Monthly Traffic Safety Analysis

3,754 CRASHES IN
IOWA, IA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, there were 3,754 total crashes across Iowa, representing a 2.5% decrease from the 3,850 crashes recorded in April 2022. Despite the overall decline in collisions, the most notable year-over-year shift was an 18.2% increase in traffic fatalities, which rose from 22 to 26. The total number of injuries remained relatively stable, with a slight increase from 1,285 to 1,296.

3,754

▼ -2.5%was 3,850

Total Crash Events

26

▲ 18.2%was 22

Persons Killed

1,296

▲ 0.9%was 1,285

Persons Injured

24

▲ 20.0%was 20

Fatal Crash Events

Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Statewide traffic crashes saw a modest year-over-year decrease of 2.5%, falling from 3,850 in April 2022 to 3,754 in April 2023. However, this decrease in total volume was accompanied by a concerning rise in fatalities, which increased by 18.2% from 22 to 26. The number of total injuries remained nearly unchanged, increasing by less than 1% from 1,285 to 1,296.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 2→0.0%

0

Cyclists Killed

Prior: 0→0.0%

24

Motorists Killed

Prior: 20↑20.0%

0

Other Killed

Prior: 0→0.0%

19

Pedestrians Injured

Prior: 26↓-26.9%

22

Cyclists Injured

Prior: 11↑100.0%

1,250

Motorists Injured

Prior: 1,242↑0.6%

5

Other Injured

Prior: 6↓-16.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The primary temporal patterns for crashes were consistent year-over-year. Friday remained the day with the most crashes in both April 2023 (619 crashes) and April 2022 (791 crashes). The peak time for collisions shifted slightly later in the afternoon, moving from the 3 p.m. hour in 2022 (324 crashes) to the 4 p.m. hour in 2023 (347 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased in April 2023 compared to the prior year. The number of fatal crashes rose from 20 to 24, and the count of serious injury crashes increased from 81 to 96. This shift is reflected in the crash proportions, where the share of fatal crashes increased from 0.5% to 0.6% of all collisions, and the share of no-injury crashes decreased from 70.7% to 69.5%.

Severity is per crash event (most severe injury). 24 fatal crash events resulted in 26 persons killed.

Outcome by Severity (Crash Events)

Fatal24fatal crashes0.6%
↑20.0%prior 20
Serious Injury96serious injury crashes2.6%
↑18.5%prior 81
Minor Injury395minor injury crashes10.5%
↑5.6%prior 374
Possible Injury629possible injury crashes16.8%
↓-3.8%prior 654
No Injury2,610no injury crashes69.5%
↓-4.1%prior 2,721

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

The top two contributing factors for crashes were 'Followed too close' and 'Animal' in both periods. The count of crashes attributed to following too closely increased slightly from 424 to 439, while animal-related crashes decreased from 420 to 390. A notable change was observed in crashes involving 'Improper or erratic lane changing', which saw its count increase by 26% from 73 incidents in 2022 to 92 in 2023.

Officer-Reported Primary Contributing Cause

Followed too close439 (11.7%)↑3.5%prior 424
Animal390 (10.4%)↓-7.1%prior 420
Other (explain in narrative): Other226 (6%)↓-18.7%prior 278
FTYROW: From stop sign215 (5.7%)↓-3.2%prior 222
Ran off road - left205 (5.5%)↓-7.2%prior 221
Lost Control192 (5.1%)↓-8.1%prior 209
FTYROW: Making left turn167 (4.4%)↑0.6%prior 166
Ran Traffic Signal160 (4.3%)↓-5.3%prior 169
Operating vehicle in an reckless, erratic, careless, negligent manner133 (3.5%)↑11.8%prior 119
Ran off road - straight131 (3.5%)↑4.0%prior 126

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in April 2023 occurred under significantly better environmental conditions than in the previous year. The number of crashes in clear weather increased from 2,096 to 2,598, while crashes during rain fell sharply from 366 to 113. Correspondingly, collisions on dry roads increased from 2,648 to 3,033, while those on wet surfaces dropped from 704 to 254. The proportion of crashes happening in daylight remained relatively stable year-over-year.

Weather

Clear2,598 (76.1%)
↑24.0%prior 2,096
Cloudy611 (17.9%)
↓-26.7%prior 834
Rain113 (3.3%)
↓-69.1%prior 366
Freezing rain/drizzle25 (0.7%)
↓-45.7%prior 46
Snow23 (0.7%)
↓-41.0%prior 39
Severe Winds18 (0.5%)
↓-51.4%prior 37
Blowing Snow12 (0.4%)
↑71.4%prior 7
Other (explain in narrative)6 (0.2%)
Fog, smoke, smog4 (0.1%)
↓-90.5%prior 42
Sleet, hail4 (0.1%)
↓-20.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight2,644 (77.3%)
↑0.5%prior 2,631
Dark - roadway lighted392 (11.5%)
↓-7.5%prior 424
Dark - roadway not lighted240 (7.0%)
↓-17.8%prior 292
Dusk89 (2.6%)
↑39.1%prior 64
Dawn44 (1.3%)
↓-33.3%prior 66
Dark - unknown roadway lighting13 (0.4%)
↓-31.6%prior 19

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry3,033 (88.7%)
↑14.5%prior 2,648
Wet254 (7.4%)
↓-63.9%prior 704
Gravel75 (2.2%)
↑27.1%prior 59
Ice/frost23 (0.7%)
↓-39.5%prior 38
Slush13 (0.4%)
→0.0%prior 13
Snow13 (0.4%)
→0.0%prior 13
Mud, dirt8 (0.2%)
Other (explain in narrative)1 (0.0%)
↓-80.0%prior 5
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes for both periods, although the total counts for both decreased in April 2023 compared to April 2022. The number of Ford vehicles in crashes fell from 1,067 to 980, while the combined count for Chevrolet vehicles ('CHEV' and 'CHEVROLET') also declined. The age distribution of persons involved in collisions showed no significant year-over-year shifts, with all age brackets maintaining a similar proportional representation.

Top Vehicle Makes (6,582 vehicles)

1
FORD980 (14.9%)
↓-8.2%prior 1,067
2
CHEV867 (13.2%)
↓-14.9%prior 1,019
3
CHEVROLET369 (5.6%)
↑4.2%prior 354
4
TOYT306 (4.6%)
↓-8.4%prior 334
5
HOND296 (4.5%)
↑8.8%prior 272
6
JEEP277 (4.2%)
↑6.1%prior 261
7
NISS238 (3.6%)
↑7.2%prior 222
8
GMC236 (3.6%)
↑19.8%prior 197
9
DODG229 (3.5%)
↓-20.2%prior 287
10
KIA186 (2.8%)
↓-1.6%prior 189

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

1,090 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,935 persons with recorded sex)

Male3,316 (55.9%)
↓-3.0%prior 3,419
Female2,619 (44.1%)
↓-0.4%prior 2,630

Source: Iowa Crash Data · ArcGIS Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,754
  • Total persons involved: 8,752
  • Total vehicles involved: 6,582

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 2023." Published September 9, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/april-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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