data to policy project Program for the Spring 2019 Symposium
Schedule 9:00am 1st Presentation Set e 9:45am 2nd Presentation Set e 10:30 am Casual Poster Viewing I Discussions 11:45 pm Lunch -Student Commons Bldg, Rm 25008 12:00 pm Panel Discussion Transforming Data into Policy in Denver A Community Discussion Jorge Chavez, UCD School of Education and Human Development Miriam Estrada, Mental Health Colorado Jenn Greiving, UCD School of Education and Human Development Ashley Summers, Information Systems Manager at DRCOG The Data to Policy Project Executive Committee thanks everyone for taking part in this important event! Special thanks to this semester's faculty with participating students: ShaharBoneh Steffen Borgwardt Joshua French Jenn Greiving Audrey Hendricks Sheila Huss Serena Kim ) I datatopolicy project And to our graduate research assistant: Melissa Mejia With gratitude, Shea Swauger Mike Ferrara Diane Fritz Matt Mariner AURARIA LIBRARY RaCAS
Titles and Abstracts The projects are listed by their poster location number and color-coded for 1st or 2nd presentation time. Blue: 9:00am I Grey: 9:45am 0 Crime Through a Statistical Lens Daniel Long, Erik Raab &Jeanna Willson â€¢ Square One: A Feasible Shift from Conflict to Cooperation â€¢ We carried out a study to seek out and understand spatial relationships between the occurrence of different types of crimes; namely violent, non-violent, and traffic; in terms of demographics, neighborhood services, and land use in each neighborhood of Denver. This study is in conjunction with the Data to Policy Program purported to engage students with the Denver community via data driven policy research We will present our statistical findings along with policy suggestions. Divergent Social Paths for C-Sections: A Statistical Analysis of Cesarean Delivery Birth Rates Among Mothers From 2014 to 2017, Accounting for State Level Medicaid Expansion under the Patient Protection and Affordable Care Act (ACA) Dennis Wright, II Cesarean section deliveries are correlated with increased risks to health and recovery for mothers and their newborns than vaginal deliveries. In 2014, the Centers for Disease Control and Prevention (CDC) identified a national trend of increasing medically unnecessary (low risk) cesarean rates. In 2015, the World Health Organization (WHO) produced a statement asserting, among other conclusions, a disassociation of maternal and newborn mortality rate reductions for cesarean deliveries above 10% at the population level. Both the CDC and the WHO highlight limited access to care as a barrier to maternal health and associated with higher rates of cesarean deliveries. Using federally-available trend data, I measured state-level low-risk cesarean rates from 2014 through 2017 and compared the rates of change between 2014 and 2017. Further, I compared these rates of change against states that either opted into or out of Medicaid expansion via the ACA. The results indicate that low-risk cesarean delivery rates remain two to three times higher than the recommended WHO threshold. Further, the results highlight a racial disparity with black mothers in both having the highest percentage of cesarean deliveries and being the lone group who has experienced an average increase in cesarean deliveries. Last, Medicaid expansion is positively associated with both an increase in access to health care and more variability in cesarean delivery rates across the United States. Policy implications include increased research and funding to study these cesarean rate disparities, investment into early intervention prenatal services and strengthening the protections under the ACA to prevent a relapse to pre-ACA cesarean delivery rates. â€¢ â€¢ Stephen Ball The peace officer/suspect interaction can be broken down into two categories: Conflict & Cooperation. An examination of the risks and rewards of each category concludes that the incentives for conflict outweigh those of cooperation. Neighborhoods in the city of Denver are the target of this study and through formal inference we find that the total amount of crime, and the rate of crime per capita, are weighted towards neighborhoods with minority percentages above the city average. As a result of these interactions, stakeholders comprise of all Coloradoans; citizens, peace officers, business owners, tax payers, etc. By deriving a policy built around cooperation, the end result is that the neighborhoods containing higher crime by amount and rate are specifically targeted for growth and unity while the stakeholders' benefits are too impressive to ignore. Dispensary Density and Traffic Accidents in Denver Daniel Diorio [Abstract unavailable for program] Cleaning Parks for a Safer Future Connor Mattes & Zachary Sorenson Parks are a place for communities to come together. In fact, several studies have shown that a clean park can help to reduce the crime of the area in and around the park. Our goal is to develop routes to clean parks in Denver. We will create these routes by solving a famous integer program called "The Traveling Salesmen Problem." We plan to implement Christofides' algorithm to find a route for city workers and volunteers to visit and clean our parks in a quick, efficient manner. Cleaner parks will lead to safer neighborhoods around the parks. Park locations and size are pulled from data sets provided on the Data to Policy website. Distances are calculated by using the driving distances between individual parks.
