County profile
Hart County, Georgia Community Health Profile
Environmental risk, disease burden, provider access, and SDOH scores for community health needs assessment and service line planning. Fused from EPA, CDC, CMS, and Census data into a single free view.
Opportunity Score
Env
33
−17 vs U.S. mean
Disease
58
+8 vs U.S. mean
Provider
60
+10 vs U.S. mean
SDOH
55
+5 vs U.S. mean
Specific health risk patterns
Hart County, GA: 3 specific risk patterns triggered
Each pattern below combines a specific environmental exposure with a population that is more vulnerable to that exposure. When both are present at meaningful levels in Hart County, the pattern triggers. These are the most concrete data points for documenting a significant health need in a Community Health Needs Assessment and for planning where services or community investment would land hardest.
Internally, we call these “Compound Signals.” Each is a versioned, weighted composite scored against the national distribution. The full formula and citations live on the methodology page.
Pesticide intensity at 62.2 kg per sq mi, summer max temperatures averaging 89.9°F.
Pesticide + heat exposure × Farmworker population
Defend this finding — full lineage to source data3 sources cited
Field Burdenneeds reviewHart County: 77/100 (elevated above the 70th-percentile threshold)
Hart County: 77/100 (elevated above the 70th-percentile threshold)
Pesticide intensity × summer heat × farmworker population proxy. Surfaces counties where outdoor agricultural workers face simultaneous heat-illness and pesticide-exposure risk.
Methodology. Demographic identifies the population HRSA 330(g) migrant/seasonal worker centers were created to serve. v1 weights are pending finalization — see ticket #90 — and the score is published with medium confidence pending the curation pass.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. All US counties evaluated for the signal (~3,222, less coverage gaps)
Components (3)
49th percentile
National percentile rank of pesticide application intensity per square mile, conservative-against-undercounting (EPest_HIGH) basis.
USGS — Pesticide National Synthesis Project (PNSP)
Vintage: PNSP 2019 (preliminary) · Refresh: Annual when published · Lag: 2–3 years
How it's measured. Total kg / county land area in sq mi, then rank-percentile against all PNSP-covered US counties. EPest_HIGH is the regional-pool imputation that errs against undercounting.
Caveat. PNSP is on medium-low update reliability — see pesticide_total_kg caveat.
Coverage. 3,054 of 3,222 US counties
89.9 °F
Mean of the daily maximum temperature across the meteorological summer (June–August).
NOAA — Applied Climate Information System (ACIS) — RCC-ACIS
Vintage: Multi-year mean (2018–2023 typical) · Refresh: Monthly · Lag: Current year
How it's measured. NOAA ACIS aggregates GHCN-Daily station observations to county-level summer (JJA) daily-max means using inverse-distance weighting. Smooths year-to-year noise; captures the structural heat profile.
Coverage. All 3,222 US counties
Composite proxy for outdoor agricultural worker exposure, derived from USDA NASS livestock counts and crop acreage indicators.
USDA — NASS — National Agricultural Statistics Service
Vintage: NASS Quick Stats current vintage · Refresh: Annual · Lag: 1–2 years
How it's measured. Weighted blend of farmworker-intensive crop acreage and livestock operations, used as a proxy for the population that HRSA 330(g) migrant/seasonal worker centers were created to serve. Direct farmworker counts are unreliable below state level; this proxy is the structural-pattern stand-in.
Coverage. Counties with non-zero ag activity
755.3 CAFO animal-units per sq mi (99th national percentile) led by broilers.
Agricultural runoff + flood exposure × Uninsured rural population
Defend this finding — full lineage to source data3 sources cited
Runoff Burdenneeds reviewHart County: 75/100 (elevated above the 70th-percentile threshold)
Hart County: 75/100 (elevated above the 70th-percentile threshold)
CAFO density × flood exposure × rural Medicaid coverage gap. Pattern after Hurricane Florence inundated 91 NC swine + 36 poultry CAFOs in 2018.
Methodology. Surfaces counties where concentrated animal feeding operations sit in flood-exposed terrain and the local health system is least equipped to absorb the public-health spillover. v1 uses placeholder-friendly formulation until Lynch/Parks 2025 lands.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. All US counties evaluated for the signal (~3,222, less coverage gaps)
Components (3)
99th percentile
National percentile rank of animal-unit density per square mile, derived from USDA livestock head counts and EPA Animal Unit conversion factors.
