scholarly journals Geographic Distribution of Foot and Ankle Orthopaedic Surgeons Throughout the United States

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0008
Author(s):  
Hui Zhang ◽  
Matthew G. Fanelli ◽  
Coleman Cush ◽  
Benjamin Wagner ◽  
Louis C. Grandizio ◽  
...  
Keyword(s):  
Geographic Distribution ◽  
Pearson Correlation ◽  
Negative Relationship ◽  
The United States ◽  
Economic Factors ◽  
Foot And Ankle ◽  
Congressional District ◽  
Poverty Level ◽  
Congressional Districts ◽  
The Us

Category: Other Introduction/Purpose: Orthopaedic Surgery has become increasingly subspecialized since fellowships were established in the 1970s. Previous investigations within hand and urologic surgery have demonstrated an uneven geographic distribution within these subspecialties. Economic factors can influence surgeon distribution within a particular geographic region. At present, the geographic distribution of orthopaedic foot and ankle (OFA) surgeons in the US is poorly defined. The purpose of this investigation is to determine the geographic distribution of OFA surgeons in the US. We hypothesize that there will be substantial differences in OFA surgeon density throughout the US and that economic factors may play a role in access to subspecialty OFA care. Methods: A current membership list was obtained from the American Orthopaedic Foot & Ankle Society (AOFAS). Active AOFAS members were categorized relative to states and US House of Representatives Congressional Districts. Using publicly available census data, we recorded the population within each state and district as well as the percentage of families and people with income below the federally defined poverty level. Descriptive statistics were utilized for demographic information. The relationship between income level and the number of surgeons was determined using a Pearson correlation. These data were used to generate OFA surgeons per capita at a state and congressional district level. This information was also used to generate choropleth maps comparing surgeon density and poverty. Results: We identified a list of 1,103 active AOFAS members with 1,311 practice addresses. There was an average of 21.2 OFA surgeons per state. There was an average of 0.38 and 0.40 OFA surgeons per 100,000 people in each state and congressional district respectively. The District of Columbia, VT, WY, and NE had the highest OFA surgeon density. WV, KY, NM, RI had the lowest density. 75 congressional districts had no OFA surgeons. There was a statistically significant negative relationship demonstrating that regions with higher levels of poverty had fewer OFA surgeons, with a Pearson correlation coefficient of -0.14, (P-value = 0.008). This relationship is further illustrated in Figure 1. Conclusion: There is wide geographic variation of OFA surgeon density throughout the US. Regions with higher levels of poverty have less access to OFA surgeons compared to regions with lower poverty levels. Understanding these trends may aid in developing both recruitment and referal strategies for complex foot and ankle care in underserved regions.

scholarly journals Geographic Distribution of Foot and Ankle Orthopedic Surgeons Throughout the United States

2021 ◽  
Vol 6 (2) ◽  
pp. 247301142110035
Author(s):  
Matthew Fanelli ◽  
Coleman Cush ◽  
Hui Zhang ◽  
Benjamin Wagner ◽  
Amanda J. Young ◽  
...  
Keyword(s):  
United States ◽  
Geographic Distribution ◽  
Census Data ◽  
Pearson Correlation ◽  
Negative Relationship ◽  
The United States ◽  
Foot And Ankle ◽  
Congressional District ◽  
Level Of Evidence ◽  
Congressional Districts

