ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · 2019
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2019-annual-report
Yearly Traffic Safety Analysis
2,473 CRASHES IN
IOWA, IA
2019
In 2019, Woodbury County recorded 2,473 total crashes, a 3.9% increase from the 2,381 crashes reported in 2018. The total number of injuries rose by a similar margin, from 785 to 816. The most significant year-over-year change was a sharp rise in traffic fatalities, which increased from 5 in 2018 to 12 in 2019.
2,473
▲ 3.9%was 2,381
Total Crash Events
12
▲ 140.0%was 5
Persons Killed
816
▲ 3.9%was 785
Persons Injured
12
▲ 140.0%was 5
Fatal Crash Events
Note: "Persons Killed" (12) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic safety metrics in Woodbury County showed a negative trend from 2018 to 2019. The total number of crashes rose by 3.9%, from 2,381 to 2,473. This was accompanied by a 3.9% increase in total injuries and a 140% increase in total fatalities, which grew from 5 to 12.
Vulnerable Road User Casualties
2
Pedestrians Killed
3
Cyclists Killed
7
Motorists Killed
0
Other Killed
24
Pedestrians Injured
15
Cyclists Injured
772
Motorists Injured
5
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Woodbury County remained largely consistent between 2018 and 2019. Friday was the peak day for crashes in both periods, with incidents increasing from 403 to 436. The 3 p.m. hour was also the peak hour in both years, rising from 206 crashes in 2018 to 217 in 2019. The afternoon commute hours consistently accounted for the highest volume of crashes.
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened from 2018 to 2019. The number of fatal crashes more than doubled from 5 to 12, increasing the fatal crash share from 0.2% to 0.5% of all incidents. Crashes resulting in serious injuries also increased in both count (from 32 to 36) and proportion (from 1.3% to 1.5%). While the share of 'No Injury' crashes remained the largest category at approximately 69% in both years, the absolute number of injury-involved crashes rose.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes were consistent year-over-year, with some shifts in volume. 'Followed too close' remained the top factor in both periods, though its count decreased from 243 incidents in 2018 to 232 in 2019. Similarly, 'Ran off road - left' stayed the second-most common factor, with its count declining from 216 to 207. Conversely, crashes attributed to 'Failure to yield right of way from a stop sign' increased from 166 to 179, and incidents involving 'Ran Traffic Signal' rose from 109 to 133.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2019 occurred more frequently on dry roads compared to the prior year, with the proportion rising from 60.8% to 65.7%. Correspondingly, the share of crashes on wet, snow, or ice-covered surfaces declined from a combined 32.2% in 2018 to 28.1% in 2019. The distribution of crashes by lighting conditions remained stable, with approximately two-thirds of incidents in both years occurring during daylight hours. Crashes in clear weather increased from 1,340 to 1,462, representing a larger share of the total.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field
Vehicles & Demographics
The types of vehicles involved in crashes remained consistent, with Ford and Chevrolet models being the most common in both 2018 and 2019. The number of Fords involved in collisions increased from 652 to 681, while Jeep involvement rose from 184 to 204. An analysis of persons involved in crashes shows an increase across most age demographics, with a notable rise in the 65 and older age group from 472 individuals in 2018 to 580 in 2019. The 26-34 age group remained the largest demographic involved in crashes in both years.
Top Vehicle Makes (4,548 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records
1,297 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,785 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Person-level records linked to crash events
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: ArcGIS Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2019-01-01 through 2019-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2019-01-01 through 2019-12-31 (365 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 2,473
- Total persons involved: 6,122
- Total vehicles involved: 4,548
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2019." Published September 9, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2019-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2019-01-01 – 2019-12-31
Generated: September 9, 2026 · All rights reserved