Risk Assessment Methodology

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Comprehensive Wisconsin Coverage

Our tool now covers all 72 Wisconsin counties with detailed risk assessments for 95 public health agencies, including:

  • 72 county health departments
  • 12 city/municipal health departments
  • Organized across 5 public health regions
  • Comprehensive coverage of all 84 public health agencies
  • All 11 federally-recognized tribal health centers/departments

See version history

Data Source Overview

Real-time Data Sources
  • CDC Social Vulnerability Index (SVI)
    • County-level vulnerability themes
    • Used for risk adjustments across all domains
    • Source: CDC/ATSDR SVI API
    • Annual Cache (365 days)
  • Wisconsin DHS Health Data
    • Respiratory illness surveillance (Flu, COVID, RSV)
    • County-level health metrics via web scraping
    • Source: Wisconsin DHS Public Data
    • Daily Cache (24 hours)
  • EPA AirNow API
    • Real-time air quality index (AQI)
    • County coordinates-based monitoring
    • Multi-point sampling for tribal areas
    • Hourly Updates
  • OpenWeatherMap API
    • Current weather conditions
    • Weather alerts and forecasts
    • County-based coordinate queries
    • Daily Cache (24 hours)
  • NOAA/NWS Climate Data
    • Wisconsin climate projections (2025-2050)
    • Heat forecasting and historical trends
    • Strategic extreme heat methodology
    • Annual Cache (365 days)
Static Data Sources
  • NCES SSOCS Survey (2019-2020)
    • School Survey on Crime and Safety
    • Wisconsin school safety indicators
    • Integrated into active shooter risk model
    • Static Dataset
  • Gun Violence Archive (GVA) 2023
    • Mass shooting incidents by county
    • Wisconsin-specific incident analysis
    • Historical trend calculations
    • Static Dataset
  • Wisconsin Tribal Boundaries
    • 11 federally-recognized tribal areas
    • GeoJSON boundary data
    • Tribal jurisdiction mapping
    • Static Geospatial Data
  • Wisconsin Health Departments
    • 95 public health jurisdiction boundaries
    • HERC region mappings
    • Service area definitions
    • Static Geographic Data
Synthetic Risk Models
  • Cybersecurity Risk
    • County-based statistical modeling
    • Population and infrastructure factors
    • SVI vulnerability adjustments
    • Model-Based
  • Utilities Risk
    • Infrastructure resilience modeling
    • County-level risk estimates
    • Based on demographic factors
    • Model-Based
Data Transparency Commitment
  • Real Data Sources: All API integrations use authentic government and scientific data
  • Cache Strategy: Appropriate refresh intervals based on data source update frequency
  • Static Datasets: Clearly identified with version dates and source attribution
  • Model-Based Components: Transparently labeled as synthetic risk calculations
  • No Placeholder Data: All risk scores are based on real data inputs or documented statistical models

Data Validation Process

Data Caching Strategy

Our persistent caching system optimizes data retrieval while maintaining data quality and integrity:

  • Annual Data (365-day cache): CDC Social Vulnerability Index, NOAA Climate Projections
  • Daily Data (24-hour cache): Wisconsin DHS Health Data, Weather alerts and forecasts
  • Hourly Data (1-hour cache): EPA AirNow API air quality index
  • Static Data (No cache expiry): NCES SSOCS Survey, Gun Violence Archive 2023, Tribal boundaries

Each data source has appropriate validation checks and error handling protocols.

Data Source Validation Method Frequency
CDC Social Vulnerability Index
  • API response validation
  • County FIPS code verification
  • SVI theme score range checks (0.0-1.0)
  • Error handling with graceful degradation
 Annual with 365-day cache
Wisconsin DHS Health Data
  • Web scraping data extraction
  • County name normalization
  • Disease activity metric validation
  • Temporal consistency checks
 Daily with 24-hour cache
EPA AirNow API
  • Coordinate-based query validation
  • AQI value range verification (0-500)
  • Multi-point sampling for tribal areas
  • API key authentication and retry logic
 Hourly with 1-hour cache
NCES SSOCS & GVA Static Data
  • Data file integrity verification
  • Wisconsin-specific filtering
  • County mapping validation
  • Statistical calculation verification
 Static datasets with version tracking

Risk Prioritization and Percentile Ranking

To enhance risk prioritization and create a more equitable distribution for comparing jurisdictions, we implement a percentile-based ranking system alongside absolute risk scores.

