Visualizing data leads to better local decisions | Stephen Sills | TEDxGreensboro

[Music] recently my wife and I visited Peru like all tourists to this South American country we had to go to Machu Picchu high in the Andes it was an amazing city standing at 8,000 feet looking at across this city built over 500 years ago and wondering just how did they do this how did they move granite blocks so I'm weighing over 50 tons around the top of this mountain how did they build to withstand the frequent earthquakes in the region how did they build irrigation systems and aqueducts that are still functioning today my wonder didn't stop there we also visited the South of Peru a small town called Nazca it was my first time in a 8 seat Cessna airplane a dizzying experience as we flew over the Nazca lines these lines are over 2,000 years old they're up to 1/4 mile long and they're made by removing the top surface layer of red pebbles exposing the light clay beneath archaeologists and anthropologists have studied these lines and really have no clear idea what they're all about they represent insects animals humans large abstract geometric figures there's been speculation as varied as alien landing strips giant weaving looms perhaps offerings to water guides the anthropologist and archaeologists have collected a lot of information over the past hundred years systematically studying the Inca in the mountains and the Nazca and the planes they've catalogued the building techniques and materials the ark agricultural techniques the social stratification of the Incan Empire the rituals and rulers and their practices much like the archaeologists and anthropologists I study information and I try to demystify data I try to present information in a in a way that communicates to a broader audience I try to find the meaning behind numbers and understand why people do what they do many of my days are looking at screens like this row upon row of numbers and wondering what's the hidden idea here what what is the the message these numbers might be visits to a hospital an emergency department for respiratory illness they may be people in the community who have a chronic disease such as diabetes or sorry diabetes or other chronic issues it might be housing information such as code enforcement cases evictions by landlords in civil claims courts it may be substandard properties it's hard sometimes to make sense out of these numbers in a way that can communicate to a broader audience of the community of policymakers and the public here's a first attempt to take that same data set and make sense out of it by simply adding color coding to the rows of numbers red for example and our culture means stop bad not good yellow a warning something that's in transition green good in this case we're looking at neighborhoods ranked on the basis of a variety of characteristics such as vacant properties substandard homes number of properties with delinquent tax bills the level of poverty or the amount of crime in the community ranking them based on the value of that neighborhood economically taking that information just a step further and mapping it we begin to see inequalities in our community we can begin to see systemic disinvestment and areas of opportunity for new investment it allows us to rank and prioritize information and begin to align policies that might address some of the social issues within these neighborhoods the Center for Community progress gives several recommendations on what you can do for example in extremely weak markets you might have redevelopment planning or blight elimination plans in a stable market functioning neighborhood you might need tactical code enforcement to tackle just few properties that otherwise will bring down property values and create a weaker market you match this data often with information from municipal sources this for example is tax code information that tells us that some properties are delinquent on their taxes and may be a good opportunity for strategic reinvestment purchasing this property and turning it into a community garden a playground or more affordable housing I'm going to turn now to talking a little bit about indicators of quality of life we see that in the United States the average life expectancy is now 78 years it's actually come down in the past few years this map shows us county by county the life expectancy across the US and we begin to see some regional differences the variations and colors tell us that in some places average life expectancy is well above 80 years the dark blue for example in other places we see average like life expectancy in the 60s the yellow and the red in this map I've done a lot of work in southern Appalachia recently where average life expectancy is eight years lower than the national norm seventy years in on average what are some of the factors that we found that are associated with this quality of life difference intergenerational poverty substandard housing conditions lack of access to medical care and health insurance the in availability of healthy foods in a local proximity and more recently opioid overdose deaths a study quality of life all across North Carolina this is a map of High Point North Carolina where we've been doing some work life expectancy in high point is also 78 years long however when we look at it at a neighborhood level we see 17 years difference in just a two mile radius 70 years on average in the south of High Point and just two miles north in the northwest of High Point 87 years is average life expectancy so what are some of the factors that contribute to these differences on the neighborhood level well it's really very basic having access to wholesome foods having access to quality medical care and having access to good safe and affordable housing in neighborhoods with rich amenities food insecurity is a significant problem across North Carolina 15 percent of North Carolinians are food insecure and in High Point that's 19 percent of the general population we