â€¢ Optimizing the patrolling route Dongdong Lu â€¢ The Denver Metro area is administered by a multitude of policing zones and within these policing zones, crime incidents have different distributions. Optimizing the patrolling route for a police car is a strategy which we can apply to improve policing. By analyzing historical crime data, we can identify which locations would benefit the most using optimized patrolling routes. Using graph theory, we model those locations as vertices in a graph. Determining an optimized patrolling route can then be solved as a classical Travelling Salesman Problem. Gentrification and the Elderly: Ensuring Age-Friendly Communities Anne Conklin & Shani O'Brien As the march of gentrification changes the face of urban landscapes throughout the world, the older adult demographic is disproportionally affected by the impacts of the loss of a sense of belonging to a neighborhood and the potential for displacement that can occur during efforts to revitalize older urban areas. It is increasingly important for city planning processes to allow for their needs to be considered and for policies to support aging in place, as statistics show that by 2050 there will be more older adults than children in most countries around the world. This project outlines key characteristics of age friendly cities and communities, reviewing what researchers have found to be important factors in enabling older adults to live out their lives with dignity in safe, supportive environments. We explore the research regarding gentrification and displacement of older adults, as well as how the preservation of heritage and supporting the maintenance of social capital within their neighborhoods may also contribute to positive quality of life for elders . â€¢ Coordinating Response to Fatal Accidents Eric Culver & Christina Ebben Denver Police and Fire Departments have separate dispatch systems that can only track their respective fleets. Because of this, dispatchers rarely have the opportunity to communicate to the other dispatch entity about their deployment decisions. Given that potentially fatal car accidents require a response from both police and fire units, we can better coordinate response to these incidents using a Many-to-One matching problem and the locations of previous fatal car accidents in Denver County. Our results offer a set of "suggested partnerships" of police and fire units given the location of a potentially fatal car crash. Deploying units with a set of "suggested partnerships" can improve the response to accidents; if the unit deployed from one entity is aware of the other's activities, every responder will be better prepared to deal with life threatening emergencies. â€¢ The Influence of Parks on Crime Rates: An Analysis of Denver's Neighborhoods Sarah Martinez, Rebecca Short & Amel Zediri Denver is a city in transformation. The population and demographics of the Denver Metropolitan area have been greatly changing over the past 10 years and is projected to continue growing and changing even more. As the population grows, there is potential to see growing rates of crime in our neighborhoods. With these changes in mind, we sought to examine the relationship between crime rates in neighborhoods in the city of Denver and how these may be affected by public goods the city offers, specifically public parks and playgrounds. The purpose of the research is to implement future policies and strategies in identifying and understanding the variables influencing crime to effectively reduce crime rates in public parks and playgrounds. To study this relationship we tested crime rates for the City of Denver at the Census-Tract level of neighborhoods within Denver over the past 5 years. In our research we analyze our hypothesis that parks have an effect on crime. Through our analisis, our results show that parks are correlated with more crime while playgrounds are correlated with less crime. Crime is a complex issue with multiple contributing factors. To have a broader idea of what is happening in Denver parks we controlled for the presence of police stations, median household income, park acreage, and population within the tract. The data shows crime occurs more frequently in park areas rather than in playgrounds, but the reasoning for this has not fully apparent in our results alone. We recommend that a future study be conducted that dives deeper and examines the types of crimes being committed in these areas and then test whether or not parks are the cause of crime or if they are just a convenient location for crime to take place.
