ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · SEPTEMBER 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/september-2019-report
Monthly Traffic Safety Analysis
4,500 CRASHES IN
IOWA, IA
SEPTEMBER 2019
In September 2019, there were 4,500 total crashes, representing a 2.3% decrease from the 4,607 crashes recorded in September 2018. Despite the overall drop in collisions, the number of resulting fatalities rose significantly. There were 39 fatalities in September 2019, a 56% increase from the 25 fatalities documented in the same month of the prior year.
4,500
▼ -2.3%was 4,607
Total Crash Events
39
▲ 56.0%was 25
Persons Killed
1,702
▲ 5.6%was 1,612
Persons Injured
39
▲ 85.7%was 21
Fatal Crash Events
Note: "Persons Killed" (39) counts individual fatalities across all crash events. "Fatal" in the severity table below (39) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume saw a slight year-over-year decrease of 2.3% in September 2019 compared to September 2018. However, this downward trend in total crashes did not extend to crash outcomes, as total injuries increased by 5.6% from 1,612 to 1,702. Most notably, fatalities increased by 56%, rising from 25 in the prior year to 39 in the current period.
Vulnerable Road User Casualties
3
Pedestrians Killed
1
Cyclists Killed
35
Motorists Killed
0
Other Killed
29
Pedestrians Injured
52
Cyclists Injured
1,612
Motorists Injured
9
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent between September 2018 and September 2019. Friday was the peak day for crashes in both periods, with 776 incidents in 2019 and 778 in 2018. The 3 PM hour also remained the peak time for collisions in both years, with crash counts increasing from 379 to 411 during this hour. The distribution of crashes throughout the day and week showed no significant shifts year-over-year.
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened in September 2019 compared to the previous year, even as total crashes fell. The number of fatal crashes increased from 21 to 39, and the fatal crash rate per 100 crashes nearly doubled from 0.46 to 0.87. The proportion of crashes involving any level of injury (serious, minor, or possible) also increased, rising from 29.4% to 31.0% of all incidents. Consequently, the share of crashes with no reported injuries decreased from 70.3% in September 2018 to 68.1% in September 2019.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors shifted between the two periods. In September 2019, 'Followed too close' became the top factor with 610 incidents, an increase from 560 incidents in the prior year. 'Animal' related crashes, which were the top factor in 2018 with 590 incidents, dropped to the second position in 2019 with 423 incidents, a 28.3% decrease in count. The count of crashes attributed to 'Ran off road - left' increased by 11.7% from 248 to 277, while incidents involving 'Failure to Yield from a stop sign' remained relatively stable with 253 crashes compared to 256 the previous year.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions in September 2019 were characterized by a higher prevalence of clear weather compared to the same month in 2018. The proportion of crashes occurring in clear weather increased from 57.8% to 63.3%, while those in rainy conditions decreased from 11.1% to 9.0% of total crashes. Similarly, crashes on dry road surfaces made up a larger share of the total, rising to 74.6% from 69.8% the previous year. The distribution of crashes by lighting condition remained stable, with approximately 70% of incidents in both periods occurring during daylight hours.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Road surface condition field
Vehicles & Demographics
The demographics of vehicles and persons involved in crashes showed little change year-over-year. The top vehicle makes involved in collisions remained consistent, with Chevrolet and Ford models being the most frequent in both September 2019 and September 2018. The age distribution of persons involved in crashes also remained stable; for instance, the 26-34 age group accounted for 17.4% of individuals in 2019, nearly identical to their 17.6% share in 2018. The proportion of male and female persons involved was also consistent across both periods.
Top Vehicle Makes (8,091 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · Vehicle unit records
1,493 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,231 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2019-09-01 to 2019-09-30 · 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: 2019-09-01 through 2019-09-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2019-09-01 through 2019-09-30 (30 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 4,500
- Total persons involved: 10,863
- Total vehicles involved: 8,091
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: September 2019." Published September 9, 2026. Reporting period: 2019-09-01 to 2019-09-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/september-2019-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: 2019-09-01 – 2019-09-30
Generated: September 9, 2026 · All rights reserved