Absolute Risk Scores
  • Scale: 0.0 to 1.0
  • Calculation: Based on raw data inputs, SVI adjustments, and risk modeling
  • Interpretation:
    • Low Risk (0.0 - 0.3)
    • Medium Risk (0.3 - 0.6)
    • High Risk (0.6 - 1.0)
  • Purpose: Provides absolute measure of risk based on defined risk factors
Percentile Rankings
  • Scale: 0 to 100th percentile
  • Calculation: Statistical percentile rank among all assessed jurisdictions
  • Interpretation:
    • High Readiness Level (0-50th percentile)
    • Moderate Readiness Level (50-80th percentile)
    • Development Needed (80-100th percentile)
  • Purpose: Enables relative prioritization across jurisdictions, regardless of absolute risk values
Percentile Ranking Implementation

Percentile rankings are calculated for:

  • Overall Risk Score: Prioritization across all risk dimensions
  • Individual Hazard Types: Each hazard has its own percentile ranks (flood, tornado, etc.)
  • Risk Components: Component-specific percentiles (exposure, vulnerability, resilience)

This approach allows emergency managers to identify where their jurisdiction stands relative to others in Wisconsin, enhancing resource allocation decisions and mutual aid planning.

Temporal Risk Component Framework

Our new Baseline-Seasonal-Trend-Acute (BSTA) framework for risk assessment provides a more nuanced understanding of risks over time by decomposing risk scores into four temporal components:

Baseline (50%)

Long-term structural risk that changes very slowly (1-10 years)

Characteristics:
  • Represents fundamental risk exposure
  • Based on geographical, infrastructural, and demographic factors
  • Relatively stable over long periods
Intervention Focus: Long-term infrastructure and capacity building
Seasonal (20%)

Predictable cyclical variations throughout the year

Characteristics:
  • Follows annual patterns (e.g., winter storms in winter, tornadoes in spring/summer)
  • Highly predictable based on historical patterns
  • Specific to hazard types and geography
Intervention Focus: Cyclical preparedness activities
Trend (20%)

Medium-term directional changes (2-5 years)

Characteristics:
  • Represents emerging patterns from climate change, population shifts, etc.
  • Shows increasing or decreasing risk trajectory
  • May indicate effectiveness of mitigation efforts
Intervention Focus: Strategic planning and adaptation
Acute (10%)

Short-term, event-driven spikes (days to weeks)

Characteristics:
  • Current active events or immediate threats
  • Temporary but potentially severe elevation in risk
  • Requires real-time monitoring and alerts
Intervention Focus: Immediate response and resource allocation
Benefits of the BSTA Framework

This framework enables more nuanced and actionable risk information:

  • Improved resource allocation: Target interventions to the appropriate time scale
  • Enhanced planning: Prepare for both predictable patterns and emerging trends
  • Real-time responsiveness: Integrate current conditions for up-to-date risk assessment
  • Better communication: Provide context to stakeholders about the nature of risks
Temporal Patterns by Hazard Type
Hazard Type Seasonal Peak Trend Direction Acute Detection
Flood Spring (March-June) Increasing due to climate change Weather alerts, river gauges
Tornado Late Spring/Summer (April-August) Variable, subject to climate patterns Severe storm warnings
Winter Storm Winter (November-March) Stable, but greater extremes Winter storm warnings, ice alerts
Extreme Heat Summer (June-September) Increasing due to climate change Heat advisories, air quality alerts
Infectious Disease Variable by pathogen (respiratory in winter) Variable, affected by vaccination rates Disease surveillance systems

Enhanced Extreme Heat Risk Methodology

Climate-Adjusted Risk Assessment

Our enhanced extreme heat risk methodology incorporates climate change projections and uses only quantitative, publicly accessible data sources for complete transparency and replicability.

Data Sources
  • NOAA State Climate Summaries: Regional warming projections, heat frequency increases
  • EPA Heat Island Reports: Urban amplification factors, infrastructure vulnerability
  • CDC Social Vulnerability Index: Heat-sensitive demographics, housing conditions
  • NOAA Technical Reports: Wet bulb temperature calculations, humidity effects
  • IPCC AR6 Projections: Regional climate trends, multi-day heat events
Calculation Framework
  • Exposure: Geographic base × Climate frequency × Urban heat island
  • Vulnerability: SVI demographics × Heat-specific factors
  • Resilience: Infrastructure capacity × Adaptation penalty
  • Climate Adjustment: 40% frequency increase, 3°F warming
  • Wet Bulb Integration: Humidity-adjusted physiological limits
Scientific Transparency

All calculations use publicly accessible datasets with documented methodologies. The enhanced framework produces realistic risk scores that reflect current climate science while maintaining complete replicability for public health planning.

Multi-Dimensional Risk Framework

Our new multi-dimensional risk framework provides enhanced analysis of risk factors by breaking down each hazard into three key components:

Exposure

The likelihood and magnitude of the hazard itself based on historical data, geographical factors, and climate patterns.

Key Factors:
  • Event frequency
  • Historical severity
  • Projected trends
  • Geographic location
Data Sources: FEMA NRI, NOAA, NWS historical records
Vulnerability

Population and infrastructure susceptibility to the hazard, including demographic factors that increase risk.

