Monthly Traffic Safety Analysis

4,032 CRASHES IN
IOWA, IA
JULY 2023

All metrics benchmarked againstJuly 2022

In July 2023, there were 4,032 vehicle crashes statewide, representing a 0.9% increase from the 3,997 crashes recorded in July 2022. While overall crash volumes and outcomes were relatively stable, crashes involving a driver under the influence (DUI) saw a notable year-over-year decrease of 23.4%, falling from 197 incidents to 151.

4,032

▲ 0.9%was 3,997

Total Crash Events

42

▲ 2.4%was 41

Persons Killed

1,503

▲ 1.5%was 1,481

Persons Injured

33

▼ -8.3%was 36

Fatal Crash Events

Note: "Persons Killed" (42) counts individual fatalities across all crash events. "Fatal" in the severity table below (33) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends remained relatively stable between July 2022 and July 2023. Total crashes increased by a slight 0.9% from 3,997 to 4,032. In the same timeframe, total injuries rose by 1.5% from 1,481 to 1,503, and fatalities increased by one person, from 41 to 42.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1↑100.0%

1

Cyclists Killed

Prior: 1→0.0%

39

Motorists Killed

Prior: 39→0.0%

0

Other Killed

Prior: 0→0.0%

36

Pedestrians Injured

Prior: 24↑50.0%

40

Cyclists Injured

Prior: 43↓-7.0%

1,418

Motorists Injured

Prior: 1,410↑0.6%

9

Other Injured

Prior: 4↑125.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · 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 between the two periods. In July 2022, Friday was the day with the most crashes at 788, whereas in July 2023, the peak shifted to Monday with 690 crashes. The peak hour for collisions remained consistent at 4 p.m. in both periods, though the number of crashes during this hour increased from 328 to 369.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity was largely consistent year-over-year. The proportion of fatal crashes decreased slightly from 0.9% of all crashes in July 2022 to 0.8% in July 2023. Similarly, crashes resulting in serious injury accounted for 2.8% of incidents in the current period, down from 2.9% in the prior period. The share of crashes involving no injuries remained steady at approximately 67.4%.

Severity is per crash event (most severe injury). 33 fatal crash events resulted in 42 persons killed.

Outcome by Severity (Crash Events)

Fatal33fatal crashes0.8%
↓-8.3%prior 36
Serious Injury112serious injury crashes2.8%
↓-2.6%prior 115
Minor Injury512minor injury crashes12.7%
↑5.8%prior 484
Possible Injury658possible injury crashes16.3%
↓-0.8%prior 663
No Injury2,717no injury crashes67.4%
↑0.7%prior 2,699

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors remained consistent, though their counts shifted. Collisions involving an "Animal" were the leading cause in both periods, with counts decreasing from 478 to 457. "Followed too close" remained the second-most cited factor, with its count increasing from 408 to 429. Crashes attributed to a driver losing control increased from 182 to 201, while incidents involving running a stop sign decreased from 127 to 112.

Officer-Reported Primary Contributing Cause

Animal457 (11.3%)↓-4.4%prior 478
Followed too close429 (10.6%)↑5.1%prior 408
Ran off road - left223 (5.5%)↑3.7%prior 215
Other (explain in narrative): Other221 (5.5%)↓-14.7%prior 259
Lost Control201 (5%)↑10.4%prior 182
FTYROW: From stop sign195 (4.8%)↓-10.1%prior 217
FTYROW: Making left turn179 (4.4%)↓-5.3%prior 189
Ran Traffic Signal170 (4.2%)↑19.7%prior 142
Driver Distraction: Other interior distraction162 (4%)↑11.7%prior 145
Operating vehicle in an reckless, erratic, careless, negligent manner127 (3.1%)↓-17.0%prior 153

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions at the time of crashes were highly similar across both periods. In both July 2023 and July 2022, the vast majority of crashes occurred in clear weather (75.6% and 75.9%, respectively) and on dry road surfaces (82.5% and 83.1%, respectively). The proportion of crashes occurring during daylight hours saw a minor increase from 70.4% to 72.8% year-over-year, but there was no significant shift in crashes related to adverse conditions.

Weather

Clear3,049 (83.4%)
↑0.5%prior 3,034
Cloudy427 (11.7%)
↑2.2%prior 418
Rain149 (4.1%)
↑18.3%prior 126
Fog, smoke, smog24 (0.7%)
↑300.0%prior 6
Other (explain in narrative)3 (0.1%)
Severe Winds1 (0.0%)
Blowing sand, soil, dirt1 (0.0%)
Freezing rain/drizzle1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight2,936 (79.8%)
↑4.4%prior 2,813
Dark - roadway lighted329 (8.9%)
↓-9.4%prior 363
Dark - roadway not lighted276 (7.5%)
↓-3.5%prior 286
Dusk72 (2.0%)
↓-12.2%prior 82
Dawn52 (1.4%)
↑13.0%prior 46
Dark - unknown roadway lighting13 (0.4%)
↓-7.1%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry3,327 (90.7%)
↑0.2%prior 3,321
Wet226 (6.2%)
↑22.8%prior 184
Gravel95 (2.6%)
↑4.4%prior 91
Other (explain in narrative)9 (0.2%)
Mud, dirt9 (0.2%)
Sand1 (0.0%)
Water (standing or moving)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes showed a stable trend. Ford and Chevrolet were the most frequently involved makes in both July 2022 and July 2023, with Ford vehicle involvements increasing from 1,058 to 1,087. The overall rankings of the most common vehicle makes did not change significantly. An analysis of persons involved in crashes also showed a stable age distribution, with no notable year-over-year shifts in any age group's representation.

Top Vehicle Makes (6,969 vehicles)

1
FORD1,087 (15.6%)
↑2.7%prior 1,058
2
CHEV965 (13.8%)
↑10.3%prior 875
3
CHEVROLET351 (5%)
↓-16.0%prior 418
4
TOYT330 (4.7%)
↑8.9%prior 303
5
JEEP270 (3.9%)
↑3.8%prior 260
6
HOND247 (3.5%)
↓-1.6%prior 251
7
DODG237 (3.4%)
↑7.2%prior 221
8
GMC236 (3.4%)
↓-3.3%prior 244
9
NISS234 (3.4%)
↓-5.3%prior 247
10
NR198 (2.8%)
↓-4.8%prior 208

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

1,326 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,198 persons with recorded sex)

Male3,680 (59.4%)
↑1.9%prior 3,611
Female2,518 (40.6%)
→0.0%prior 2,517

Source: Iowa Crash Data · ArcGIS Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,032
  • Total persons involved: 9,487
  • Total vehicles involved: 6,969

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: July 2023." Published September 9, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-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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