Background: At present, the geographic distribution of orthopedic foot and ankle (OFA) surgeons in the United States is poorly defined. The purpose of this investigation is to determine the geographic distribution of OFA surgeons in the United States. We hypothesize that there will be differences in OFA surgeon density throughout the United States and that economic factors may play a role in access to subspecialty OFA care. Methods: A current membership list was obtained from the American Orthopaedic Foot & Ankle Society (AOFAS). Active members were categorized relative to states and US congressional districts, using publicly available census data. The relationship between income and surgeon density was determined using a Pearson correlation. Results: We identified a list of 1103 active AOFAS members. There was an average of 0.38 and 0.40 OFA surgeons per 100 000 people in each state and congressional district, respectively. We found a weak negative relationship demonstrating that regions with higher levels of poverty had fewer OFA surgeons, with a Pearson correlation coefficient of –0.14 (95% CI: –0.24, –0.04), P = .008. Conclusion: There is wide geographic variation of OFA surgeon density throughout the United States. Regions with higher levels of poverty were weakly associated with decreased population density of OFA surgeons compared to regions with lower poverty levels. Understanding these trends may aid in developing both recruitment and referral strategies for complex foot and ankle care in underserved regions. Level of Evidence: Level V.

Silence of the Land: On the Historical Irrelevance of Territory to Congressional Districting and Political Representation in the United States

2001 ◽  
Vol 15 (01) ◽  
pp. 53-87 ◽  
Author(s):  
Andrew Rehfeld
Keyword(s):  
United States ◽  
House Of Representatives ◽  
Political Representation ◽  
The United States ◽  
Representative Government ◽  
Congressional District ◽  
Congressional Districts ◽  
Communities Of Interest

Every ten years, the United States “constructs” itself politically. On a decennial basis, U.S. Congressional districts are quite literally drawn, physically constructing political representation in the House of Representatives on the basis of where one lives. Why does the United States do it this way? What justifies domicile as the sole criteria of constituency construction? These are the questions raised in this article. Contrary to many contemporary understandings of representation at the founding, I argue that there were no principled reasons for using domicile as the method of organizing for political representation. Even in 1787, the Congressional district was expected to be far too large to map onto existing communities of interest. Instead, territory should be understood as forming a habit of mind for the founders, even while it was necessary to achieve other democratic aims of representative government.

Redistricting and Electoral Competition in American Politics

2019 ◽  
Author(s):  
Ryan Williamson
Keyword(s):  
Voting Behavior ◽  
Electoral Competition ◽  
Congressional District ◽  
Incumbency Advantage ◽  
Substantial Impact ◽  
Electoral Success ◽  
Congressional Districts ◽  
The Us ◽  
Us Supreme Court ◽  
The Relationship

Redistricting, or the process of redrawing congressional district boundaries, can be a highly contentious and political affair. Electoral competition within districts is dependent on both of the major American political parties being evenly balanced. Therefore, redistricting can enhance or diminish competition through how it distributes partisans across districts. Indeed, politicians have used this process to manipulate boundaries in their favor for centuries. In fact, the term most commonly used for exploiting the redistricting process for partisan gain—gerrymandering—was coined in 1812 as Massachusetts governor Elbridge Gerry signed legislation creating a map with heavily distorted districts, one of which resembled a salamander. Thus, the portmanteau “gerry-mander” was born. The misshapen districts produced the intended effect of facilitating greater electoral success for members of the governor’s party. Throughout history, Congress, the US Supreme Court, individual states, the American electorate, and an ever-evolving political environment have all impacted the construction of district maps. Additionally, each of these factors further influences the level of electoral competition within the district. Therefore, this work seeks to outline how redistricting can directly or indirectly influence electoral competition within congressional districts. Directly, different redistricting entities (legislatures, commissions, and courts) possess different motivations and constraints when drawing district lines, which can impact competition. Indirectly, redistricting can influence voting behavior and the incumbency advantage, which can also impact competition. This work also explores the tradeoff between representation and competition, the relationship between redistricting and polarization, what constitutes a gerrymander, and how durable redistricting plans are over time. Each can have a substantial impact on electoral competition, which in turn bears consequences for our understanding of the consequences of redistricting.