Key Factors:
  • Demographic characteristics
  • Housing quality
  • Medical conditions
  • Socioeconomic status
Data Sources: CDC SVI, Census ACS, WI DHS
Resilience

Community capacity to absorb and recover from the hazard impact, including emergency response capabilities.

Key Factors:
  • Resource availability
  • Emergency infrastructure
  • Healthcare capacity
  • Community support systems
Data Sources: WEM data, HERC statistics, health department records
Implementation Note

The multi-dimensional approach provides more actionable insights than a single risk score by allowing emergency managers to target specific weaknesses (e.g., "Your community has high exposure but low resilience - focus on building recovery capacity").

This framework is implemented for all key natural hazards:

  • Flood Risk: Exposure (historical events, proximity to water, terrain), Vulnerability (population, infrastructure), Resilience (community capacity)
  • Tornado Risk: Exposure (historical patterns, seasonal factors), Vulnerability (building types, mobile homes), Resilience (warning systems, shelters)
  • Winter Storm Risk: Exposure (snowfall patterns, extreme cold frequency), Vulnerability (infrastructure, isolated areas), Resilience (road clearing, power capacity)
  • Thunderstorm Risk: Exposure (lightning density, severe storm frequency), Vulnerability (infrastructure, building stock), Resilience (warning systems, recovery capacity)
  • Extreme Heat Risk: Climate-adjusted exposure (NOAA projections, urban heat island), SVI-enhanced vulnerability (demographics, housing), infrastructure resilience capacity, wet bulb temperature considerations
  • Utilities Risk: Exposure (outage frequency, system age), Vulnerability (population density, critical facilities), Resilience (backup systems, recovery protocols)
  • Cybersecurity Risk: Threat Landscape, Vulnerability, Capability components
  • Active Shooter Risk: Historical Incident Density, School & Youth Vulnerability, Social & Community Fragility, Mental Health & Behavioral Health Risk, Access to Lethal Means (detailed methodology)

Social Vulnerability Index (SVI) Integration

The CDC's Social Vulnerability Index (SVI) is integrated throughout our risk assessment methodology as a critical multiplier that enhances the accuracy of various risk calculations.

What is SVI?

The Social Vulnerability Index uses 15 U.S. census variables to identify communities that may need additional support before, during, or after disasters. SVI indicates the relative vulnerability of every U.S. Census tract on four main themes:

  • Socioeconomic Status: Poverty, employment, income, education
  • Household Composition: Age, single-parent households, disability status
  • Minority Status: Race, ethnicity, language barriers
  • Housing Type & Transportation: Housing structure, crowding, vehicle access
How SVI Enhances Risk Calculations
SVI Theme Affected Risk Types Adjustment Method Maximum Impact
Housing & Transportation
  • Flood Risk
  • Tornado Risk
  • Winter Storm Risk
  • Thunderstorm Risk
 Multiplier based on housing vulnerability, affecting structural risk factors and evacuation capabilities Up to 50% increase in base risk for maximally vulnerable communities
Socioeconomic Status
  • Extreme Heat Risk (primary)
  • Flood Risk (secondary)
  • Tornado Risk (secondary)
  • Winter Storm Risk (secondary)
  • Thunderstorm Risk (secondary)
  • Utilities Risk (secondary)
  • Active Shooter Risk (secondary)
  • Cybersecurity Risk (secondary)
 Primary multiplier (40%) for Extreme Heat Risk reflecting access to cooling resources; Secondary multiplier (25%) for all other risk types reflecting resource access, recovery capacity, and disaster resilience Up to 40% increase for Extreme Heat Risk and up to 25% increase for all other risk categories in communities with high socioeconomic vulnerability
Household Composition
  • Active Shooter Risk
 Adjustment factor based on household vulnerability and evacuation challenges Up to 30% increase in risk score for communities with vulnerable household compositions
Overall SVI
  • Health Risk Metrics
  • Resource Allocation Guidance
 Incorporated in existing health vulnerability calculations, affecting response capacity assessment Built into disease impact calculation and resource recommendations
Implementation Note

SVI data is incorporated as a vulnerability multiplier, not as a primary risk driver. This approach ensures that risk assessments reflect both hazard likelihood (from primary data sources) and community vulnerability factors (from SVI), providing a more comprehensive and equitable risk assessment.

Socioeconomic Factor Universal Application: We've implemented socioeconomic vulnerability as a secondary factor across all risk types (25% maximum impact) because communities with fewer economic resources face greater challenges in emergency preparedness, response, and recovery regardless of the hazard type. This approach ensures that resource allocation and preparedness planning account for areas where economic disparities could exacerbate disaster impacts.

Verify Our Data Sources

You can independently verify our real-time data through these official sources:

Data Sources and Risk Calculations

Residual Risk Calculation Framework (v1.7.0)

Our risk assessment methodology now incorporates an enhanced residual risk calculation formula that provides more accurate, jurisdiction-specific risk prioritization without comparison to other jurisdictions. The latest update (v1.7.0) adds a health impact factor from FEMA NRI data:

Residual Risk = [(Exposure × Vulnerability) - (Resilience × Maximum Risk)] × Health Impact Factor

This formula represents a significant advancement in risk assessment methodology with the following components:

Exposure

Represents the likelihood and magnitude of a hazard event occurring. Factors include historical occurrence rates, geographic vulnerability, and event forecasting models.

