scholarly journals Views of City, County, and State Policy Makers About Childhood Obesity in New York State, 2010–2011

2013 ◽  
Vol 10 ◽  
Author(s):  
Rebecca Robbins ◽  
Jeff Niederdeppe ◽  
Helen Lundell ◽  
Jamie Meyerson
Keyword(s):  
New York ◽  
Childhood Obesity ◽  
State Policy ◽  
New York State ◽  
Policy Makers ◽  
York State

Shooting the Moon: Should states require the H1N1 vaccine for healthcare workers?

2009 ◽  
Vol 7 (6) ◽  
pp. 11
Author(s):  
Paris Nourmohammadi, JD ◽  
Brigid Ryan, JD
Keyword(s):  
New York ◽  
Healthcare Workers ◽  
New York State ◽  
Mitigation Strategies ◽  
World Health ◽  
Health Departments ◽  
State Health ◽  
H1n1 Vaccine ◽  
Policy Makers ◽  
York State

On June 11, 2009, the director of the World Health Organization (WHO) raised the phase of alert in the Global Influenza Plan from level five to level six. The cause for this was the H1N1 virus which had already affected several countries. A level five alert is declared when more than one country in a single WHO geographic region is affected by the same virus. A level six declaration means that community outbreaks are occurring in at least two WHO geographic regions. Once such a declaration is made, little time remains before mitigation efforts must be planned and communicated to the public. In the wake of the WHO declaration, policy makers are clamoring for adequate disease mitigation strategies. Some health departments intend to require employees to wear personal protective equipment while on the job. Other state health departments are encouraging employees to stay home sick if they think they might have the flu. The New York State Health Department has issued an order requiring all healthcare workers to be vaccinated for H1N1 or risk being terminated. This article will explore the New York State policy and make recommendations to policy makers about how to prevent the spread of H1N1.

Public Reactions to the New York State Policy on Flavored E-Cigarettes on Twitter: Observational Study (Preprint)

2020 ◽  
Author(s):  
Li Sun ◽  
Xinyi Lu ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
New York ◽  
Sentiment Analysis ◽  
State Policy ◽  
Topic Modeling ◽  
Electronic Cigarettes ◽  
Public Attitudes ◽  
New York State ◽  
York State ◽  
Before And After ◽  
Twitter Users

BACKGROUND Flavored electronic cigarettes (e-cigarettes) have become popular in recent years, especially among youth and young adults. To address the epidemic of e-cigarettes, New York State approved a ban on sales of most flavored vaping products other than tobacco and menthol flavors on September 17, 2019. OBJECTIVE This study aimed to examine the public responses on social media to the policy on flavored e-cigarettes in New York State. METHODS Twitter posts (tweets) related to e-cigarettes and the New York State policy on flavored e-cigarettes were collected using Twitter streaming API from June 2019 to December 2019. Tweets from New York State, and other states that did not have a flavored e-cigarettes policy were extracted. Sentiment analysis was applied to analyze the proportion of negative and positive tweets about e-cigarettes or the flavor policy. Topic modeling was applied to e-cigarettes related datasets to identify the most frequent topics before and after the announcement of the New York State policy on flavored e-cigarettes. RESULTS Our results showed that average number of tweets related to e-cigarettes and the New York State policy on flavored e-cigarettes increased in both New York State and other states after the NY flavor policy was announced. Sentiment analysis revealed that after the announcement of the New York State flavor policy, in both New York State and other states, the proportion of negative tweets on e-cigarettes increased, from 34.07% to 44.58% and from 32.48% to 44.40% respectively, while positive tweets decreased significantly, from 39.03% to 32.86% and from 42.78% to 33.93% respectively. The majority of tweets about the New York State flavor policy were negative in both New York State (from 88.78% to 83.46%) and other states (from 78.43% to 81.54%) while New York State had a higher proportion of negative tweets than other states. Topic modeling results demonstrated that teenage vaping and health problems were the most discussed topic associated with e-cigarettes. CONCLUSIONS Public attitudes toward e-cigarettes became more negative on Twitter after the New York State announced the policy on flavored e-cigarettes. Twitter users in other states that did not have such a policy on flavored e-cigarettes paid close attention to New York State flavor policy. This study provides some valuable information about the potential impact of the flavored e-cigarettes policy in New York State on public attitudes towards the flavored e-cigarettes.

scholarly journals Medical Capacity Shortages Facilitated the Rapid Dissemination of COVID-19 in Wuhan, New York State, and Italy

2021 ◽  
Author(s):  
Yuehao Xu ◽  
Cheng Zhang ◽  
Lixian Qian
Keyword(s):  
New York ◽  
New York State ◽  
The United States ◽  
Policy Makers ◽  
York State ◽  
Proposed Model ◽  
Rapid Dissemination ◽  
City State ◽  
And Control ◽  
The Impact

Abstract Background: During the coronavirus disease 2019 (COVID-19) outbreak, every public health system faced the potential challenge of medical capacity shortages. Infections without timely diagnosis or treatment may facilitate the stealth transmission and spread of the virus. Important as the influence of capacity shortages on the epidemic, it is still unclear how they could intensify the spread of the epidemic qualitatively under different circumstances. Our study aims to throw light on this influence.Methods: Using infection and medical capacity information reported in Wuhan in China, New York State in the United States, and Italy, we developed a dynamic susceptible–exposed–infected–recovered (SEIR) model to estimate the impact of medical capacity shortages during the COVID-19 outbreak at the city, state, and country levels.Results: The proposed model can fit data well (R-square > 0.9). Through sensitivity analysis, we found that doubled capacity would lead to a 39% lower peak infected number in Wuhan. Italy and New York State have similar results.Conclusions: The less shortages in medical capacity, the faster decline in the daily infection numbers and the fewer deaths, and more shortage would lead to steepen infection curve. This study provides a method for estimating potential shortages and explains how they may dynamically facilitate disease spreading during future pandemics such as COVID-19. Based on this, policy makers may figure out some way to explore more medical capacity and control the epidemic better.

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