USDA + EPA — USDA Census of Agriculture + EPA 40 CFR §122.23 AU formula
Vintage: USDA Census of Ag 2022 (most recent quinquennial) · Refresh: Every 5 years · Lag: 1–2 years
How it's measured. Per-county livestock head counts (hogs, cattle, dairy, broilers, layers, turkeys, sheep) from USDA Census, multiplied by EPA 40 CFR §122.23 Animal Unit conversion factors, divided by county land area in square miles, then rank-percentile against all US counties.
Caveat. USDA Census suppresses cells where disclosure would identify individual farms, biasing the AU total downward in concentrated-producer counties. Census is quinquennial — between releases the value goes stale.
Coverage. Counties with non-zero animal-unit totals
County-level flood exposure index from Lynch & Parks 2025 — combines historical flood footprints, FEMA SFHA coverage, and 100-year floodplain population overlap.
Lynch / Parks — Lynch & Parks 2025 — county flood exposure index (pending ingestion #76)
Vintage: Pending pipeline ingestion (ticket #76) · Refresh: TBD
How it's measured. Peer-reviewed flood-exposure composite combining historical inundation footprints with current FEMA Special Flood Hazard Area coverage. Pending ingestion as of methodology v1.8.0; the v1 Runoff Burden signal uses placeholder-friendly formulation until this lands.
Caveat. Not yet in production JSON. Runoff Burden score is computable from CAFO density + uninsured rural alone in the interim; this leg is reserved for the post-#76 score refresh.
Coverage. All 3,222 US counties when ingested
Composite of rural-classified census tract share and Medicaid coverage shortfall — proxy for the rural population least insured against environmental health spillover.
Census Bureau — ACS 5-Year + Census urban-rural classification
Vintage: ACS 5-Year 2019–2023; rural classification 2020 decennial · Refresh: Quarterly (ACS); decennial (rural class) · Lag: 1 year (ACS)
How it's measured. Weighted blend of rural-classified tract share (Census urban-rural classification) and Medicaid + uninsured rate (ACS). Captures the population that bears the brunt of agricultural-runoff health events without coverage to absorb the medical cost.
Coverage. All 3,222 US counties
30 days above 95°F against a heart-disease + diabetes prevalence of 8.3% + 15.3%.
Extreme heat exposure × Heat-vulnerable population
Defend this finding — full lineage to source data5 sources cited
Heat VulnerabilityHart County: 74/100 (elevated above the 70th-percentile threshold)
Hart County: 74/100 (elevated above the 70th-percentile threshold)
Extreme heat exposure × cardiometabolic comorbidity × cardiology access deficit. Surfaces counties where a hot-day mortality event would land hardest.
Methodology. Heat-related cardiovascular mortality is the canonical climate-health linkage. The cardiometabolic blend identifies populations with the comorbidity profile that most amplifies heat-event mortality; the cardiology access leg captures whether the local system can absorb a heat-event surge.
Threshold. Elevated when score ≥ 70th national percentile across all US counties evaluated for this signal
Peer set. All US counties evaluated for the signal (~3,222, less coverage gaps)
Evidence base
- · Bobb JF et al. 'Heat-related mortality and adaptation to heat in the United States.' Environmental Health Perspectives 2014.
- · Khatana SAM et al. 'Association of extreme heat with all-cause mortality in the contiguous US.' JAMA Network Open 2022.
Components (3)
89.9 °F
Mean of the daily maximum temperature across the meteorological summer (June–August).
NOAA — Applied Climate Information System (ACIS) — RCC-ACIS
Vintage: Multi-year mean (2018–2023 typical) · Refresh: Monthly · Lag: Current year
How it's measured. NOAA ACIS aggregates GHCN-Daily station observations to county-level summer (JJA) daily-max means using inverse-distance weighting. Smooths year-to-year noise; captures the structural heat profile.
Coverage. All 3,222 US counties
Coronary heart disease + diabetes blend30%
60/40 dominant/secondary percentile blend of CHD and diabetes prevalence.
Methodology. Heat-vulnerability cardiometabolic cluster — counties with both conditions elevated face compounding heat-event mortality risk. Same dominant/secondary rule as the asthma+COPD blend.
Components (2)
8.3%
Percent of adults age 18+ self-reporting coronary heart disease diagnosis.