Vulnerability

Measures the susceptibility of a jurisdiction to harm from the hazard. Includes population characteristics, infrastructure susceptibility, and socio-economic factors from the CDC's Social Vulnerability Index.

Resilience

Represents a jurisdiction's capacity to resist, absorb, and recover from hazards. Higher resilience values (0-1 scale) directly reduce the overall risk score, reflecting preparedness investments.

Maximum Risk

A calibration constant (default: 1.0) that ensures all risk scores are properly scaled. This allows for consistent interpretation across different hazard types.

NEW Health Impact Factor

A multiplier (0.8-1.5) derived from FEMA's National Risk Index (NRI) data that adjusts risk based on health-related consequences. It incorporates:

  • Expected Annual Loss of Population: Direct health impacts based on historical mortality
  • Social Vulnerability components: Health-specific vulnerabilities from CDC SVI data
  • Healthcare Access metrics: Distance to care and healthcare system capacity
  • Population with Disabilities: Percentage of population requiring specialized assistance

The factor amplifies risks with significant health consequences (>1.0) and de-emphasizes those with minimal health impacts (<1.0).

Risk Scale Interpretation:

  • 0.0-0.3 High Readiness Level - Low residual risk due to strong preparedness
  • 0.3-0.6 Moderate Readiness Level - Moderate risk requiring some improvements
  • 0.6-1.0 Development Needed - Higher risk requiring significant investment

Benefits of the new approach:

  • Provides jurisdiction-specific prioritization without comparison to others
  • Directly acknowledges how resilience counters specific risks
  • Enables high resilience to significantly reduce even high exposure/vulnerability
  • More accurately reflects real-world risk dynamics
  • Applies consistently across all hazard types including flood, tornado, winter storm, thunderstorm, extreme heat, infectious disease, active shooter, and all utilities risks

Visual Risk Prioritization System (v1.6.0)

Our visual risk prioritization system helps agencies clearly identify and address their most critical risks with intuitive visual elements:

Risk Scoring Framework
  • Raw Risk Score (0.0-1.0): Calculated from multiple data sources
  • Risk Classification:
    • High Risk: 0.6-1.0
    • Medium Risk: 0.3-0.6
    • Low Risk: 0.0-0.3
  • Visual Impact Indicators: Progress bars showing relative risk magnitude
Prioritization Benefits
  • Clear Risk Ordering: Risks are sorted by priority in descending order
  • Intuitive Visualization: Impact bars provide immediate visual cues
  • Resource Allocation: Helps agencies focus on most critical threats
  • Tailored Action Plans: Recommendations match the risk severity
Note: The visual prioritization system in v1.5.0 replaces the percentile ranking approach from v1.4.0. This change provides a more intuitive risk assessment format that focuses on absolute risk levels rather than relative ranking among jurisdictions.

NEW: Five-Domain Active Shooter Risk Framework (v1.8.0)

In version 1.8.0, we've enhanced our risk assessment methodology with improved active shooter risk assessment using the Five-Domain framework and NCES (National Center for Education Statistics) SSOCS (School Survey on Crime and Safety) data integration. This comprehensive approach provides more accurate risk scoring for all Wisconsin jurisdictions.

Five-Domain Framework

Active Shooter Risk = (0.25 × Historical) + (0.20 × School/Youth) + (0.20 × Social/Community) + (0.20 × Mental Health) + (0.15 × Lethal Means)

Each domain produces a score between 0.0-1.0, weighted by importance

The model uses five evidence-based domains that comprehensively assess active shooter risk factors. Each domain incorporates multiple data sources and metrics to create a robust risk assessment that can help jurisdictions prepare for and mitigate potential threats.

