ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · OCTOBER 2022
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/october-2022-report
Monthly Traffic Safety Analysis
5,003 CRASHES IN
IOWA, IA
OCTOBER 2022
In October 2022, Iowa recorded 5,003 traffic crashes, a 4.5% decrease from the 5,238 crashes reported in October 2021. This overall reduction was accompanied by a slight drop in total injuries from 1,619 to 1,583 and fatalities from 34 to 33. A notable shift occurred in environmental conditions, with a significantly higher proportion of crashes in the current period happening in clear weather on dry roads compared to the prior year.
5,003
▼ -4.5%was 5,238
Total Crash Events
33
▼ -2.9%was 34
Persons Killed
1,583
▼ -2.2%was 1,619
Persons Injured
31
▼ -6.1%was 33
Fatal Crash Events
Note: "Persons Killed" (33) counts individual fatalities across all crash events. "Fatal" in the severity table below (31) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Iowa showed a downward trend in a year-over-year comparison for October. The total number of crashes fell by 4.5%, from 5,238 in October 2021 to 5,003 in October 2022. Similarly, the number of people injured decreased by 2.2% to 1,583, and fatalities saw a minor decline from 34 to 33.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
32
Motorists Killed
0
Other Killed
43
Pedestrians Injured
41
Cyclists Injured
1,497
Motorists Injured
2
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained broadly consistent year-over-year. Friday was the peak day for crashes in both October 2022 (823 crashes) and October 2021 (1,028 crashes), though the volume on Friday decreased significantly. The 3 p.m. hour was the peak hour in both periods, with 435 crashes in the current period compared to 385 in the prior period.
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes saw minor shifts between the two periods. The fatal crash count decreased slightly from 33 to 31, but the fatal crash rate as a percentage of all crashes remained stable at 0.6%. While total crashes declined, the share of crashes resulting in minor injuries increased from 8.5% to 9.6%, and the share of serious injury crashes rose from 2.4% to 2.6%. Conversely, the proportion of crashes with possible injuries or no injuries saw a slight decrease.
Severity is per crash event (most severe injury). 31 fatal crash events resulted in 33 persons killed.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes remained consistent year-over-year, with 'Animal' being the most common cause in both periods, though its count decreased by 6.8% from 1,025 to 955 crashes. 'Followed too close' remained the second-ranked factor, with its count dropping by 5.1% from 551 to 523. The third-ranked factor, 'Other', had an identical count of 312 in both years. Notably, crashes attributed to 'Driving too fast for conditions' saw a significant count-based decrease of 27.1%, from 144 to 105 incidents.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a significant year-over-year shift in the conditions under which crashes occurred. In October 2022, a much larger share of collisions happened in favorable conditions compared to October 2021. Crashes on dry roads accounted for 77.3% of the total, up from 66.5% the previous year, while crashes on wet roads fell from 15.3% to 5.5% of the total. Similarly, 71.7% of crashes occurred in clear weather, a substantial increase from 56.7% in the prior period, suggesting driving conditions were generally better.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained stable, with Ford, Chevrolet, and Toyota being the top three in both periods, all showing slight decreases in involvement consistent with the overall trend. An analysis of persons involved in crashes shows a shift in age demographics. The proportion of involved individuals aged 16-20 decreased from 15.3% to 14.1% of the total. In contrast, the share of those aged 26-34 increased from 16.6% to 17.1%, and the 65+ age group's representation grew from 12.2% to 13.8%.
Top Vehicle Makes (8,455 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records
1,341 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,663 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2022-10-01 through 2022-10-31 (31 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 5,003
- Total persons involved: 11,444
- Total vehicles involved: 8,455
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: October 2022." Published September 9, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/october-2022-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: 2022-10-01 – 2022-10-31
Generated: September 9, 2026 · All rights reserved