Changing Housing Cost in Colorado and its Effects on Where People with Disabilities Live Leah Wing Denver Metro Program Approved Services Agencies (PASA's) serving people with disabilities have observed a decrease in referrals they are receiving for residents of Denver and have wondered if rent increases within certain areas are forcing people with disabilities to relocate. This study develops and tests hypotheses to identify associations between increased rent and decreased proportions of people with disabilities. Methods included testing four linear regression models using Stata. These models using data from the U.S. census bureau indicate that there is a negative correlation between increased rent and proportion of people with disabilities and in poverty in Colorado between 2012 and 2017. This means that the proportion of people with disabilities and in poverty decreased in census tracts with higher rent increases. Expectations were that the same correlation would exist between people with disabilities who were not in poverty and increased rent, but that indicates a positive correlation, though not statistically significant. Future data analysis should be done on an individual basis to identify where people with disabilities and in poverty are relocating to, such as institutions, homes of parents or caregivers or other areas outside of their previous geographical location. Investing in Denver's Kids: A Spatial Analysis of Affordable Housing and Afterschool Programs Emily Nilsen Both afterschool programming and affordable housing continue to be effective resources for low-income children. Through the creation of a one mile radius around each affordable housing complex in Denver and a spatial analysis of the amount of afterschool programs within the buffered area, this research was able to identify correlative trends concerning the amount of afterschool programs and independent demographic variables such as density of units and number of children within specific age ranges. Furthermore, five specific affordable housing projects with a deficit of afterschool programs in a one mile radius are identified and suggested as areas of investment for afterschool program providers. Parks and Public Health Kaitlin Prichard, Sun eel Raza & Jimmy Reed As the public health of Americans continues to decline we found it important to explore possible public policy opportunities that could be implemented to increase the wellbeing of our communities. While there is extensive research that exists focusing on increasing public health in urban areas, we dug into this issue by examining the importance of park space in Denver neighborhoods and how it relates to public health. Specifically, we showed how the number of park acres in a neighborhood could impact the diabetes rates within that neighborhood. We included a number of other variables including park features, safety features, lifestyle features, and median home values to gain a full understanding of each individual neighborhood and their socio-economic tendencies. We utilized existing datasets from the D2P Data Guide including descriptive variables for neighborhoods to accompany crime collated by Auraria Library with data from the City and County of Denver, neighborhood demographic data collected by the American Community survey from the City and County of Denver and age adjusted rate of diabetes-related hospital discharges and impatient hospitalizations per 100,000 persons from the Colorado Department of Public Health and Environment. As we predicted, we found a negative correlation between park acres and instances of diabetes. This confirms our alternative hypothesis. We also concluded that home value has a strong negative relationship with the diabetes-related discharges from hospitals. Based on these results, the urban metropolitan areas should increase the number of park acres in each of their neighborhoods, starting with the less affluent. In doing so, they would dramatically increase the public health of the city's residents.
Unintended consequences: Giffords gun control ranking as a predictor of increasing inequities in mental health status of people shot by police Kate Fitch This research seeks to describe a disparity in average threat levels of people killed by police who did and did not present signs of mental illness when they were killed. Further, it seeks to describe the relationship between 3 interventions Crisis Intervention Team (CIT) training, mental health court, and gun control policy and this disparity. Methods: An independent samples t-test was performed to test for a difference of mean threat level of people with and without signs of mental illness who were killed by police between 2015 and 2019. CIT, mental health court, and relative strictness of gun control policy measured by Giffords gun policy rank were tested for correlation with difference of mean threat level across so states. The only correlated intervention, gun control policy, was further tested in a multiple linear regression while controlling for other factors. Results: The results show a significant difference in mean threat level of people with and without signs of mental illness who were shot by police. The results showed that, of the three tested interventions, only gun control policy was correlated with a change in this difference between states. Gun control policy, measured by Giffords rank, had a small, but significant, linear relationship with a widening difference of mean threat level. Further analysis showed that the main contribution to this widening difference was a reduction in mean threat level of people with signs of mental illness. Implications: Gun control policy often targets people with mental health conditions and an unintended consequence of this phenomenon is demonstrated in this research. Stricter gun control policy seems to predict a worsening disparity in the conditions under which people showing signs of mental illness are killed by police. â€¢ Housing in Denver: affordable for all? Neissrien Alhubieshi The ability to have housing is a basic need for every person. The problem of affordable housing can be a difficult one, especially for a growing city like Denver. Affordable housing can be defined as housing which is considered affordable to those with a median household income or below. In this study, we consider affordable housing patterns associated with 79 neighborhoods in the city of Denver. We will construct a linear model that considers factors related to income, age, gender, race, education, commute time, and the structure was built in order to identify the factors that are most related to an increased rate of affordable housing. We conclude by discussing policies that could be used to reduce the problem of affordable housing based on our findings. Rent Burdening: A Growing Concern Lauren Hearn The lack of affordable housing can have many impacts including homelessness and the ability to build a future. A notable cause for the lack of affordable housing is "rent burdening", commonly defined as the percentage of income spent on rent being greater than 30%. In this study, we consider rent burdening patterns associated with 79 neighborhoods in the city of Denver. Using a linear regression model, we will explore factors related to housing availability/supply, median income, cost of living, total population living in poverty, etc., in order to identify which factors could be related to rent burdening. We will conclude by discussing potential policies that could be used to reduce the problem of rent burdening, and thus the unintended effects mentioned above, based on our statistical findings. Identifying Factors that Contribute to the percentage of people's income spent on housing in the Denver Area Negar Janani Welfare and comfort are the natural rights of human beings. Balancing income and expenses always engages people's mind especially when they are required to spend the main part of their income on rent and housing. Affordable housing crisis compels people to sacrifice some of their desires and postpone some of them to future since housing expenses swallows a great amount of their income every month. In this study, we consider spatial patterns may affect the percentage of people's income spent on housing among 79 neighborhoods in the city of Denver. We will construct a linear model that considers factors related to income, rent, education, the value of house, and race in order to identify the factors that are most related to the amount of money people spend on housing. We conclude by discussing policies that could be used to reduce the percentage of people's income spend on housing based on our findings. â€¢ Examining Proportions of Income Spent on Rent Max McGrath High rent costs place individuals and families under incredible financial and mental stress. As rent costs rise disproportionately to income, households are paying increasing portions of their income on rent leaving little left over for other necessities and discretionary spending. In this study, we consider rent costs as a proportion of household income within each neighborhood in Denver. We will use a linear model that includes factors related to the racial makeup, housing availability, economic status, age demographics, and commute times within the Denver neighborhoods to identify factors most correlated with higher proportions of income spent on rent. We conclude by suggesting polices based on our findings that could alleviate rent burden for the most affected populations.