Key Improvements
  • NCES (National Center for Education Statistics) SSOCS (School Survey on Crime and Safety) Data: Added comprehensive school safety metrics
  • Improved GVA (Gun Violence Archive) Integration: Better city-to-county mapping for more accurate incident attribution
  • Detailed Documentation: Comprehensive methodology page with all data sources and calculations
  • Enhanced Youth Vulnerability: Additional metrics for school safety and youth disconnectedness
  • Better Data Attribution: Clear documentation of all data sources throughout the application
Risk Type Data Sources Data Scale Calculation Method Weight
Flood Risk
  • FEMA National Risk Index (NRI) Wisconsin Data
    • Annual loss estimates
    • Social vulnerability indicators
    • Community resilience scores
  • Wisconsin DNR Flood Hazard Data
    • 100-year floodplain maps
    • Historical flood records (1950-present)
  • USGS Stream Gauge Data
    • Real-time water levels
    • Historical peak flows
 Census Tract Level
  • Base score from NRI data (0-100 scale)
  • Normalized to 0-1 scale using min-max normalization
  • Historical trend analysis using 10-year moving average
  • Additional weight factors:
    • Population density (+0.1)
    • Infrastructure vulnerability (+0.1)
    • Mitigation measures (-0.1)
 10%
Tornado Risk
  • FEMA NRI Wisconsin Data
    • Historical tornado tracks
    • Damage assessments
    • Building exposure data
    • Mobile home density (% of housing units)
  • National Weather Service Storm Data
    • Enhanced Fujita (EF) Scale ratings
    • Path width and length measurements
    • Time and date records
  • Wisconsin Emergency Management Reports
    • Response effectiveness metrics
    • Recovery time analysis
  • US Census Bureau Housing Data
    • Mobile home percentage by jurisdiction
    • Housing unit vulnerability metrics
 Census Tract Level
  • Base score from NRI data (0-100 scale)
  • Normalized to 0-1 scale
  • Mobile home vulnerability adjustment:
    • Base risk increased by factor of mobile home percentage
    • Higher percentages of mobile homes increase vulnerability
    • Maximum adjustment capped at 2x base risk
  • Critical infrastructure adjustment:
    • Prison facility count from FEMA RAPT
    • Risk increased by 10% per facility
    • Maximum 20% increase for multiple facilities
  • Frequency adjustment based on:
    • 30-year occurrence rate
    • Average EF scale rating
    • Seasonal probability factors
 10%
Winter Storm Risk
  • FEMA NRI Wisconsin Data
    • Winter storm frequency
    • Impact assessments
    • Infrastructure resilience data
  • National Weather Service Records
    • Snowfall accumulation data
    • Ice storm frequency
    • Wind chill statistics
  • WI DOT Winter Operations Data
    • Road treatment effectiveness
    • Snow removal response times
    • Equipment readiness metrics
 Census Tract Level
  • Base score from NRI data (0-100 scale)
  • Normalized to 0-1 scale
  • Seasonal adjustment factors:
    • Average snowfall (+0.1 per 10" above mean)
    • Ice storm frequency (+0.05 per event)
    • Road accessibility score (-0.1 to +0.1)
 10%
Thunderstorm Risk
  • FEMA NRI Wisconsin Data
    • Thunderstorm frequency
    • Lightning strike density
    • Wind gust data
    • Property damage assessments
  • NOAA Storm Event Database
    • Historical severe thunderstorm records
    • Damage reports by county
    • Wind speed measurements
  • National Weather Service
    • Severe thunderstorm warnings
    • Frequency of high wind events
    • Lightning detection network data
  • US Census Bureau Housing Data
    • Housing construction quality metrics
    • Storm shelter availability
 Census Tract Level
  • Base score from NRI and NOAA data (0-100 scale)
  • Normalized to 0-1 scale
  • SVI adjustments:
    • Housing vulnerability multiplier (up to 50% increase)
    • Socioeconomic vulnerability factor (up to 25% increase)
  • Additional risk factors:
    • Tree coverage density (+0.05 to +0.15)
    • Power infrastructure vulnerability (+0.1 to +0.2)
    • Historical property damage rates (+0.05 to +0.15)
 10%
Extreme Heat Events
  • NOAA State Climate Summaries - Wisconsin (2022)
    • Regional warming projections (2-4°F by 2050)
    • Heat event frequency increases (40% by 2050)
    • RCP4.5 scenario data
  • EPA Climate Change and Heat Islands (2021)
    • Urban heat island amplification factors
    • Infrastructure heat vulnerability
    • Heat threshold guidelines
  • NOAA Technical Report OAR CPO-2 (2020)
    • Wet bulb temperature calculations
    • Humidity-adjusted heat stress
    • Physiological heat limits
  • CDC Social Vulnerability Index 2020
    • Heat-sensitive demographics
    • Housing vulnerability factors
    • Cooling center availability
  • CDC Environmental Public Health Tracking
    • Urban heat island effects
    • Demographic vulnerability data
    • Air quality correlations
 County Level
  • Enhanced Climate-Adjusted Framework:
    • Exposure = Geographic base × NOAA climate frequency multiplier × Urban heat island factor
    • Vulnerability = CDC SVI demographic factors × Heat-specific multipliers
    • Resilience = Infrastructure capacity × Climate adaptation penalty
