scholarly journals Injury-related falls from bicycles, skateboards, roller skates, and non-motorized scooters in the United States: 2005 - 2014

2017 ◽  
Vol 4 (1) ◽  
pp. 16
Author(s):  
William Milczarski ◽  
Peter Tuckel ◽  
Richard Maisel
Keyword(s):  
Public Health ◽  
New York ◽  
Negative Binomial ◽  
Local Level ◽  
Specific Treatment ◽  
Negative Binomial Regression ◽  
The United States ◽  
Treatment Modalities ◽  
Public Health Officials ◽  
National Databases

Purpose: To provide an updated and comparative analysis of injury-related falls from bicycles, skateboards, roller skates and non-motorized scooters.Methods: The study uses two national databases – the Nationwide Emergency Department Sample and the Nationwide Inpatient Sample  – and subnational databases for New York, California, and Maryland.  Univariate and multivariate analyses (negative binomial regression) are performed to identify effects of age, gender, racial-ethnic background, and region on the incidence of injury-related falls from each of the four devices.Results: The rate of injuries due to falls from bicycles far surpasses the rates due to falls from the other devices.  When a measure of “exposure” is taken into consideration, however, the rate of injuries from skateboards outstrips the rates from bicycles or roller skates.  The profile of patients who are injured from falls from each of the four devices is distinctive.  Asian-Americans are greatly underrepresented among those who suffer a fall-related injury from any of the four devices.  The incidence of injuries attributable to falls varies considerably by geographic region.Conclusions: Public health officials need to be mindful that while certain activities such as scootering might be gaining in popularity, the number of injuries sustained from bicycles still dwarfs the number attributable to falls from skateboards, roller skates, and scooters combined.  Thus special attention needs to be paid to both prevent falls from bicycles and specific treatment modalities.  It is important for public health officials to gather injury data at the local level to allocate prevention and treatment resources more efficiently.

Temporal trends in opioid prescribing patterns among oncologists in the Medicare population.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 12022-12022
Author(s):  
Vikram Jairam ◽  
Daniel X. Yang ◽  
Saamir Pasha ◽  
Pamela R. Soulos ◽  
Cary Philip Gross ◽  
...  
Keyword(s):  
New York ◽  
Negative Binomial ◽  
Temporal Trends ◽  
Negative Binomial Regression ◽  
The United States ◽  
Prescribing Patterns ◽  
Part D ◽  
Opioid Prescribing ◽  
Provider Characteristics ◽  
Final Study

12022 Background: In the wake of the United States (U.S.) opioid epidemic, there have been significant governmental and societal efforts to curb opioid prescribing. However, it is unknown whether these efforts have affected prescribing among oncologists, whose patient population often requires narcotics for symptom management. We investigated temporal patterns in opioid prescribing for Medicare patients among oncologists. Methods: We queried the Centers for Medicare and Medicaid Services Part D prescriber dataset to identify independently practicing physicians between January 1, 2013 and December 31, 2017. We used population-averaged multivariable negative binomial regression to estimate the association between time and per-provider opioid prescribing rate, defined as number of opioid claims (original prescriptions and refills) per 100 patients, among oncologists and non-oncologists on both a national and statewide level. All models were adjusted for provider characteristics and annual total patient count per provider. Results: The final study sample included 20,513 oncologists and 711,636 non-oncologists. From 2013 to 2017, the national opioid prescribing rate declined by 19.3% (68.8 to 55.5 opioid prescriptions per 100 patients; P< 0.001) among oncologists and 20.4% (50.7 to 40.3 prescriptions per 100 patients; P< 0.001) among non-oncologists. During this timeframe, 40 U.S. states experienced a significant ( P< 0.05) decrease in opioid prescribing among oncologists, most notably in Vermont (-43.2%), Idaho (-34.5%), and Maine (-32.8%). In comparison, all 50 states exhibited a significant decline ( P< 0.05) in opioid prescribing among non-oncologists. In 5 states, opioid prescribing decreased more among oncologists than non-oncologists, including Oklahoma (-24.6% vs. -7.1%), Idaho (-34.5% vs. -17.8%), Utah (-31.7% vs. -18.7%), Texas (-19.9% vs. -14.7%), and New York (-24.0% vs. -19.7%) (all P< 0.05). Conclusions: Between 2013 and 2017, the opioid prescribing rate decreased by approximately 20% nationwide among both oncologists and non-oncologists. These findings raise concerns about whether opioid prescribing legislation and guidelines intended for the non-cancer population are being applied inappropriately to patients with cancer and survivors.