CDC — PLACES — Local Data for Better Health
Vintage: PLACES 2022–2023 · Refresh: Monthly · Lag: 1–2 years
How it's measured. PLACES small-area estimation from BRFSS self-report. Self-reported CHD undercounts asymptomatic disease.
Coverage. All 3,222 US counties
15.3%
Percent of adults age 18+ self-reporting diabetes diagnosis (excludes gestational).
CDC — PLACES — Local Data for Better Health
Vintage: PLACES 2022–2023 · Refresh: Monthly · Lag: 1–2 years
How it's measured. PLACES small-area estimation from BRFSS self-report. Excludes gestational diabetes per the BRFSS question framing.
Coverage. All 3,222 US counties
Cardiology access deficit30%
Inverted national percentile rank of cardiologists per 100K, with a 50/50 in-county/neighbor-county adjacency adjustment.
Methodology. Same adjacency-adjusted inversion as pulmonology deficit. Reduces false positives near major cardiac centers.
Components (2)
11.3 providers / 100K
Active cardiology specialists practicing in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry filtered to active cardiology taxonomy codes, geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation. The 50/50 adjacency adjustment helps but does not eliminate location noise.
Coverage. All 3,222 US counties
11.3 providers / 100K
Active cardiology specialists practicing in the county, normalized to population.
CMS — NPPES — National Plan and Provider Enumeration System
Vintage: Current month · Refresh: Monthly · Lag: Same month
How it's measured. NPPES registry filtered to active cardiology taxonomy codes, geocoded to practice address, summed per county, divided by Census population estimate.
Caveat. NPPES is registration-time data, not practice attestation. The 50/50 adjacency adjustment helps but does not eliminate location noise.
Coverage. All 3,222 US counties
2 signals near threshold: Outage Vulnerability (63) · Heat-Dialysis Vulnerability (55)
8 signals evaluated. See all signal methodologies →
Where Hart County stands
Health risks here sit near national averages
Hart County, Georgia has elevated doctor and specialist shortages — primary care and specialty access rank worse than 60% of U.S. counties. Pollution exposure, chronic disease rates, and social and economic conditions all sit closer to the middle of the national distribution. The issue here is healthcare infrastructure — not enough providers for the population — rather than vulnerability piling up across multiple dimensions. Counties in this profile are candidates for provider-recruitment and capacity-building investment.
Methodology: when three or more of the four major health-risk areas (pollution, chronic disease, doctor access, social and economic conditions) score above the 70th national percentile, we call the pattern “multi-pillar convergence.” The scoring approach and citations live on the methodology page.
Risk profile
Hart County compared to Georgia and the U.S. average
Four health-risk scores on a 0-100 scale, where 50 is the U.S. average. A higher score means that area is a stronger contributor to community health risk.
Disease Burden (58), Provider Gap (60), and SDOH Stress (55) are moderately worse than the U.S. average of 50.
Environmental Risk (33) is at or better than the U.S. average.
- Hart County
- Georgia state mean
- U.S. mean (50)
- Signal threshold (70)
Current Conditions
Today's air quality, fires, and weather alerts
Live operational data for Hart County: real-time AQI from EPA AirNow, active fires from NIFC, and any National Weather Service advisories. Updated daily.
Environmental Factors
Air, water, and exposure indicators
Top environmental indicators for Hart County with state and national benchmarks. Full profile covers 40+ metrics on the platform.
| Indicator | Hart County | GA avg | US avg |
|---|---|---|---|
PM2.5 (annual mean) EPA AQS / EJSCREEN | 8.4 µg/m³ -1.5% vs GA | 8.5 | 7.4 |
Ozone EPA AQS / EJSCREEN | 54.6 ppb ▲ +2.3% vs GA | 53.4 | 57.1 |
Traffic Proximity EJSCREEN | 58,685 index ▼ -67% vs GA | 179,769 | 291,320 |
Days Above 95°F NOAA ACIS | 30 days/yr ▲ +52% vs GA | 20 | 25 |
Superfund Proximity EPA EJSCREEN | 0.00 score ▼ -100% vs GA | 0.04 | 0.16 |
Drinking Water Violations EPA EJSCREEN | 0.11 score ▼ -92% vs GA | 1.37 | 3.39 |
Wildfire-Attributable Air Quality
Smoke PM2.5 the EPA doesn't count
Stanford peer-reviewed wildfire-attributable PM2.5 for Hart County. The EPA classifies wildfire smoke as "exceptional events" and excludes it from official AQS monitoring; Childs/Burke fills that gap with daily county-level data.