    • Wet Bulb = Regional humidity patterns × Climate humidity increase
    • Climate Trend = IPCC regional warming × Urban amplification
  • Overall Formula: (Exposure × Vulnerability ÷ Resilience) × (1 + Wet_Bulb × 0.5) × Climate_Trend
  • Climate Adjustments:
    • 40% frequency increase (NOAA RCP4.5)
    • 3°F temperature rise (Great Lakes region)
    • 60% duration increase (IPCC AR6)
    • 2.2x multi-day events (EPA)
  • All calculations based on publicly accessible, quantitative datasets
 10%
Infectious Disease Risk
  • Wisconsin DHS Surveillance Data
    • Disease outbreak reports
    • Vaccination coverage rates
    • Healthcare access metrics
  • County Health Department Records
    • Local outbreak data
    • Contact tracing effectiveness
    • Testing capacity metrics
  • CDC Community Health Indicators
    • Social vulnerability index
    • Healthcare facility density
    • Population demographics
 County Level
  • Base rate: 0.3-0.4
  • Adjusted by:
    • Vaccination rate (-0.1 to +0.1)
    • Population density factor (0.05 per 1000/sq mi)
    • Healthcare access score (-0.1 to +0.1)
    • Historical outbreak frequency (+0.05 per significant event)
 20%
Active Shooter Risk
  • Five-Domain Risk Framework:
    • Historical Incident Density (25%): GVA (Gun Violence Archive) data, crime patterns
    • School & Youth Vulnerability (20%): NCES (National Center for Education Statistics) SSOCS (School Survey on Crime and Safety) data, youth factors
    • Social & Community Fragility (20%): Social cohesion metrics
    • Mental Health Risk (20%): Provider availability, access metrics
    • Access to Lethal Means (15%): Availability factors
  • Data Sources:
    • Gun Violence Archive (GVA)
    • NCES (National Center for Education Statistics) SSOCS (School Survey on Crime and Safety) 2019-2020
    • Census ACS (American Community Survey) & CDC (Centers for Disease Control) SVI (Social Vulnerability Index)
  • View detailed methodology
  • FBI Crime Data API
    • Violent crime statistics
    • County-level offense data
    • Multi-year trend analysis
  • HRSA Health Professional Shortage Areas
    • Mental health provider shortages
    • Healthcare access metrics
    • County-level provider ratios
 County Level
  • Five-Domain Weighted Formula:
    • Historical Incident Density (25%)
    • School & Youth Vulnerability (20%)
    • Social & Community Fragility (20%)
    • Mental Health Risk (20%)
    • Access to Lethal Means (15%)
  • Adjustments:
    • SVI socioeconomic factor (up to 25%)
    • Rural/urban density scaling
    • Data quality confidence indicators
 10%
Utilities Risk
  • Multi-dimensional Risk Components:
    • Electrical Outage: Power grid reliability and backup capabilities
    • Utilities Disruption: Water, gas, telecommunications systems
    • Supply Chain: Critical supply availability and logistics
    • Fuel Shortage: Fuel reserves and distribution networks
  • NEW: Residual Risk Calculation Applied
    • All utilities risk types now use the residual risk formula: (Exposure × Vulnerability) - (Resilience × Maximum Risk)
    • This provides more accurate jurisdiction-specific risk assessments
    • Directly accounts for resilience investments reducing overall risk
  • Wisconsin Public Service Commission Data
    • Outage frequency and duration statistics
    • Critical infrastructure resilience metrics
    • System age and maintenance factors
  • Wisconsin Emergency Management (WEM)
    • Utility vulnerability assessments
    • Regional dependency mappings
    • Resilience capability metrics
 County Level
  • Component weighting:
    • Electrical Outage (30%)
    • Utilities Disruption (30%)
    • Supply Chain (20%)
    • Fuel Shortage (20%)
  • Each component analyzed using:
    • Exposure: Historical outage frequency, system vulnerabilities
    • Vulnerability: Population density, critical facility dependency
    • Resilience: Backup systems, recovery protocols, resource allocation
  • SVI socioeconomic adjustment factor applied (max 25% increase)
 10%
Cyberthreats
  • Wisconsin Department of Enterprise Technology (DET)
    • Security incident reports
    • Vulnerability assessment data
    • Critical infrastructure protection metrics
  • MS-ISAC (Multi-State Information Sharing & Analysis Center)
    • Threat intelligence feeds
    • Regional cyber incident data
    • State-specific vulnerability alerts
  • HHS HC3 (Health Sector Cybersecurity Coordination Center)
    • Healthcare-specific threat intelligence
    • Sector vulnerability reports
    • Medical device security metrics
  • Wisconsin Healthcare Emergency Preparedness Program
    • Healthcare facility cybersecurity assessments
    • IT infrastructure resilience scores
    • Emergency response capabilities
 Healthcare Facility Level
  • Base score derived from:
    • NIST Cybersecurity Framework compliance score
    • Recent incident frequency and severity
    • Critical system vulnerability metrics
  • Risk modifiers:
    • Security control maturity (+/-0.1 per NIST tier level)
    • Incident response capability (-0.1 for mature program)
    • Connected medical device density (+0.05 per 100 devices)
    • Staff security training completion (-0.05 per 90% compliance)
  • Final score normalized to 0-1 scale
 10%