Geographic distribution of Pythium insidiosum infections in the United States

2021 ◽  
pp. 1-5
Author(s):  
Don Nguyen ◽  
Raquel Vilela ◽  
Bruno M. Miraglia ◽  
Gabriella Vilela ◽  
Noora Jasem-Alali ◽  
...  
Keyword(s):  
Geographic Distribution ◽  
The United States ◽  
Skin Lesions ◽  
Microbial Culture ◽  
Serum Samples ◽  
Pythium Insidiosum ◽  
Southeastern Us ◽  
The Us ◽  
Histologic Evaluation ◽  
Diagnostic Modalities

Abstract OBJECTIVE To describe the geographic distribution of infections caused by Pythium insidiosum in dogs, horses, and other animal species in the US. ANIMALS For the last 20 years, we have collected data from cases of pythiosis in 1,150 horses, 467 dogs, and other species (59) from various geographic locations in the US. PROCEDURES Due to lost data (from 2006 to 2016), the selected cases include years 2000 to 2005 and 2016 to 2020. The selection of cases was based on infected host clinical features, serum samples demonstrating strong positive anti–P insidiosum IgG titers in serologic assays, and positive results on ≥ 1 of the following diagnostic modalities: microbial culture on 2% Sabouraud dextrose agar, histologic evaluation, PCR assay, and wet mount cytologic evaluation (with potassium hydroxide). RESULTS Most confirmed P insidiosum infections were found in horses and dogs in the southeastern US. Interestingly, in Texas, no cases were found west of longitude 100°W. Few pythiosis cases were diagnosed in west-coast states. Equine cases were more often diagnosed during summer and fall months, but canine cases were more often diagnosed between September and February. Cases in other species were discovered in the same geographic areas as those in dogs and horses. CLINICAL RELEVANCE To our knowledge, this is the first report providing the ecological distribution of P insidiosum infection in affected species in the US. Results of this study illustrated the importance of including P insidiosum in the differential diagnostic scheme of nonhealing skin lesions or intestinal granulomatous masses, particularly in dogs and horses inhabiting or having visited endemic areas.

scholarly journals The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level

2021 ◽  
Author(s):  
Shiro Kuriwaki ◽  
Stephen Ansolabehere ◽  
Angelo Dagonel ◽  
Soichiro Yamauchi
Keyword(s):  
Survey Data ◽  
Total Variation ◽  
The United States ◽  
District Level ◽  
Congressional District ◽  
Congressional Districts ◽  
Individual Level ◽  
National Differences ◽  
Racial Polarization ◽  
Hispanic Voters

Voting in the United States has long been known to divide sharply along racial lines, and the degree of racially polarized voting evidently varies across regions, and even within a state. Researchers have further studied variation in racially polarized voting using aggregate data techniques, but these methods assume that variation in individual preferences is not related to geography. This paper presents estimates based on individual level data of the extent and variation in racially polarized voting across US Congressional Districts. Leveraging large, geocoded sample surveys, we develop an improved method for measuring racial voting patterns at the Congressional District-level. The method overcomes challenges in previous attempts of survey modeling by allowing survey data to inform the synthetic population model. This method has sufficient power to provide precise estimates of racial polarization even when survey data are sparse. We find that variation across districts but within states explains roughly 20 percent of the total variation; states explain a further 20 percent of the total variation, and 55 percent of the variation is simply national differences between races. The Deep South still has the highest racial polarization between White and Black voters, but some Midwestern congressional districts exhibit comparably high polarization. The polarization between White and Hispanic voters is far more variable than between Black and White voters.

scholarly journals Air passenger travel and international surveillance data predict spatiotemporal variation in measles importations to the United States

2021 ◽  
Author(s):  
Marya L. Poterek ◽  
Moritz U.G. Kraemer ◽  
Alexander Watts ◽  
Kamran Khan ◽  
T. Alex Perkins
Keyword(s):  
United States ◽  
Measles Virus ◽  
Pearson Correlation ◽  
Area Under The Curve ◽  
The United States ◽  
Air Travel ◽  
Surveillance Data ◽  
Data Type ◽  
The Us ◽  
Imported Cases

