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]
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]
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