Data Update Frequency

  • Wisconsin DHS Health Metrics Daily
  • OpenFEMA Facility Data Weekly
  • FEMA National Risk Index Quarterly
  • Representative Data Updates As Available
Verify Our Data Sources

You can verify our data directly through these official sources:

Detailed Documentation

For a comprehensive understanding of our risk assessment methodology, including:

  • Complete data source details
  • Current limitations
  • Future improvements
  • Validation methods
Download Complete Methodology (PDF)

Cybersecurity Risk Assessment Methodology

Note: Our cybersecurity risk assessment uses publicly available data sources to ensure transparency and reproducibility. While this approach has limitations, it provides a standardized baseline for comparing jurisdictions.
Data Sources
  • HHS Breach Portal

    Healthcare-specific breach incidents reported per 100,000 population

    Weight in risk calculation: 40%
  • FBI Internet Crime Complaint Center (IC3)

    Regional cybercrime reports per 100,000 population

    Weight in risk calculation: 35%
  • CISA Known Exploited Vulnerabilities (KEV) Catalog

    Critical vulnerabilities affecting healthcare systems

    Weight in risk calculation: 25%
Risk Score Calculation
Component Calculation Method Score Range
Breach Score (Incidents per 100k) / 5.0
Normalized against maximum expected rate of 5 incidents per 100k population 		0.0 - 1.0
Cybercrime Score (Reports per 100k) / 500.0
Normalized against maximum expected rate of 500 reports per 100k population 		0.0 - 1.0
Vulnerability Score (Critical vulnerabilities) / 15.0
Normalized against maximum expected count of 15 critical vulnerabilities 		0.0 - 1.0
Limitations and Considerations
Data Limitations
  • Reporting delays in public data sources (typical lag: 30-90 days)
  • Underreporting of incidents, especially in smaller jurisdictions
  • Geographic attribution challenges for cybersecurity incidents
  • Limited visibility into internal security measures and controls
Data Update Frequency
  • HHS Breach Portal Daily
  • FBI IC3 Reports Quarterly
  • CISA KEV Catalog Weekly
SVI Integration for Cybersecurity Risk

We apply the CDC's Social Vulnerability Index socioeconomic factor as a secondary multiplier in cybersecurity risk assessment based on research showing strong correlations between:

  • Socioeconomic status and cybersecurity budget/resource allocation
  • Economic vulnerability and cybersecurity resilience/recovery capability
  • Poverty indicators and access to cybersecurity expertise
  • Education levels and staff security awareness/training outcomes

This integration increases cybersecurity risk scores by up to 25% for jurisdictions with high socioeconomic vulnerability, ensuring resource allocation accounts for these disparities.

Future Enhancements

We continuously evaluate opportunities to enhance our cybersecurity risk assessment methodology, including:

  • Integration of additional public threat intelligence feeds
  • Improved geographic specificity for incident attribution
  • Enhanced visualization of threat patterns and trends
  • Integration of anonymized aggregate data from security information sharing partnerships

Health System Metrics Impact

  • Hospital Beds per 1000 residents 30% Source: WI Hospital Association
  • Vaccination Rate 25% Source: WI DHS Immunization Program
  • Emergency Response Time 25% Source: WI EMS Incident Reports
  • Healthcare Facilities Density 20% Source: WI DHS Facility Database

Risk Level Categories

  • Low Risk < 0.3 Standard monitoring and preparedness
  • Medium Risk 0.3 - 0.6 Enhanced monitoring and response readiness
  • High Risk > 0.6 Immediate action and resource allocation required

CDC Public Health Emergency Preparedness (PHEP) Capabilities Integration

The Wisconsin Geospatial Health & Emergency Preparedness Risk Assessment Tool has been enhanced to align with the CDC's Public Health Emergency Preparedness (PHEP) Cooperative Agreement 2024-2028. This alignment ensures that preparedness strategies provided by the tool directly support the core capabilities required for effective public health emergency response.

PHEP Capabilities Integrated Throughout Tool

All risk assessment results, action plans, and preparedness recommendations have been designed to support the following CDC PHEP Capabilities:

Foundational Capabilities
  1. Community Preparedness - Building community resilience through risk-informed planning
  2. Community Recovery - Supporting recovery operations for public health systems
  3. Emergency Operations Coordination - Establishing effective incident command structures
  4. Emergency Public Information and Warning - Facilitating timely information exchange
  5. Information Sharing - Maintaining situational awareness across partners
  6. Responder Safety and Health - Protecting public health workforce
Incident-Specific Capabilities
  1. Medical Countermeasure Dispensing and Administration
  2. Medical Materiel Management and Distribution
  3. Medical Surge - Supporting healthcare systems during crises
  4. Nonpharmaceutical Interventions - Implementing community mitigation strategies
  5. Public Health Laboratory Testing - Identifying biological and chemical threats
  6. Public Health Surveillance and Epidemiological Investigation
PHEP Capability Implementation in Risk Assessment and Action Planning