scholarly journals Landscape of COVID-19 Treatments on Media and Internet Trends: Observational Study (Preprint)

2020 ◽  
Author(s):  
Kacper Niburski ◽  
Oskar Niburski
Keyword(s):  
Public Health ◽  
The United States ◽  
Treatment Modalities ◽  
Press Conference ◽  
White House ◽  
Global Database ◽  
Fox News ◽  
Public Health Officials ◽  
Speech Transcripts ◽  
Unproven Therapies

BACKGROUND Individuals with large followings can influence public opinions and behaviors, especially during a pandemic. In the early days of the pandemic, US president Donald J Trump has endorsed the use of unproven therapies. Subsequently, a death attributed to the wrongful ingestion of a chloroquine-containing compound occurred. OBJECTIVE We investigated Donald J Trump’s speeches, Twitter posts, Google searches and purchases, Amazon purchases, and television airtime for mentions of hydroxychloroquine, chloroquine, azithromycin, and remdesivir. METHODS Twitter sourcing was catalogued with Factba.se, and analytics data, both past and present, were analyzed with Tweet Binder to assess average analytics data on key metrics. Donald J Trump’s time spent discussing unverified treatments on the United States’ 5 largest TV stations was catalogued with the Global Database of Events, Language, and Tone, and his speech transcripts were obtained from White House briefings. Google searches and shopping trends were analyzed with Google Trends. Amazon purchases were assessed using Helium 10 software. RESULTS From March 1 to April 30, 2020, Donald J Trump made 11 tweets about unproven therapies and mentioned these therapies 65 times in White House briefings, especially touting hydroxychloroquine and chloroquine. These tweets had an impression reach of 300% above Donald J Trump’s average. Following these tweets, at least 2% of airtime on conservative networks for treatment modalities like azithromycin and continuous mentions of such treatments were observed on stations like Fox News. Google searches and purchases increased following his first press conference on March 19, 2020, and increased again following his tweets on March 21, 2020. The same is true for medications on Amazon, with purchases for medicine substitutes, such as hydroxychloroquine, increasing by 200%. CONCLUSIONS Individuals in positions of power can sway public purchasing, resulting in undesired effects when the individuals’ claims are unverified. Public health officials must work to dissuade the use of unproven treatments for COVID-19.

scholarly journals Impact of Trump's Promotion of Unproven COVID-19 Treatments on Social Media and Subsequent Internet Trends: Observational Study

10.2196/20044 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e20044
Author(s):  
Kacper Niburski ◽  
Oskar Niburski
Keyword(s):  
Public Health ◽  
The United States ◽  
Treatment Modalities ◽  
Press Conference ◽  
White House ◽  
Global Database ◽  
Fox News ◽  
Public Health Officials ◽  
Speech Transcripts ◽  
Unproven Therapies

Background Individuals with large followings can influence public opinions and behaviors, especially during a pandemic. In the early days of the pandemic, US president Donald J Trump has endorsed the use of unproven therapies. Subsequently, a death attributed to the wrongful ingestion of a chloroquine-containing compound occurred. Objective We investigated Donald J Trump’s speeches and Twitter posts, as well as Google searches and Amazon purchases, and television airtime for mentions of hydroxychloroquine, chloroquine, azithromycin, and remdesivir. Methods Twitter sourcing was catalogued with Factba.se, and analytics data, both past and present, were analyzed with Tweet Binder to assess average analytics data on key metrics. Donald J Trump’s time spent discussing unverified treatments on the United States’ 5 largest TV stations was catalogued with the Global Database of Events, Language, and Tone, and his speech transcripts were obtained from White House briefings. Google searches and shopping trends were analyzed with Google Trends. Amazon purchases were assessed using Helium 10 software. Results From March 1 to April 30, 2020, Donald J Trump made 11 tweets about unproven therapies and mentioned these therapies 65 times in White House briefings, especially touting hydroxychloroquine and chloroquine. These tweets had an impression reach of 300% above Donald J Trump’s average. Following these tweets, at least 2% of airtime on conservative networks for treatment modalities like azithromycin and continuous mentions of such treatments were observed on stations like Fox News. Google searches and purchases increased following his first press conference on March 19, 2020, and increased again following his tweets on March 21, 2020. The same is true for medications on Amazon, with purchases for medicine substitutes, such as hydroxychloroquine, increasing by 200%. Conclusions Individuals in positions of power can sway public purchasing, resulting in undesired effects when the individuals’ claims are unverified. Public health officials must work to dissuade the use of unproven treatments for COVID-19.

