties are rapidly adopting paid sick leave laws. Paid sick leave policies for restaurant workers may be particularly beneficial, since these workers are less likely to have these benefits and have the potential to spread infection through food-handling and engagement with the public. In order for paid sick leave laws to work, workers and employers must be educated about these laws broadly and effectively. Focusing on New York City, we conducted a pilot research using key stakeholder interviews to learn about New York City’s successes and challenges in educating workers and businesses about the law. Our findings indicate several lessons learned, including allocating sufficient funding, combined use of coalition building and organizing models, and attention to the needs of immigrant restaurant workers. Findings also suggest that greater attention should be paid to proactively addressing workplace organization and practices that thwart paid sick leave use.

scholarly journals Engagement with COVID-19 Public Health Measures in the United States: A Cross-Sectional Social Media Analysis from June to November 2020 (Preprint)

2020 ◽  
Author(s):  
Daisy Massey ◽  
Chenxi Huang ◽  
Yuan Lu ◽  
Alina Cohen ◽  
Yahel Oren ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Language Processing ◽  
Daily Life ◽  
The United States ◽  
Media Analysis ◽  
Prevention Measures ◽  
Cross Sectional ◽  
Health Measures ◽  
The Us

BACKGROUND The coronavirus disease 2019 (COVID-19) has continued to spread in the US and globally. Closely monitoring public engagement and perception of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE To measure the public’s behaviors and perceptions regarding COVID-19 and its daily life effects during the recent 5 months of the pandemic. METHODS Natural language processing (NLP) algorithms were used to identify COVID-19 related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged, and sensitivity and specificity were both calculated to validate the classification of posts. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the US. RESULTS The final sample size included 9,065,733 posts, 70% of which were sourced from the US. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the US beginning in October. Additionally, counter to reports from March and April, discussion was more focused on daily life topics (69%), compared with COVID-19 in general (37%) and COVID-19 public health measures (20%). CONCLUSIONS There was a decline in COVID-19-related social media discussion sourced mainly from the US, even as COVID-19 cases in the US have increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures until a vaccine is widely available to the public.

Public Health and the Law

2012 ◽  
Vol 40 (3) ◽  
pp. 690-695 ◽  
Author(s):  
James G. Hodge ◽  
Lexi C. White ◽  
Andrew Sniegowski
Keyword(s):  
Public Health ◽  
The United States ◽  
Public And Private ◽  
Health Measures ◽  
Public Health Officials ◽  
Key Issues ◽  
Structural Principles ◽  
Laws And Policies ◽  
Private Actors

Promoting and protecting the public's health in the United States and abroad are intricately tied to laws and policies. Laws provide support for public health measures, authorize specific actions among public and private actors, and empower public health officials. Laws can also inhibit or restrict efforts designed to improve communal health through protections for individual rights or structural principles of government. Advancing the health of populations through law is complex and subject to constant tradeoffs. This column seeks to explore the role of law in the interests of public health through scholarly and applied assessments across a spectrum of key issues. The first of these assessments focuses on a critical topic in emergency legal preparedness.

scholarly journals Policy liberalism and source of news predict pandemic-related health behaviors and trust in the scientific community

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252670
Author(s):  
Madeleine Reinhardt ◽  
Matthew B. Findley ◽  
Renee A. Countryman
Keyword(s):  
Public Health ◽  
United States ◽  
Health Behaviors ◽  
News Media ◽  
Perceived Risk ◽  
Scientific Community ◽  
The United States ◽  
World Health ◽  
Health Crisis ◽  
Health Measures

In March of 2020, the United States was confronted with a major public health crisis caused by the coronavirus disease (COVID-19). This study aimed to identify what factors influence adherence to recently implemented public health measures such as mask-wearing and social distancing, trust of scientific organizations like the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) on information pertaining to the pandemic, and level of perceived risk. Data were collected from June 30, 2020 to July 22, 2020 on 951 adult residents of the United States using an online survey through Microsoft Forms. Multiple linear regression was used to identify the strongest predictors for compliance to pandemic-related health measures, trust in the scientific community, and perceived risk. Results showed that the strongest predictor of all variables of interest was degree of policy liberalism. Additionally, participants who consumed more conservative news media conformed less to the pandemic health guidelines and had less trust in the scientific community. Degree of policy liberalism was found to have a significant moderating effect on the relationship between gender and conformity to pandemic-related health behaviors. These findings have concerning implications that factors like degree of policy liberalism and source of news are more influential in predicting adherence to life-saving health measures than established risk factors like pre-existing health conditions.

scholarly journals Quantifying the effect of quarantine control in Covid-19 infectious spread using machine learning

2020 ◽  
Author(s):  
Raj Dandekar ◽  
George Barbastathis
Keyword(s):  
Neural Network ◽  
South Korea ◽  
The United States ◽  
Government Interventions ◽  
Infected Case ◽  
Health Measures ◽  
Case Count ◽  
The Us ◽  
Spread Of Infection ◽  
Limited Testing