â€¢ Unaffordable Housing: An Analysis of Rental Prices in Denver Jessica Murphy Affordable housing is a problem now more than ever in Denver as the population continues to grow rapidly. The demand for housing far outweighs the supply, significantly increasing rental prices. In this study, I aim to determine which factors have the biggest effect on rent in 77 Denver neighborhoods. The study considers aspects such as age, race, education, crime, poverty, vacancy, home value, foreclosures, and public services. I will construct a linear model that includes the factors most related to rent and test to see which of these factors are most significant. Based on these results, I will discuss policies that could be used to reduce rental prices and make Denver more affordable. Affordable housing issues in Denver Pitshou Nzazi Duki Housing affordability is a crucial problem facing many cities in the United States. Concerns about affordable housing can influence many decisions people make, such as how much they spend, the place where they live, and what housing unit to rent or buy. In this study, we consider spatial patterns associated with affordable housing issues among 78 neighborhoods in the city of Denver. We will construct linear models that considers factors related to income, education, age range, and type of infrastructure built in order to identify the factors that are most related to influence house renting and home values. We conclude by discussing policies that could be used for housing afford ability in the city of Denver. Modeling and Understanding Variables Influencing Proportion of Denver Residents Spending At Least 30% of Monthly Income on Housing Alexandra Rotondo Recently, Denver has seen a sharp increase in rent and housing costs while wages remain relatively constant. This has a number of far-reaching effects including an increase in foreclosures, individuals and families being priced out of their homes, and most notably a greater proportion of residents spending at least 30% of their monthly income on housing costs. Essentially, this results in highly unstable housing patters in Denver neighborhoods. This project aims to create a linear model for the proportion of neighborhood residents spending over 30% of their monthly income on housing. The ultimate goal of this model is to better understand what groups of residents are most heavily affected by the housing changes and what factors most profoundly influence the proportion of residents spending over 30% of their monthly income on housing. Upon solidifying and verifying the findings from the model, this project will conclude by making policy recommendations to help create sustainable housing patterns for the future. The focus of the policy recommendations of this project will be the distribution of funds for housing subsidization to ensure that groups of residents disproportionately affected by rising housing prices are given adequate support. â€¢ Affordable Housing vs Neighborhood Characteristics: A Regression Analysis of Denver's Neighborhood Characteristics and Monthly Housing Payments Joryn Anderson, Jamie Longenecker, Gregory Matesi & Christopher Taylor Affordable housing is a concern for many people. Many factors relate to affordability. This research presents a regression model analyzing the relationship between monthly housing payments and other neighborhood characteristics in Denver. More specifically, this study regresses the amount of monthly income spent on housing against several variables such as: the number of non-family households per neighborhood, median earnings based on education, the poverty rate, etc. This research utilizes linear regression methods and accounts for col linearity among regressors. A few well-known tests of model efficacy were used when building this model, including Mallow's Cp, AIC/BIC, Adjusted R2 , and RMSE/MSE. The goal of this study is to assess and compare the relationships between the abovementioned variables and monthly housing payments across Denver neighborhoods. The data used in this analysis is taken directly from the Data2Policy Project website and compiled at the neighborhood level. After analyzing the results of the study, some potential policy directions may be proposed relating to affordable housing. The effect of factors on house value Yu Lan, Tianqi Liu, Qiuchi Shan & Xinyi Wang Houses are necessities of life. Overburdened housing prices can lead to many problems. People have to reduce other living expenses to pay high housing prices and reduce people's quality of life. To figure out the factors associated with house value, we will construct a linear model which include education level, income, races, crimes, population and house unit amount, collected from 79 neighborhood in Denver, using house value as response. Finally, use the result of our study to support relative policies which can affect factors associated with housing prices, and then solve people's housing problems. Let Housing Be Affordable Again: What Affects the Rental Housing Price in The City of Denver? Dongrui Han, Jiayun Liu, Jiewei Ruan & Xinyi Yang Residents in Denver are struggling to find affordable housing. Accommodations at reasonable prices are necessities for people, as they contribute to the welfare of the whole society. Hence, we decided to explore what factors would influence the rental housing prices. In this project, a linear model will be constructed with predictors related to income, race, crimes, public services, marriage and the number of children in a household. The data of 78 neighborhoods in the city of Denver was collected and will be processed in this model. The ultimate goal is to identify the variables that affect the rental housing prices the most, and policy recommendation will be generated based on the results.