scholarly journals The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Fares Qeadan ◽  
Nana Akofua Mensah ◽  
Benjamin Tingey ◽  
Rona Bern ◽  
Tracy Rees ◽  
...  
Keyword(s):  
Public Health ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Mortality Rates ◽  
Negative Binomial Regression Model ◽  
Socioeconomic Indicators ◽  
Opioid Use ◽  
Average Maximum ◽  
Related Mortality

Abstract Background The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. Methods Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). Results After controlling for covariates, counties with higher rates of opioid-related mortality per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P = 0.001). Counties with higher average daily Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. Conclusions This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences.

scholarly journals Super-Spreader Businesses and Risk of COVID-19 Transmission

2020 ◽  
Author(s):  
Ashley O’Donoghue ◽  
Tenzin Dechen ◽  
Whitney Pavlova ◽  
Michael Boals ◽  
Garba Moussa ◽  
...  
Keyword(s):  
New York ◽  
Rhode Island ◽  
Potential Risk ◽  
Negative Binomial ◽  
Risk Index ◽  
Positive Association ◽  
Negative Binomial Regression ◽  
The United States ◽  
Transmission Risk ◽  
Cumulative Number

AbstractPurposeThe United States has the highest number of confirmed COVID-19 cases in the world to date, with over 94,000 COVID-19-related deaths1. The true risk of a COVID-19 resurgence as states prepare to reopen businesses is unknown. This paper aims to classify businesses by their risk of transmission and provide a method to measure traffic and risk at businesses as states reopen in order to quantify the relationship between the density of potential super-spreader businesses and COVID-19 cases.MethodsWe constructed a COVID-19 Business Transmission Risk Index based upon the frequency and duration of visits and square footage of businesses pre-pandemic in 2019 in 8 states (Massachusetts, Rhode Island, Connecticut, New Hampshire, Vermont, Maine, New York, and California). We used this index to classify businesses as potential super-spreaders. Then, we analyzed the association between the density of super-spreader businesses in a county and the rate of COVID-19 cases. We performed significance testing using a negative binomial regression. The main outcome of interest is the cumulative number of COVID-19 cases each week.ResultsWe developed an index to monitor traffic and quantify potential risk at businesses and found a positive association between the density of potential super-spreader businesses and COVID-19 cases. A 1 percentage point increase in the density of super-spreader businesses is associated with 5% higher COVID-19 cases, all else equal.ConclusionHigher densities of potential super-spreader businesses are associated with higher rates of COVID-19 cases. This may have important implications for how states reopen potential super-spreader businesses. Our main contribution is an index that provides a way for policymakers to monitor traffic and potential risk at businesses as states reopen.

Unresolved Issues in Controlling the Tuberculosis Epidemic Among the Foreign-Born in the United States

1996 ◽  
Vol 22 (4) ◽  
pp. 503-536
Author(s):  
Guido S. Weber
Keyword(s):  
Public Health ◽  
The United States ◽  
Laboratory Research ◽  
Treatment Programs ◽  
State Governments ◽  
Foreign Born ◽  
Health Crisis ◽  
Department Of Health ◽  
Public Health Officials ◽  
Year 2000

Tuberculosis (TB), “the world’s most neglected health crisis,” has returned after decades of decline, but has only gradually caught the attention of governments as a formidable threat to public health. By 1984, when TB cases hit an all-time low, federal and state governments stopped supporting the medical infrastructure that once served to contain the disease. State officials around the nation began dismantling laboratory research programs and closing TB clinics and sanitoria. Since 1985, however, TB rates have steadily increased to 26,673 reported cases in 1992, and some have estimated that by the year 2000, there could be a twenty percent increase. By 1993, Congress, realizing that TB could pose a major public health threat, allocated over $100 million to the Department of Health and Human Services for TB prevention and treatment programs. Those funds, however, were sorely needed years before and amounted to only a fraction of what public health officials believe necessary to control TB today.