Source: Childs et al, Environmental Science & Technology 2022 (Harvard Dataverse 10.7910/DVN/DJVMTV). Latest year shipped: 2020. Burke et al, Nature 2023 estimate that the EPA AQS network undercounts wildfire-attributable PM2.5 by 10–30% in fire-affected counties. Coverage is CONUS only. Full methodology →
Outage Burden
When the grid goes dark
DOE/ORNL EAGLE-I customer-hours-out for Hart County in 2024. The fraction is population-normalized via the Maximum Customer Count denominator (Brelsford et al, Sci Data 2024) so it's directly comparable across counties of any size.
Source: DOE/ORNL EAGLE-I (figshare 10.6084/m9.figshare.24237376). Latest year shipped: 2024. Coverage: 3,050 of 3,222 US counties; AK and some sparsely-served rural counties may have no data. Full methodology →
Severe Weather History
Recorded storm events and damages
NOAA NCEI Storm Events Database for Hart County, 2010–2026. Cumulative + last 5 years of recorded weather events with deaths, injuries, and damages.
Source: NOAA NCEI Storm Events Database (full history rollup). NOAA buckets ~50 raw event_type strings into 8 health-relevant categories. Coverage: 3,107 of 3,222 US counties; the absent are typically Alaska boroughs and territories where NOAA codes events as forecast zones rather than counties. Full methodology →
Concentrated Animal Feeding Operations
Livestock density and federal-permit confidence
USDA Census of Agriculture (vintage 2022) animal-unit totals for Hart County, normalized to land area and ranked nationally. Animal Units (AU) follow the EPA federal definition under 40 CFR §122.23.
Source: USDA Census of Agriculture 2022 (head counts) + EPA 40 CFR §122.23 (animal-unit conversion). The CAFO composite deliberately omits NPDES facility counts because federal coverage averages ~32% nationally per EPA-IG and is heavily state-skewed — adding it as a numerator would systematically bias the index toward delegated states. Full methodology →
Pesticide Use
USGS Pesticide National Synthesis
Annual pesticide application rollup for Hart County from the USGS Pesticide National Synthesis Project. Most recent year on file: 2019. Mass figures use the EPest_HIGH estimate (the conservative-against-undercounting framing); EPest_LOW is also retained on the underlying data.
- 1.2,4-D5.7K kg
- 2.GLYPHOSATE2.8K kg
- 3.TRICLOPYR912 kg
- 4.METOLACHLOR & METOLACHLOR-S853 kg
- 5.METOLACHLOR-S780 kg
Source: USGS Pesticide National Synthesis Project (2019). USGS PNSP nationally; year 2019 is preliminary; 2018 unavailable; 2020+ not released. Update reliability medium-low. Full methodology →
Health Outcomes
Chronic disease prevalence
CDC PLACES model-based prevalence estimates for adults in Hart County. Full profile covers 15+ health outcomes plus mortality on the platform.
| Condition | Hart County | GA avg | US avg |
|---|---|---|---|
Current Asthma % of adults with current asthma | 10.2% ▼ -3.2% vs GA | 10.5% | 10.6% |
COPD % of adults with diagnosed COPD | 9.0% ▲ +2.5% vs GA | 8.8% | 8.6% |
Diabetes % of adults with diagnosed diabetes | 15.3% ▼ -2.2% vs GA | 15.6% | 13.7% |
Coronary Heart Disease % of adults with CHD | 8.3% ▲ +6.9% vs GA | 7.8% | 7.9% |
Depression % of adults ever diagnosed with depression | 20.4% +0.1% vs GA | 20.4% | 23.1% |
Frequent Mental Distress % of adults with 14+ poor mental health days/month | 17.2% ▼ -5.4% vs GA | 18.2% | 17.2% |
Vulnerable Medicare Population
Who needs the grid to stay alive
Medicare beneficiaries in Hart County who depend on electricity for dialysis, oxygen, or other powered medical equipment. From the HHS emPOWER program, which CMS publishes monthly so emergency managers know who to find first when the power goes out.