see that food insecurity is due to low income low food access neighborhoods in these neighborhoods the only food supply is a corner super corner market where you can get energy dense cheap high carb food that's really nutrient poor it leads to obesity and type 2 diabetes the supply of fresh fruits and vegetables is non-existent or very expensive in these little markets in those same neighborhoods we see that adults are getting less than a serving of fresh fruits or vegetables a day about 18 to 20 percent this leads to those issues of diabetes and hypertension so we see that in this map diabetes is in the same neighborhoods where fresh fruit fresh vegetables and ready supply fresh foods is lacking but a turn now to talking about affordable housing and the quality of housing I spend most of my time looking at housing issues today across the United States half of renters are now cost burdened this means that they spend more than 30 percent of their incomes on housing and housing related expenses leaving very little left over for medical care good foods education for their children transportation and other family expenses over the last 7 years we've seen that the cost of housing nationwide has increased over thirty five percent at the same time real wages have only gone up five percent and the availability of housing has decreased the Green Line show you that vacancy rates have gone from near ten percent down to seven percent the result is that in low-income areas with affordable housing the margin for landlords is very slim there's always a renter seeking new housing there's few vacancies available and there's a little incentive to discount properties or spend additional funds on maintaining those properties how do we know that the quality of housing has decreased well we trained a team of research assistants at UNCG to investigate housing quality they conducted a survey of over 78,000 parcels in Greensboro and 16,000 parcels in High Point looking at 53 items of housing characteristics from their roof condition to the foundation the walls the windows the paint and what kind of siding is being used this information was very important in allowing us to map where substandard housing is concentrated this map shows a concentration of substandard housing on the basis of scoring those properties of roof foundation walls windows etc importantly housing is related to the health of the community we find that substandard housing is correlated with several health problems and mental health issues asthma for example is affects more than 10 million children in the United States and it's been linked directly to substandard housing conditions this map shows us 6,200 cases from one quarter of 2016 from the local emergency department and health clinics people reporting for respiratory illnesses and asthma it it it shows us a hotspot map very similar to what we saw with substandard housing asthma cases are concentrated in low-income communities with substandard housing and little available health care when we begin to link these data sources together housing conditions hospital visits hotspot mapping of hospital ER admissions we begin to see which neighborhoods need interventions our team includes residents city officials hospital employees and staff researchers across multiple universities they've targeted these particular neighborhoods for interventions such as rehabbing housing and providing referrals for patients who have asthma that's triggered by substandard housing interestingly we've been able to leverage over four and a half million dollars of social impact investing in one neighborhood alone based on this information this investment is going to rehabbing multifamily complexes that had clusters of asthma cases we're hoping that this data and this process can make Greensboro an asthma safe city I'm gonna turn now to another chronic and a concerning issue within our community opiate overdose deaths the use of opiates has increased over the last 20 years and the opiate overdose deaths now are over a hundred every day in this country last year there were 700 overdose calls to EMS with in Guilford County alone and more than a hundred deaths reported in our County this map shows us where overdose reversals occurred using naloxone a life-saving drug that reverses the effects of opiates EMS first responders medical personnel have been able to track where clusters of overdoses occur and we've begun to match this information with Health Department data that shows us where there's high incidences of hepatitis C or HIV diseases that are often spread by IV drug use it's also allowed us to see that overdoses occur throughout the community opiate addiction is spread in all sectors rural and urban rich and poor it's also allowing us to target Rapid Response programs to those communities that need most to reduce mortality in our community by 20% overdose deaths in 2005 Jared Diamond wrote his book collapse how societies choose to fail or succeed he said in this book a society's fate lies in its own hands and depends substantially on its own choices I'd like to think that we have the data and the methods to make that make choices better for our community to avoid those collapses that have occurred to community to societies in the past my wife and I in Peru saw two great societies that no longer exist societies that had advanced technology mathematics sophisticated governments agricultural practices and yet they're gone and no one knows why I believe that by using empirical data translating that information into a way that speaks to a public that can make democratic choices and policy makers who can be most informed we can avoid the societal collapse that's occurred in other societies in the past thank you [Applause]

Channel: TEDx Talks

Views: 1,894

Rating: 4.875 out of 5

Keywords: TEDxTalks, English, Social Science, Community, Data, Decision making, Government, Urban Planning

Id: oaBrAOlEyRc

Length: 15min 11sec (911 seconds)

Published: Tue Jun 05 2018