Bike Count Forecast Model with Multimodal Network Connectivity Measures

2021 ◽  
pp. 036119812110218
Author(s):  
Bingqing Liu ◽  
Divya Bade ◽  
Joseph Y. J. Chow
Keyword(s):  
New York ◽  
Negative Binomial ◽  
Network Connectivity ◽  
Negative Binomial Regression ◽  
Forecast Model ◽  
Negative Binomial Regression Model ◽  
Significance Level ◽  
Commute Time ◽  
Improve Model ◽  
Subway Stations

With the rise of cycling as a mode choice for commuting and short-distance delivery, as well as policy objectives encouraging this trend, bike count models are increasingly critical to transportation planning and investment. Studies have found that network connectivity plays a role in such models, but there remains a lack of measure for the connectivity of a link in a multimodal trip context. This study proposes a connectivity measure that captures the importance of a link in connecting the origins of cyclists and nearby subway stations, and incorporates it in a negative binomial regression model to forecast bike counts at links. Representative bike trips are generated with regard to bike-friendliness using the New York City transit trip planner and used to determine the deviation from the shortest path via the designated link. The measure is shown to improve model fitness with a significance level within 10%. Insights are also drawn for income levels, bike lanes, subway station availability, and average commute time of travelers.

scholarly journals Trends in Opioid Prescribing Among Hemodialysis Patients, 2007–2014

2018 ◽  
Vol 49 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Matthew Daubresse ◽  
G. Caleb Alexander ◽  
Deidra C. Crews ◽  
Dorry L. Segev ◽  
Mara A. McAdams-DeMarco
Keyword(s):  
Low Income ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Incidence Rates ◽  
Opioid Prescription ◽  
Opioid Prescribing ◽  
Hispanic Patients ◽  
Estimate Annual Incidence ◽  
National Trends

Background: Hemodialysis (HD) patients frequently experience pain. Previous studies of HD patients suggest increased opioid prescribing through 2010. It remains unclear if this trend continued after 2010 or declined with national trends. Methods: Longitudinal cohort study of 484,745 HD patients in the United States Renal Data System/Medicare data. We used Poisson/negative binomial regression to estimate annual incidence rates of opioid prescribing between 2007 and 2014. We compared prescribing rates with the general US population using IQVIA’s National Prescription Audit data. Outcomes included the following: percent of HD patients receiving an opioid prescription, rate of opioid prescriptions, quantity, days supply, morphine milligram equivalents (MME) dispensed per 100 person-days, and prescriptions per person. Results: In 2007, 62.4% of HD patients received an opioid prescription. This increased to 63.2% in 2010 then declined to 53.7% by 2014. Opioid quantity peaked in 2011 at 73.5 pills per 100 person-days and declined to 62.6 pills per 100 person-days in 2014. MME peaked between 2010 and 2012 then declined through 2014. In 2014, MME rates were 1.8-fold higher among non-Hispanic patients and 1.6-fold higher among low-income patients. HD patients received 3.2-fold more opioid prescriptions per person compared to the general US population and were primarily prescribed oxycodone and hydrocodone. Between 2012 and 2014, HD patients experienced greater declines in opioid prescriptions per person (18.2%) compared to the general US population (7.1%). Conclusion: Opioid prescribing among HD patients declined between 2012 and 2014. However, HD patients continue receiving substantially more opioids than the general US population.

scholarly journals Early introductions and community transmission of SARS-CoV-2 variant B.1.1.7 in the United States

2021 ◽  
Author(s):  
Tara Alpert ◽  
Erica Lasek-Nesselquist ◽  
Anderson F. Brito ◽  
Andrew L. Valesano ◽  
Jessica Rothman ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
New York ◽  
Diagnostic Testing ◽  
The United States ◽  
International Travel ◽  
Health Concern ◽  
Public Health Response ◽  
Community Transmission ◽  
The Uk

SummaryThe emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a national public health concern in the United States because of its increased transmissibility. Over 500 COVID-19 cases associated with this variant have been detected since December 2020, but its local establishment and pathways of spread are relatively unknown. Using travel, genomic, and diagnostic testing data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. New York, which receives the most international travel from the UK, is likely one of the key hubs for introductions and domestic spread. Finally, we provide evidence for increased community transmission in several states. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Improving the Fate of Nursing Homes During the COVID-19 Pandemic: The Need for Policy

2021 ◽  
pp. e1-e3
Author(s):  
R. Tamara Konetzka
Keyword(s):  
Public Health ◽  
United States ◽  
New York ◽  
Nursing Homes ◽  
Long Term Care ◽  
New York Times ◽  
The United States ◽  
Term Care ◽  
Care Facilities

Approximately 40% of all COVID-19 deaths in the United States have been linked to long-term care facilities.1 Early in the pandemic, as the scope of the problem became apparent, the nursing home sector generated significant media attention and public alarm. A New York Times article in mid-April referred to nursing homes as “death pits”2 because of the seemingly uncontrollable spread of the virus through these facilities. This devastation continued during subsequent surges,3 but there is a role for policy to change this trajectory. (Am J Public Health. Published online ahead of print January 28, 2021: e1–e3. https://doi.org/10.2105/AJPH.2020.306107 )

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