For each risk type, specific PHEP capabilities are identified and integrated into our three-phase implementation approach:

Implementation Phase Timeframe PHEP Capability Focus
Immediate 0-30 days
  • Emergency Operations Coordination
  • Emergency Public Information and Warning
  • Community Preparedness
Short-term 1-3 months
  • Information Sharing
  • Medical Countermeasure Dispensing
  • Public Health Surveillance
  • Responder Safety and Health
Long-term 3-12 months
  • Community Recovery
  • Public Health Laboratory Testing
  • Medical Surge
  • Medical Materiel Management
PHEP Cooperative Agreement Alignment

The action plans generated by this tool are specifically designed to help local and Tribal health departments meet the requirements of the CDC PHEP Cooperative Agreement 2024-2028. Each recommendation is tied to specific PHEP capabilities and can be directly incorporated into jurisdictional preparedness plans and funding applications.

Version History and Updates

Version Date Key Changes
1.9.0 May 4, 2025
  • NEW: Persistent Caching System - Implemented efficient file-based persistent caching for data sources based on their update frequency
  • NEW: Advanced Data Validation - Created comprehensive validation and verification tools for Census API data
  • NEW: API Error Handling - Added robust error handling with retry mechanisms and graceful degradation for all external API connections
  • Reduced API usage for Census ACS data from daily to annual with quality-controlled persistent caching
  • Enhanced SVI data retrieval with validation, error handling, and annual persistent caching
  • Implemented cache expiration periods appropriate to each data source's update frequency
  • Added metadata tracking for all cached data to improve traceability and debugging
1.8.0 April 20, 2025
  • NEW: NCES (National Center for Education Statistics) SSOCS (School Survey on Crime and Safety) Integration - Added SSOCS 2019-2020 data into Active Shooter risk model
  • NEW: Five-Domain Active Shooter Framework - Created dedicated active shooter methodology page with detailed explanation of risk domains
  • Enhanced Active Shooter Risk calculation with improved GVA (Gun Violence Archive) data and county mapping
  • Improved School & Youth Vulnerability domain with comprehensive school safety metrics
  • Added detailed attribution of data sources throughout Active Shooter documentation
1.7.0 April 16, 2025
  • NEW: Health Impact Factor Integration - Added health-related consequence multiplier from FEMA NRI data, scaling risk scores to better reflect health impacts
  • Enhanced residual risk formula to include health impact factor
  • Improved flood risk calculation with health consequences data
  • Updated methodology documentation to explain health impact factors
1.6.0 April 16, 2025
  • NEW: Implemented advanced residual risk calculation formula across all risk types: (Exposure × Vulnerability) - (Resilience × Maximum Risk)
  • NEW: Replaced percentile-based ranking with jurisdiction-specific risk scoring that doesn't require comparison
  • NEW: Enhanced utilities risk calculations (electrical outage, utilities disruption, supply chain, fuel shortage) with residual risk model
  • Integrated CDC Public Health Emergency Preparedness (PHEP) Capabilities framework throughout all risk types
  • Enhanced action plans with public health-specific preparedness strategies aligned with CDC PHEP Cooperative Agreement 2024-2028
  • Implemented enhanced visual risk prioritization system with impact bars for resource allocation decisions
  • Added comprehensive utilities risk assessment with four distinct components (Electrical Outage, Utilities Disruption, Supply Chain, Fuel Shortage)
  • Implemented multi-dimensional risk models for tornado, winter storm, and thunderstorm hazards using Exposure, Vulnerability, and Resilience components
  • Updated risk weight distribution: Natural Hazards (40%), Health Metrics (20%), Active Shooter (10%), Utilities (30%)
  • Applied SVI socioeconomic factors to all risk calculations (25% maximum impact)
1.2.0 April 15, 2025
  • Applied socioeconomic SVI factor to all risk calculations (25% maximum impact)
  • Enhanced risk calculation accuracy with multi-factor SVI integration
  • Improved cybersecurity risk assessment methodology with socioeconomic indicators
  • Updated methodology documentation to reflect comprehensive SVI integration
  • Fixed data quality issues in regional risk assessment calculations
1.1.0 April 4, 2025
  • Added coverage for all 90+ Wisconsin health departments
  • Implemented Southwest Suburban Health Department (West Allis-Greenfield)
  • Added Wauwatosa Health Department with complete risk profile
  • Fixed jurisdiction mapping duplications (Shawano-Menominee, Brown County)
  • Improved data scraping for Wisconsin DHS portal
  • Enhanced jurisdiction mapping for all counties
  • Updated methodology documentation with comprehensive coverage details
1.0.0 March 24, 2025
  • Initial release with 12 core jurisdictions
  • Base implementation of risk calculation methodology
  • Integration with Census, DHS, and FEMA data sources
  • Basic risk visualization and reporting
Next Scheduled Review: September 30, 2025