Yearly Traffic Safety Analysis

526 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Wapello County recorded 526 total crashes, a 1.9% increase from the 516 crashes documented in 2022. While the total number of crashes remained relatively stable, the number of resulting injuries rose significantly by 25.9%, from 170 in the prior year to 214 in the current year. Fatalities also increased, with 4 individuals killed in 2023 compared to 3 in 2022.

526

▲ 1.9%was 516

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

214

▲ 25.9%was 170

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Wapello County showed a slight increase in 2023 compared to the previous year. The total number of crashes rose by 1.9%, from 516 to 526. This increase was accompanied by a more substantial rise in crash consequences, with total injuries increasing by 25.9% and fatalities rising from 3 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 2↑100.0%

6

Pedestrians Injured

Prior: 4↑50.0%

4

Cyclists Injured

Prior: 1↑300.0%

204

Motorists Injured

Prior: 165↑23.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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. The peak day for crashes moved from Friday (86 incidents) in 2022 to Tuesday (92 incidents) in 2023. A more pronounced change occurred in the peak crash hour, which shifted from 3 p.m. in the prior year (41 crashes) to 7 a.m. in the current year (45 crashes). Crashes during the 7 a.m. hour increased by 87.5% year-over-year.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained constant at 3 in both 2023 and 2022, resulting in a nearly unchanged fatal crash rate of approximately 0.6%. However, the severity of non-fatal incidents increased, with serious injury crashes rising from 10 to 16 and minor injury crashes increasing from 46 to 71. Consequently, the share of crashes resulting in a serious injury grew from 1.9% of all incidents in 2022 to 3.0% in 2023.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
→0.0%prior 3
Serious Injury16serious injury crashes3%
↑60.0%prior 10
Minor Injury71minor injury crashes13.5%
↑54.3%prior 46
Possible Injury78possible injury crashes14.8%
↓-6.0%prior 83
No Injury358no injury crashes68.1%
↓-4.3%prior 374

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, with the count increasing from 92 to 97 incidents. The top five factors were largely consistent, including 'FTYROW: From stop sign' (increasing from 44 to 48 crashes) and 'Lost Control' (decreasing from 36 to 34 crashes). Notably, crashes attributed to 'FTYROW: Making left turn' saw a significant increase in count, rising from 18 in 2022 to 26 in 2023, while incidents involving 'Ran Stop Sign' decreased from 36 to 27.

Officer-Reported Primary Contributing Cause

Animal97 (18.4%)↑5.4%prior 92
FTYROW: From stop sign48 (9.1%)↑9.1%prior 44
Lost Control34 (6.5%)↓-5.6%prior 36
Followed too close33 (6.3%)↓-8.3%prior 36
Ran off road - left28 (5.3%)↓-6.7%prior 30
Ran Stop Sign27 (5.1%)↓-25.0%prior 36
FTYROW: Making left turn26 (4.9%)↑44.4%prior 18
Ran off road - straight20 (3.8%)↑122.2%prior 9
Driver Distraction: Other interior distraction19 (3.6%)↑72.7%prior 11
Operating vehicle in an reckless, erratic, careless, negligent manner18 (3.4%)↑5.9%prior 17

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in 2023 were more likely to occur in favorable conditions compared to 2022. The proportion of incidents happening in clear weather rose from 65.9% to 70.5%, and the share on dry road surfaces increased from 69.4% to 73.0%. Correspondingly, the raw count of crashes during adverse conditions like rain and snow, and on wet or icy roads, decreased from the prior year. The proportion of crashes occurring in daylight remained stable at approximately 57% in both periods.

Weather

Clear371 (82.6%)
↑9.1%prior 340
Cloudy42 (9.4%)
↓-37.3%prior 67
Rain15 (3.3%)
↓-16.7%prior 18
Snow8 (1.8%)
↓-42.9%prior 14
Freezing rain/drizzle6 (1.3%)
→0.0%prior 6
Fog, smoke, smog5 (1.1%)
Sleet, hail2 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight304 (67.6%)
↑4.1%prior 292
Dark - roadway lighted59 (13.1%)
↓-22.4%prior 76
Dark - roadway not lighted47 (10.4%)
↓-7.8%prior 51
Dawn16 (3.6%)
↑220.0%prior 5
Dusk12 (2.7%)
↑20.0%prior 10
Dark - unknown roadway lighting12 (2.7%)
↑9.1%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry384 (85.3%)
↑7.3%prior 358
Wet28 (6.2%)
↓-28.2%prior 39
Snow16 (3.6%)
↓-15.8%prior 19
Ice/frost15 (3.3%)
↓-25.0%prior 20
Gravel3 (0.7%)
↓-62.5%prior 8
Slush3 (0.7%)
Mud, dirt1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The vehicle makes involved in crashes saw some shifts in 2023. While Ford and Chevrolet remained the top two makes, the number of Fords involved decreased from 173 to 156, whereas Chevrolets (summing 'CHEV' and 'CHEVROLET' entries) increased from 161 to 178. The number of Jeeps involved in crashes more than doubled, from 21 to 50. Regarding persons involved, there was increased representation from the 16-20 age group (from 151 to 170) and the 35-44 age group (from 154 to 178).

Top Vehicle Makes (860 vehicles)

1
FORD156 (18.1%)
↓-9.8%prior 173
2
CHEV127 (14.8%)
↑5.8%prior 120
3
CHEVROLET51 (5.9%)
↑24.4%prior 41
4
JEEP50 (5.8%)
↑138.1%prior 21
5
DODG47 (5.5%)
↓-16.1%prior 56
6
TOYT45 (5.2%)
↓-25.0%prior 60
7
GMC34 (4%)
→0.0%prior 34
8
TOYOTA23 (2.7%)
↑27.8%prior 18
9
HOND22 (2.6%)
↑4.8%prior 21
10
BUIC19 (2.2%)
↑11.8%prior 17

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

109 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (790 persons with recorded sex)

Male494 (62.5%)
↑9.5%prior 451
Female296 (37.5%)
↓-9.5%prior 327

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 526
  • Total persons involved: 1,202
  • Total vehicles involved: 860

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-annual-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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