Yearly Traffic Safety Analysis

282 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Fayette County recorded 282 total crashes, a 6.6% decrease from the 302 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities doubled from one in the prior year to two in the current period. The most significant change in crash circumstances was a 50% reduction in collisions occurring on roads with ice or frost.

282

▼ -6.6%was 302

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

68

▼ -18.1%was 83

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 traffic safety trends in Fayette County showed a decrease in total crashes and injuries year-over-year. Total crashes fell by 6.6%, from 302 in 2022 to 282 in 2023, while the number of people injured decreased by 18.1% from 83 to 68. However, the number of fatalities doubled, rising from one to two during the same period.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 0→%

68

Motorists Injured

Prior: 81↓-16.0%

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 in Fayette County showed both consistency and change year-over-year. Thursday remained the peak day for crashes in both 2022 (48 crashes) and 2023 (50 crashes). The peak hour for collisions shifted later into the evening, moving from 6 p.m. in 2022, which saw 30 crashes, to 9 p.m. in 2023, which recorded 23 crashes.

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

While total crashes decreased, the number of fatal crashes doubled from one in 2022 to two in 2023, increasing the fatal crash share from 0.3% to 0.7% of all collisions. Conversely, there was a notable reduction in the most severe non-fatal incidents, with serious injury crashes falling from 12 in the prior year to 4 in the current year. The proportion of crashes resulting in minor injuries saw a slight increase from 8.9% to 10.3% of total crashes.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
↑100.0%prior 1
Serious Injury4serious injury crashes1.4%
↓-66.7%prior 12
Minor Injury29minor injury crashes10.3%
↑7.4%prior 27
Possible Injury21possible injury crashes7.4%
↓-16.0%prior 25
No Injury226no injury crashes80.1%
↓-4.6%prior 237

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 animals remained the leading contributing factor in both periods, with the count increasing from 110 in 2022 to 123 in 2023. The second most common factor in 2022, 'Lost Control,' saw its count decrease by 42% from 26 crashes to 15. In 2023, 'Ran off road - left' became the second-ranked factor, with its incident count more than doubling from 9 to 20. Crashes attributed to 'Driving too fast for conditions' also decreased substantially, from 16 to 5.

Officer-Reported Primary Contributing Cause

Animal123 (43.6%)↑11.8%prior 110
Ran off road - left20 (7.1%)↑122.2%prior 9
Other (explain in narrative): Other17 (6%)↑21.4%prior 14
Lost Control15 (5.3%)↓-42.3%prior 26
Ran off road - straight14 (5%)↓-41.7%prior 24
FTYROW: From stop sign13 (4.6%)→0.0%prior 13
Ran Stop Sign11 (3.9%)↑83.3%prior 6
Exceeded authorized speed8 (2.8%)
Followed too close8 (2.8%)↓-27.3%prior 11
Driving too fast for conditions5 (1.8%)↓-68.8%prior 16

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

Road & Environmental Conditions

In both 2023 and 2022, the majority of crashes occurred in clear weather during daylight hours on dry roads. However, there was a marked decrease in crashes under adverse conditions in 2023 compared to the prior year. Collisions on roads with ice or frost were cut in half, dropping from 26 to 13, and crashes on snowy surfaces decreased from 15 to 8. Similarly, crashes in darkness on unlit roadways declined from 61 incidents in 2022 to 41 in 2023.

Weather

Clear125 (72.3%)
↓-11.3%prior 141
Cloudy33 (19.1%)
↓-17.5%prior 40
Rain5 (2.9%)
↓-16.7%prior 6
Snow4 (2.3%)
↓-60.0%prior 10
Blowing Snow3 (1.7%)
Freezing rain/drizzle1 (0.6%)
↓-85.7%prior 7
Fog, smoke, smog1 (0.6%)
Other (explain in narrative)1 (0.6%)

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

Lighting

Daylight112 (63.6%)
↓-15.2%prior 132
Dark - roadway not lighted41 (23.3%)
↓-32.8%prior 61
Dark - roadway lighted10 (5.7%)
↑11.1%prior 9
Dawn6 (3.4%)
↓-40.0%prior 10
Dusk6 (3.4%)
↑20.0%prior 5
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry124 (70.5%)
↓-9.5%prior 137
Gravel17 (9.7%)
↑54.5%prior 11
Ice/frost13 (7.4%)
↓-50.0%prior 26
Wet11 (6.3%)
↓-42.1%prior 19
Snow8 (4.5%)
↓-46.7%prior 15
Mud, dirt2 (1.1%)
Other (explain in narrative)1 (0.6%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford being the top two in both 2022 and 2023 and showing minimal change in their total counts. A significant shift occurred in the age distribution of persons involved in crashes, as the 65 and older age group saw its involvement increase from 74 individuals in 2022 to 105 in 2023, becoming the largest cohort. In contrast, the number of persons aged 16-20 involved in collisions decreased from 89 to 65.

Top Vehicle Makes (369 vehicles)

1
CHEV78 (21.1%)
↓-8.2%prior 85
2
FORD73 (19.8%)
↓-1.4%prior 74
3
CHEVROLET23 (6.2%)
↑9.5%prior 21
4
DODG22 (6%)
↓-12.0%prior 25
5
GMC19 (5.1%)
↓-9.5%prior 21
6
DODGE15 (4.1%)
↑150.0%prior 6
7
CHRY13 (3.5%)
↑116.7%prior 6
8
BUIC11 (3%)
↑57.1%prior 7
9
TOYOTA9 (2.4%)
10
TOYT8 (2.2%)
↓-38.5%prior 13

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

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

Sex Distribution (352 persons with recorded sex)

Male211 (59.9%)
↓-4.1%prior 220
Female141 (40.1%)
↓-3.4%prior 146

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: 282
  • Total persons involved: 562
  • Total vehicles involved: 369

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

ThatCarHitMe.com · An Injuria.ai Company