â€¢ Availability of Affordable Housing: A Quantitative Study of Which Factors Contribute to the Availability of Affordable Housing in Denver Neighborhoods Sarah Janssen, Allison Marshall & Marc Richman This paper analyzes which factors are most influential in determining the availability of affordable housing in various neighborhoods in Denver, Colorado. This is an important question to consider, since lack of affordable housing is an increasingly pervasive issue in the Denver area. Approximately one third of Denver residents currently face unaffordable housing, mostly due to a large increase in housing demand without a corresponding increase in housing supply. Studies have shown that the populations most affected by this problem are the poor, less educated, disabled, and elderly. Not only does this issue directly affect those without affordable housing, but also has negative effects on the community as a whole. Using data collected from the Data to Policy database provided by the Aura ria Library, we investigate a number of factors related to neighborhood demographics, neighborhood characteristics, and community characteristics to determine which ones are associated with the availability of affordable housing. Examples of our variables include the percent of residents in poverty, the percent of residents over 65 years of age, and per capita income. We conclude by discussing policies that could make housing more affordable based on our findings. Significant Variables that Impact Affordable Housing and Public Policy to Address Them ian Arriaga-MacKenzie Denver has experienced a population boom over the past decade which has greatly impacted the cost of living in various ways. Rapidly increasing housing costs play a large part in this, and affect where people live and work. Examining 73 different neighborhoods in Denver across variables relating to crime, education, income and other household and individual statistics, we will look for patterns and trends associated with unaffordable housing, which is paying 30 percent or more of your income toward housing. Using linear regression methods, we will construct a model that identifies factors which are most related to unaffordable housing and present various policies to address these situations. â€¢ â€¢ Correlations and Causes of Poverty in Denver in Relation to Affordable Housing Max Richard I was hoping to find the correlation between poverty rate (the people who need affordable housing the most) and several predictor variables including population, sex, age, commute length, total housing units, vacant houses, rented buildings, and gross rent. After testing for collinearity, I reduced it down to age, commute length, total housing units, percent of vacant units, percent of renter owned units, and gross rent as predictors for the poverty rate variable. After adjusting for transformations to insure a linear relationship among all the predictors and the response I hope to have a model showing the correlations between as many or few of the regressors and the response to which I can propose a policy to try to help fix the obvious affordable housing issue in Denver. Short term rentals Impact on Affordability John Godin Short-term rentals have gained popularity in cities causing a strain on public services and the housing stock. In this study I will examine how neighborhoods are impacted by the prominence of these short-term rentals. I hypothesize that neighborhoods with a higher density of short-term rentals will experience an increase in rent prices. In order to see what impact short-term rentals had on the price of rent, controlling for population change, I performed a linear regression using the average gross rent as a dependent variable and amount of short-term rental units per neighborhood as my independent variable. The results showed a positive correlation between rent and short-term rental units. Meaning as more short-term rental units arrived in a neighborhood the neighborhood experienced a raise in rent prices. The city of Denver saw the problems the increase of these short-term rentals was causing on neighborhoods and were one of the early cities to adopt regulation on the informal industry. To better understand the formation of the regulations I interviewed with Ashley Kilroy the head of Denver's department of excise and licenses. The current regulation states a homeowner must obtain a license to operate a short-term rental and that must be their primary residence. Concluding this study, I recommend that Denver increase the lodging and set an amount of days a unit could be rented out during the year. The Future of Juvenile Justice University of Colorado Denver in Colorado CRJU 4430/5005 The goal of this project was to evaluate the current state of juvenile justice and its effectiveness-paying significant attention to the issues of mental health and substance abuse. By reviewing literature published over the past 20 years, interviewing community stakeholders, and conducting a policy analysis, we identified programs currently in the juvenile system, as well as policies and implementation recommendations that could better serve youth in the juvenile justice system.