Since the first recording of what we now call Covid-19 infection in Wuhan, Hubei province, China on Dec 31, 2019 (CHP 2020), the disease has spread worldwide and met with a wide variety of social distancing and quarantine policies. The effectiveness of these responses is notoriously difficult to quantify as individuals travel, violate policies deliberately or inadvertently, and infect others without themselves being detected (Li et al. 2020a; Wu & Leung 2020; Wang et al. 2020; Chinazzi et al. 2020; Ferguson et al. 2020; Kraemer et al. 2020). Moreover, the publicly available data on infection rates are themselves unreliable due to limited testing and even possibly under-reporting (Li et al. 2020b). In this paper, we attempt to interpret and extrapolate from publicly available data using a mixed first-principles epidemiological equations and data-driven neural network model. Leveraging our neural network augmented model, we focus our analysis on four locales: Wuhan, Italy, South Korea and the United States of America, and compare the role played by the quarantine and isolation measures in each of these countries in controlling the effective reproduction number Rt of the virus. Our results unequivocally indicate that the countries in which rapid government interventions and strict public health measures for quarantine and isolation were implemented were successful in halting the spread of infection and prevent it from exploding exponentially. In the case of Wuhan especially, where the available data were earliest available, we have been able to test the predicting ability of our model by training it from data in the January 24th till March 3rd window, and then matching the predictions up to April 1st. Even for Italy and South Korea, we have a buffer window of one week (25 March - 1 April) to validate the predictions of our model. In the case of the US, our model captures well the current infected curve growth and predicts a halting of infection spread by 20 April 2020. We further demonstrate that relaxing or reversing quarantine measures right now will lead to an exponential explosion in the infected case count, thus nullifying the role played by all measures implemented in the US since mid March 2020.

scholarly journals A Social Network Model of the COVID-19 Pandemic

2020 ◽  
Author(s):  
Pei Jun Zhao
Keyword(s):  
Public Health ◽  
United States ◽  
Social Distance ◽  
The United States ◽  
Viral Transmission ◽  
Model Parameters ◽  
Weighted Graphs ◽  
The Public ◽  
Health Measures ◽  
The U.S

AbstractIn the COVID-19 coronavirus pandemic, currently vaccines and specific anti-viral treatment are not yet available. Thus, preventing viral transmission by case isolation, quarantine, and social distancing is essential to slowing its spread. Here we model social networks using weighted graphs, where vertices represent individuals and edges represent contact. As public health measures are implemented, connectivity in the graph decreases, resulting in lower effective reproductive numbers, and reduced viral transmission. For COVID-19, model parameters were derived from the coronavirus epidemic in China, validated by epidemic data in Italy, then applied to the United States. We calculate that, in the U.S., the public is able to contain viral transmission by limiting the average number of contacts per person to less than 7 unique individuals over each 5 day period. This increases the average social distance between individuals to 10 degrees of separation.

Is the Unequal COVID-19 Burden in Canada Due to Unequal Levels of Citizens’ Discipline Across Provinces?

2020 ◽  
Vol COVID-19 ◽  
Author(s):  
Jean-François Daoust ◽  
Éric Bélanger ◽  
Ruth Dassonneville ◽  
Erick Lachapelle ◽  
Richard Nadeau
Keyword(s):  
Public Health ◽  
Health Outcomes ◽  
Empirical Test ◽  
First Year ◽  
Public Officials ◽  
Health Measures ◽  
Health Agencies ◽  
Canadian Provinces ◽  
Spread Of Infection

The unequal burden from the COVID-19 crisis (e.g., in terms of infection and death rates) across Canadian provinces is important and puzzling. Some have speculated that differences in levels of citizen compliance with public health preventive measures are central to understanding cross-provincial differences in pandemic-related health outcomes. However, there has been no systematic empirical test of this hypothesis. In this research, we make use of an exceptionally large dataset including 23 survey waves (N=22,610) fielded in Canada across twelve months (April 2020 to April 2021) to answer the question: is there evidence of substantial cross-provincial differences in citizen compliance with basic public health measures designed to prevent the spread of infection? We find that regional differences in self-reported behaviour are few and very modest, suggesting that inter-provincial differences in COVID-19 related health outcomes have little to do with differences in citizen compliance, at least in the first year of the pandemic. These results have important implications. While it is crucial that we continue to study regional variations related to the COVID-19 burden, public officials from health agencies, pundits and politicians should be cautious when musing about the role of citizen compliance as the primary explanation of inter-provincial pandemic health outcomes.

scholarly journals The Effect of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Mitigation Strategies on Seasonal Respiratory Viruses: A Tale of 2 Large Metropolitan Centers in the United States

2020 ◽  
Author(s):  
Amy C Sherman ◽  
Ahmed Babiker ◽  
Andrew J Sieben ◽  
Alexander Pyden ◽  
James Steinberg ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Severe Acute Respiratory Syndrome ◽  
The United States ◽  
Respiratory Viruses ◽  
Mitigation Strategies ◽  
The Public ◽  
Health Measures ◽  
Reproductive Rates ◽  
The Impact

Abstract To assess the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on seasonal respiratory viruses, absolute case counts and viral reproductive rates from 2019–2020 were compared against previous seasons. Our findings suggest that the public health measures implemented to reduce SARS-CoV-2 transmission significantly reduced the transmission of other respiratory viruses.

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