Monthly Traffic Safety Analysis

4,684 CRASHES IN
IOWA, IA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, there were 4,684 traffic crashes across Iowa, a 7.5% increase from the 4,356 crashes recorded in May 2022. Despite the rise in total collisions, the number of fatalities decreased from 38 to 34. Total injuries saw a corresponding increase, rising from 1,507 in the prior year to 1,599 in the current period.

4,684

7.5%was 4,356

Total Crash Events

34

-10.5%was 38

Persons Killed

1,599

6.1%was 1,507

Persons Injured

30

-16.7%was 36

Fatal Crash Events

Note: "Persons Killed" (34) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash volumes in Iowa showed an upward trend in May 2023 compared to the same month in the prior year, with total crashes increasing by 7.5% from 4,356 to 4,684. While the number of fatalities decreased by 10.5% from 38 to 34, total injuries rose by 6.1%, from 1,507 to 1,599.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 20.0%

1

Cyclists Killed

Prior: 0%

31

Motorists Killed

Prior: 36-13.9%

0

Other Killed

Prior: 00.0%

30

Pedestrians Injured

Prior: 38-21.1%

38

Cyclists Injured

Prior: 2552.0%

1,528

Motorists Injured

Prior: 1,4396.2%

3

Other Injured

Prior: 5-40.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted slightly year-over-year. While the peak hour for collisions remained stable at 3 p.m. in both May 2023 (419 crashes) and May 2022 (412 crashes), the peak day changed. Wednesday became the most frequent day for crashes in May 2023 with 816 incidents, a shift from Tuesday in the prior year which saw 724 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a slight shift between May 2022 and May 2023. The fatal crash rate decreased from 0.83% to 0.64% of all crashes, with the absolute number of fatal crashes falling from 36 to 30. While the number of crashes resulting in serious, minor, and possible injuries all increased in count, their proportion of total crashes remained relatively stable, with a slight decrease in the share of possible injury crashes from 16.1% to 15.3%.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 34 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.6%
-16.7%prior 36
Serious Injury122serious injury crashes2.6%
4.3%prior 117
Minor Injury518minor injury crashes11.1%
10.4%prior 469
Possible Injury717possible injury crashes15.3%
2.3%prior 701
No Injury3,297no injury crashes70.4%
8.7%prior 3,033

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained consistent year-over-year, with 'Animal' (680 crashes) and 'Followed too close' (532 crashes) being the top two causes in May 2023. However, the count for several major factors increased. Crashes attributed to 'Followed too close' rose by 65 incidents, a 13.9% increase in count from the prior year's 467. Similarly, incidents involving 'Failure to Yield Right of Way: Making left turn' increased by 19.1% in count, from 199 to 237 crashes.

Officer-Reported Primary Contributing Cause

Animal680 (14.5%)6.3%prior 640
Followed too close532 (11.4%)13.9%prior 467
Other (explain in narrative): Other305 (6.5%)4.1%prior 293
FTYROW: From stop sign288 (6.1%)9.9%prior 262
Ran off road - left239 (5.1%)3.0%prior 232
FTYROW: Making left turn237 (5.1%)19.1%prior 199
Lost Control207 (4.4%)5.1%prior 197
Ran Traffic Signal153 (3.3%)7.0%prior 143
Driver Distraction: Other interior distraction150 (3.2%)-10.2%prior 167
Ran Stop Sign146 (3.1%)20.7%prior 121

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A higher proportion of crashes in May 2023 occurred during favorable conditions compared to the prior year. Crashes on dry road surfaces increased from 75.7% to 80.4% of the total, while those on wet surfaces decreased from 10.4% to 6.0%. Similarly, 73.0% of collisions happened in clear weather, up from 61.9% in May 2022, with a corresponding drop in the share of crashes during rainy conditions. Lighting conditions remained largely unchanged, with about 70% of crashes in both periods occurring in daylight.

Weather

Clear3,420 (83.0%)
26.9%prior 2,695
Cloudy496 (12.0%)
-38.5%prior 807
Rain163 (4.0%)
-42.0%prior 281
Fog, smoke, smog22 (0.5%)
266.7%prior 6
Severe Winds12 (0.3%)
-25.0%prior 16
Other (explain in narrative)3 (0.1%)
-62.5%prior 8
Blowing sand, soil, dirt2 (0.0%)
Freezing rain/drizzle2 (0.0%)
-80.0%prior 10
Sleet, hail1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight3,325 (80.3%)
9.5%prior 3,037
Dark - roadway lighted369 (8.9%)
-3.1%prior 381
Dark - roadway not lighted296 (7.1%)
8.8%prior 272
Dusk81 (2.0%)
-9.0%prior 89
Dawn55 (1.3%)
1.9%prior 54
Dark - unknown roadway lighting14 (0.3%)
-6.7%prior 15

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry3,765 (91.2%)
14.2%prior 3,296
Wet283 (6.9%)
-37.5%prior 453
Gravel74 (1.8%)
-7.5%prior 80
Other (explain in narrative)4 (0.1%)
Mud, dirt2 (0.0%)
-66.7%prior 6
Sand1 (0.0%)
Ice/frost1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet vehicles accounting for the highest volumes in both May 2023 and May 2022. The ranking of the top makes saw minimal change, with Jeep entering the top five in the current period. The age distribution of persons involved in crashes also showed stability, with all age groups seeing an increase in total persons involved that was proportional to the overall rise in crashes. The share of persons aged 65 and older involved in crashes saw a slight increase from 11.3% to 11.9% year-over-year.

Top Vehicle Makes (8,085 vehicles)

1
FORD1,309 (16.2%)
13.8%prior 1,150
2
CHEV1,126 (13.9%)
8.6%prior 1,037
3
TOYT414 (5.1%)
8.1%prior 383
4
CHEVROLET378 (4.7%)
10.9%prior 341
5
JEEP338 (4.2%)
8.7%prior 311
6
HOND294 (3.6%)
-6.4%prior 314
7
DODG273 (3.4%)
-4.9%prior 287
8
NISS269 (3.3%)
22.3%prior 220
9
GMC265 (3.3%)
-4.7%prior 278
10
KIA224 (2.8%)
14.9%prior 195

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

1,243 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (7,329 persons with recorded sex)

Male4,202 (57.3%)
11.2%prior 3,780
Female3,127 (42.7%)
7.1%prior 2,920

Source: Iowa Crash Data · ArcGIS Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,684
  • Total persons involved: 10,834
  • Total vehicles involved: 8,085

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: May 2023." Published September 9, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/may-2023-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

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