ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · APRIL 2026
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/april-2026-report
Monthly Traffic Safety Analysis
3,815 CRASHES IN
IOWA, IA
APRIL 2026
In April 2026, Iowa recorded 3,815 traffic crashes, a 7.0% increase from the 3,564 crashes documented in April 2025. This year-over-year rise was accompanied by an increase in total injuries from 1,226 to 1,277 and fatalities from 20 to 22. One of the most significant changes observed was a 72% increase in the number of pedestrians injured, which rose from 25 in the prior year to 43 in the current period.
3,815
▲ 7.0%was 3,564
Total Crash Events
22
▲ 10.0%was 20
Persons Killed
1,277
▲ 4.2%was 1,226
Persons Injured
20
▲ 11.1%was 18
Fatal Crash Events
Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data indicates a rising trend in April 2026 compared to the same month in the prior year. Total crashes increased by 7.0%, from 3,564 to 3,815. This upward trend was also reflected in crash outcomes, with total injuries rising by 4.2% and total fatalities increasing by 10% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
22
Motorists Killed
0
Other Killed
43
Pedestrians Injured
44
Cyclists Injured
1,182
Motorists Injured
8
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The time of day when crashes most frequently occurred remained consistent, with the 3 p.m. hour being the peak for both April 2026 (355 crashes) and April 2025 (346 crashes). However, the peak day for crashes shifted from Wednesday (659 crashes) in the prior year to Thursday (687 crashes) in the current period. Crashes during weekdays (Monday-Friday) saw a more significant year-over-year count increase of 8.2% compared to a 2.8% rise in weekend crashes.
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall distribution of crash severity remained largely unchanged between April 2025 and April 2026. The fatal crash rate saw a marginal increase from 0.51% to 0.52%, corresponding to a rise in fatal crashes from 18 to 20. The proportion of crashes resulting in serious injury decreased slightly from 2.6% to 2.5%, while crashes with possible injuries saw a small increase in their share of all crashes from 16.3% to 16.5%. Crashes involving no injuries constituted the majority in both periods, at 70.5% in 2025 and 70.4% in 2026.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 22 persons killed.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes remained consistent year-over-year, with 'Followed too close,' 'Animal,' and 'Failure to Yield Right of Way from a stop sign' ranking as the top three in both April 2025 and April 2026. The count of crashes attributed to 'Followed too close' increased by 4.4%, from 410 to 428 incidents. Crashes involving 'Improper or erratic lane changing' increased by 21.8% in count, from 101 to 123 incidents, and crashes due to 'Exceeded authorized speed' rose 37.5% from 32 to 44 incidents.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather and on dry roads. However, April 2026 saw a significant increase in crashes under adverse conditions compared to April 2025. The number of crashes during rainfall nearly doubled from 171 to 337, and their share of total crashes rose from 4.8% to 8.8%. Correspondingly, the count of crashes on wet road surfaces also almost doubled, jumping from 301 to 598. The proportion of crashes occurring in daylight remained stable at approximately 70% for both periods.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Ford (1,006 vehicles) and Chevrolet (881 vehicles as 'CHEV') leading in both April 2025 and April 2026. The number of vehicles from these top makes involved in crashes increased, mirroring the overall growth in crash volume. Analysis of person demographics reveals a notable shift in the age of individuals involved in collisions. The 21-25 age group saw a 13.3% increase in involvement, rising from 648 individuals in the prior year to 734 in the current period, a rate of increase higher than the overall growth in crashes.
Top Vehicle Makes (6,686 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
824 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,438 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 3,815
- Total persons involved: 6,975
- Total vehicles involved: 6,686
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: April 2026." Published September 9, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/april-2026-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: 2026-04-01 – 2026-04-30
Generated: September 9, 2026 · All rights reserved