AbstractMeasles incidence in the United States has grown dramatically, as vaccination rates are declining and transmission internationally is on the rise. Measles virus is highly infectious and can cause severe symptoms and even death. Because imported cases are necessary drivers of outbreaks in non-endemic settings, predicting measles outbreaks in the US depends on predicting imported cases. To assess the predictability of imported measles cases, we performed a regression of imported measles cases in the US against an inflow variable that combines air travel data with international measles surveillance data. To understand the contribution of each data type to these predictions, we repeated the regression analysis with alternative versions of the inflow variable that replaced each data type with averaged values and with versions of the inflow variable that used modeled inputs. We assessed the performance of these regression models using correlation, coverage probability, and area under the curve statistics, including with resampling and cross-validation. Our regression model had good predictive ability with respect to the presence or absence of imported cases in a given state in a given year (AUC = 0.78) and the magnitude of imported cases (Pearson correlation = 0.84). By comparing alternative versions of the inflow variable averaging over different inputs, we found that both air travel data and international surveillance data contribute to the model’s ability to predict numbers of imported cases, and individually contribute to its ability to predict the presence or absence of imported cases. Predicted sources of imported measles cases varied considerably across years and US states, depending on which countries had high measles activity in a given year. Our results emphasize the importance of the relationship between global connectedness and the spread of measles.

scholarly journals Hotfoot for the Iron Horse

2000 ◽  
Vol 122 (06) ◽  
pp. 46-52
Author(s):  
Henry Baumgartner
Keyword(s):  
United States ◽  
21St Century ◽  
High Speed ◽  
The United States ◽  
Political Support ◽  
Economic Factors ◽  
Department Of Transportation ◽  
Rail System ◽  
The Us ◽  
Rail Service

Attempts are under way to bring US rail service into the 21st century. A range of initiatives that may spark further advances in the US rail system are under way in the United States and abroad. Amtrak’s new Acela Express is scheduled to go into service this summer in the Northeast Corridor. It is expected to achieve a speed of 150 mph. Freshly arrived at Philadelphia’s Penn Coach Yards, the Acela Express power car is unwrapped and inspected. The covering of the nose has been pushed up, revealing the engine underneath. Amtrak, which hopes its new high-speed service will finally nudge it into the black, has ambitious plans to start high-speed services in other areas of the country. The US Department of Transportation has designated several corridors where economic factors and local political support seem to indicate a chance of success.

scholarly journals US Foreign-Born Workers in the Global Pandemic: Essential and Marginalized

2020 ◽  
pp. 231150242095275
Author(s):  
Donald Kerwin* ◽  
Robert Warren*
Keyword(s):  
New York ◽  
Labor Force ◽  
Homeland Security ◽  
New York State ◽  
National Level ◽  
The United States ◽  
Economic Security ◽  
Foreign Born ◽  
Poverty Level ◽  
The Us

This article provides detailed estimates of foreign-born (immigrant) workers in the United States who are employed in “essential critical infrastructure” sectors, as defined by the Cybersecurity and Infrastructure Security Agency (CISA) of the US Department of Homeland Security (DHS) (DHS 2020). Building on earlier work by the Center for Migration Studies (CMS), the article offers exhaustive estimates on essential workers on a national level, by state, for large metropolitan statistical areas (MSAs), and for smaller communities that heavily rely on immigrant labor. It also reports on these workers by job sector; immigration status; eligibility for tax rebates under the Coronavirus Aid, Relief, and Economic Security Act (CARES Act); and other characteristics. It finds that: Sixty-nine percent of all immigrants in the US labor force and 74 percent of undocumented workers are essential workers, compared to 65 percent of the native-born labor force. Seventy percent of refugees and 78 percent of Black refugees are essential workers. In all but eight US states, the foreign-born share of the essential workforce equals or exceeds that of all foreign-born workers, indicating that immigrant essential workers are disproportionately represented in the labor force. The percentage of undocumented essential workers exceeds that of native-born essential workers by nine percentage points in the 15 states with the largest labor force. In the ten largest MSAs, the percentages of undocumented and naturalized essential workers exceed the percentage of native-born essential workers by 12 and 6 percent, respectively. A total of 6.2 million essential workers are not eligible for relief payments under the CARES Act, as well as large numbers of their 3.8 million US citizen children (younger than age 17), including 1.2 million US citizen children living in households below the poverty level. The foreign-born comprise 33 percent of health care workers in New York State, 32 percent in California, 31 percent in New Jersey, 28 percent in Florida, 25 percent in Nevada and Maryland, 24 percent in Hawaii, 23 percent in Massachusetts, and 19 percent in Texas. Section I of the article describes the central policy paradox for foreign-born workers during the COVID-19 pandemic: that they are “essential” at very high rates, but many lack status and they have been marginalized by US immigration and COVID-19-related policies. Section II sets forth the article’s main findings. Section III outlines major policy recommendations.

