Yearly Traffic Safety Analysis

100 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Keokuk County recorded 100 vehicle crashes, a 23.5% increase from the 81 crashes reported in 2022. The most significant year-over-year change was the occurrence of 4 fatalities in 2023, whereas none were recorded in the prior year. Total injuries also rose from 29 to 53 during this period.

100

▲ 23.5%was 81

Total Crash Events

4

Persons Killed

53

▲ 82.8%was 29

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

Crash trends in Keokuk County showed a notable increase from 2022 to 2023. The total number of crashes rose by 23.5%, from 81 to 100. This increase was accompanied by a more significant rise in negative outcomes, with total injuries climbing 82.8% from 29 to 53 and fatalities increasing from zero to four.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

53

Motorists Injured

Prior: 29↑82.8%

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. In 2023, Saturday was the distinct peak day with 21 crashes, compared to 2022 when Thursday and Saturday shared the peak with 14 crashes each. The peak hour for crashes moved from 6 p.m. in 2022 (9 crashes) to 7 a.m. in 2023 (12 crashes), a six-fold increase in incidents for that specific hour.

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

Crash severity worsened significantly in 2023 compared to the prior year. The county recorded 4 fatal crashes, representing 4% of all incidents, up from zero fatal crashes in 2022. While the count of serious injury crashes decreased slightly from 5 to 4, the number of persons injured overall rose from 29 to 53. Crashes resulting in minor injuries increased from 10 to 13.

Outcome by Severity (Crash Events)

Fatal4fatal crashes4%
Serious Injury4serious injury crashes4%
↓-20.0%prior 5
Minor Injury13minor injury crashes13%
↑30.0%prior 10
Possible Injury10possible injury crashes10%
→0.0%prior 10
No Injury69no injury crashes69%
↑23.2%prior 56

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 of such incidents increasing from 28 in 2022 to 36 in 2023. 'Ran off road - straight' became the second most common factor in 2023, more than doubling in count from 5 to 11 incidents. 'Lost Control' incidents also rose from 8 to 10, and crashes attributed to 'FTYROW: From stop sign' increased from 1 to 4.

Officer-Reported Primary Contributing Cause

Animal36 (36%)↑28.6%prior 28
Ran off road - straight11 (11%)↑120.0%prior 5
Lost Control10 (10%)↑25.0%prior 8
FTYROW: From stop sign4 (4%)
Followed too close4 (4%)↓-20.0%prior 5
Ran off road - left4 (4%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (4%)
Driver Distraction: Reaching for object(s)/fallen object(s)3 (3%)
Driver Distraction: Exterior distraction3 (3%)
Ran off road - right3 (3%)

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

Road & Environmental Conditions

While crashes in daylight on dry roads remained the most common scenario, their overall share of incidents decreased in 2023. Crashes on wet roads more than doubled, increasing from 5 incidents in 2022 to 12 in 2023. Similarly, collisions in dark, unlighted conditions rose from 15 to 22. Despite the overall increase in total crashes, the number of incidents during clear weather remained stable, going from 39 to 38.

Weather

Clear38 (55.9%)
↓-2.6%prior 39
Cloudy17 (25.0%)
↑21.4%prior 14
Rain4 (5.9%)
Freezing rain/drizzle3 (4.4%)
Fog, smoke, smog2 (2.9%)
Snow1 (1.5%)
Other (explain in narrative)1 (1.5%)
Severe Winds1 (1.5%)
Blowing Snow1 (1.5%)

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

Lighting

Daylight40 (58.8%)
↑14.3%prior 35
Dark - roadway not lighted22 (32.4%)
↑46.7%prior 15
Dawn3 (4.4%)
Dark - roadway lighted2 (2.9%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (1.5%)

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

Road Surface

Dry45 (66.2%)
↑2.3%prior 44
Wet12 (17.6%)
↑140.0%prior 5
Ice/frost3 (4.4%)
Gravel3 (4.4%)
Snow3 (4.4%)
Mud, dirt1 (1.5%)
Slush1 (1.5%)

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

Vehicles & Demographics

The number of vehicles involved in crashes grew from 112 in 2022 to 130 in 2023. Ford vehicles saw a notable increase in involvement, rising from 16 to 25, making it the top individual make in 2023. An analysis of persons involved shows a substantial increase in younger age groups; the number of individuals aged 0-15 rose from 2 to 22, and those aged 16-20 increased from 18 to 30.

Top Vehicle Makes (130 vehicles)

1
FORD25 (19.2%)
↑56.3%prior 16
2
CHEV23 (17.7%)
↑9.5%prior 21
3
CHEVROLET9 (6.9%)
↑80.0%prior 5
4
GMC8 (6.2%)
5
DODG7 (5.4%)
↑16.7%prior 6
6
TOYT7 (5.4%)
7
RAM6 (4.6%)
8
JEEP5 (3.8%)
9
BUIC4 (3.1%)
10
HOND3 (2.3%)

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

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

Sex Distribution (128 persons with recorded sex)

Male83 (64.8%)
↑9.2%prior 76
Female45 (35.2%)
↑36.4%prior 33

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: 100
  • Total persons involved: 221
  • Total vehicles involved: 130

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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