| Population | Count | Per 1,000 Medicare |
|---|---|---|
Total Medicare beneficiaries Denominator | 5,771 | — |
Electricity-dependent (any DME) Ventilators, oxygen concentrators, IV pumps, motorized wheelchairs | 259 | 44.9 ▼ -17% vs GA |
Dialysis-dependent ESRD beneficiaries needing in-center or home dialysis | ≤10 | 1.91 ▼ -70% vs GA |
Oxygen-dependent Home oxygen concentrators (outage-vulnerable) | 88 | 15.3 ▼ -23% vs GA |
Source: HHS emPOWER Map (ArcGIS county layer), May 2026. Counts of 1–10 are masked as “≤10” per HHS privacy rules; per-1,000 rates are derived and still respect the privacy floor. Full methodology →
Provider Supply
Specialty physician density per 100,000 residents
Active providers in Hart County from the CMS National Plan and Provider Enumeration System (NPPES). Compared to the U.S. average for each specialty. Adjacency adjustment is applied separately in the Provider Gap pillar score.
| Specialty | Hart County | US avg |
|---|---|---|
Primary Care Family medicine, internal medicine, general practice, pediatrics. | 105.7 per 100k ▼ -19% vs US | 130.4 |
Cardiology Cardiovascular disease, electrophysiology, interventional cardiology. | 11.3 per 100k ▼ -6.1% vs US | 12.1 |
Pulmonology Respiratory disease specialists — relevant to PM2.5 and wildfire smoke exposure. | 3.8 per 100k ▼ -37% vs US | 6.0 |
Psychiatry Mental health prescribers; complements behavioral health access. | 15.1 per 100k ▼ -19% vs US | 18.7 |
Oncology / Hematology Cancer specialists. | 3.8 per 100k ▼ -41% vs US | 6.4 |
Neurology Neurological disease specialists. | 7.5 per 100k ▼ -4.5% vs US | 7.9 |
Source: CMS National Plan and Provider Enumeration System (NPPES). Counts reflect providers with a primary practice address in Hart County; specialty is taken from the provider's primary NUCC taxonomy code.
Pro analytical view
What drives this county's scores
The flagged signals and service-line opportunities for Hart County, plus the methodology decomposition behind each score. Visible to Pro, Consultant Studio, and Enterprise tiers.
Where to focus
Pro feature
Top flagged signals + service lines are a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
Score decomposition
Each named signal's component breakdown with weights. The bar length is the component's percentile rank; the parenthetical is its weight in the final blend.
Pro feature
Score decomposition is a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
Tract drill-down
Census tracts inside Hart County
Pro feature
Tract-level drill-down is a Pro feature
See how each signal's components blend into its final score, and which signals + service lines this county should prioritize. Available on Professional, Consultant Studio, and Enterprise.
On the full platform
What else is available for Hart County
The page above is a subset. The free Community account unlocks the full single-county profile: every indicator, every data source, demographics, historical trends, and mortality data. Professional unlocks multi-county comparison, compound signal analysis, service line rankings, and consultant-ready PDF reports.
Full Environmental Profile
All 40+ environmental metrics including toxic releases, hazardous site proximity, PFAS detection, pesticide exposure, and climate stress indicators.
Service Line Opportunities
See how Hart County ranks for respiratory, oncology, cardiovascular, renal, endocrine, and behavioral health service line opportunity.
Multi-County Comparison
Compare Hart County side-by-side with neighboring counties across every dimension.
Trend Analysis
5-year sparklines for health outcomes, SDOH measures, and mortality rates so you can see where the county is heading, not just where it is today.
PDF Report Export
Generate a consultant-ready environmental health briefing for Hart County with methodology citations. Drops straight into a CHNA or grant application.
Nearby Counties
Counties bordering Hart County
Adjacent county profiles with their own scores and environmental health data. Source: Census Bureau County Adjacency File.
Franklin County
Georgia
59
Elevated
Madison County
Georgia
59
Elevated
Elbert County
Georgia
57
Elevated
Anderson County
South Carolina
51
Moderate
Oconee County
South Carolina
48
Moderate
Data sources: EPA AQS, EPA EJSCREEN, EPA TRI, CDC PLACES, CDC WONDER, CMS NPPES, Census ACS, County Health Rankings, NOAA ACIS, NCI State Cancer Profiles. Every score on this page is derived from publicly available federal data, fused by the Banana Analytics pipeline.
Methodology: See the full scoring methodology (v1.2.0) for weights, sensitivity analysis, and validation against county-level mortality data.
Last refreshed: May 28, 2026