scholarly journals The Wielding Influence of Political Networks: Representation in Majority-Latino Districts

2017 ◽  
Vol 71 (1) ◽  
pp. 184-198 ◽  
Author(s):  
Angela X. Ocampo
Keyword(s):  
Political Parties ◽  
Interest Groups ◽  
Case Studies ◽  
House Of Representatives ◽  
Congressional District ◽  
Substantive Representation ◽  
Congressional Districts ◽  
Political Networks ◽  
The Us ◽  
Do So

Latino-majority congressional districts are far more likely to elect Latino representatives to Congress than majority-white districts. However, not all majority-Latino districts do so. This paper addresses this question, and it investigates how the level of influence of political parties and interest groups in majority-Latino districts substantially shapes Latino representation to the US House of Representatives. I rely on five case studies and a dataset of candidates to open congressional races with a Latino population plurality from 2004 to 2014. The evidence indicates that groups and political networks are critical for Latina/o candidate recruitment, the organization of resources in a congressional district, the deployment of campaign resources on behalf of certain candidates, and the eventual success of Latina/o candidates. The findings suggest that Latino descriptive and substantive representation are shaped by the wielding influence of political parties and interest groups.

scholarly journals Air Passenger Travel and International Surveillance Data Predict Spatiotemporal Variation in Measles Importations to the United States

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 155
Author(s):  
Marya L. Poterek ◽  
Moritz U. G. Kraemer ◽  
Alexander Watts ◽  
Kamran Khan ◽  
T. Alex Perkins
Keyword(s):  
United States ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
The United States ◽  
Air Travel ◽  
Surveillance Data ◽  
Data Type ◽  
The Us ◽  
Imported Cases

Measles incidence in the United States has grown dramatically, as vaccination rates are declining and transmission internationally is on the rise. Because imported cases are necessary drivers of outbreaks in non-endemic settings, predicting measles outbreaks in the US depends on predicting imported cases. To assess the predictability of imported measles cases, we performed a regression of imported measles cases in the US against an inflow variable that combines air travel data with international measles surveillance data. To understand the contribution of each data type to these predictions, we repeated the regression analysis with alternative versions of the inflow variable that replaced each data type with averaged values and with versions of the inflow variable that used modeled inputs. We assessed the performance of these regression models using correlation, coverage probability, and area under the curve statistics, including with resampling and cross-validation. Our regression model had good predictive ability with respect to the presence or absence of imported cases in a given state in a given year (area under the curve of the receiver operating characteristic curve (AUC) = 0.78) and the magnitude of imported cases (Pearson correlation = 0.84). By comparing alternative versions of the inflow variable averaging over different inputs, we found that both air travel data and international surveillance data contribute to the model’s ability to predict numbers of imported cases and individually contribute to its ability to predict the presence or absence of imported cases. Predicted sources of imported measles cases varied considerably across years and US states, depending on which countries had high measles activity in a given year. Our results emphasize the importance of the relationship between global connectedness and the spread of measles. This study provides a framework for predicting and understanding imported case dynamics that could inform future studies and outbreak prevention efforts.

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