Yearly Traffic Safety Analysis

266 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Fayette County recorded 266 total crashes, an 8.0% decrease from the 289 crashes reported in 2020. While total and fatal crashes declined, the number of people injured in collisions increased from 75 to 88. The most notable change was a 50% reduction in fatal crashes, from four in the prior year to two in the current year.

266

▼ -8.0%was 289

Total Crash Events

4

Persons Killed

88

▲ 17.3%was 75

Persons Injured

2

▼ -50.0%was 4

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Fayette County show a decrease in total incidents from 2020 to 2021. Total crashes fell by 8.0%, from 289 to 266. However, despite this decline, the number of injuries rose by 17.3% year-over-year, while the number of fatalities held steady at four.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 4→0.0%

0

Other Killed

Prior: 0→0.0%

87

Motorists Injured

Prior: 75↑16.0%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. The busiest day for crashes moved from Monday (56 crashes) in 2020 to Thursday (48 crashes) in 2021. The peak hour for collisions also shifted two hours earlier, from 6 p.m. in 2020 (24 crashes) to 4 p.m. in 2021 (21 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, with a decrease in fatal incidents but an increase in injury-related crashes. The number of fatal crashes fell by 50%, from 4 in 2020 to 2 in 2021, and the fatal crash rate dropped from 1.4% to 0.8% of all crashes. Conversely, the proportion of crashes resulting in any level of injury increased from 19.7% of all incidents in 2020 to 26.3% in 2021.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
↓-50.0%prior 4
Serious Injury12serious injury crashes4.5%
↑50.0%prior 8
Minor Injury26minor injury crashes9.8%
↓-7.1%prior 28
Possible Injury32possible injury crashes12%
↑52.4%prior 21
No Injury194no injury crashes72.9%
↓-14.9%prior 228

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, though the count decreased by 23.6% from 110 crashes in 2020 to 84 in 2021. 'Lost Control' was the second-most cited factor in both years, with its count increasing by 38.1% from 21 to 29 incidents. 'Ran off road - straight' became the third-leading factor in 2021 with 17 crashes, replacing 'Ran off road - left' which had 19 crashes in 2020.

Officer-Reported Primary Contributing Cause

Animal84 (31.6%)↓-23.6%prior 110
Lost Control29 (10.9%)↑38.1%prior 21
Ran off road - straight17 (6.4%)↑88.9%prior 9
Driving too fast for conditions16 (6%)↑33.3%prior 12
FTYROW: From stop sign15 (5.6%)↓-11.8%prior 17
Other (explain in narrative): Other13 (4.9%)↓-7.1%prior 14
Followed too close8 (3%)↑14.3%prior 7
Other (explain in narrative): No improper action7 (2.6%)
Improper Backing7 (2.6%)↑40.0%prior 5
Ran off road - left7 (2.6%)↓-63.2%prior 19

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather and on dry roads were more frequent in 2021 than in 2020, with counts rising from 129 to 155 and 129 to 146, respectively. The most significant shift in conditions was related to lighting, where crashes on unlit dark roadways increased from 34 to 51. In contrast, incidents during daylight hours saw a slight decrease from 134 to 130.

Weather

Clear155 (76.0%)
↑20.2%prior 129
Cloudy27 (13.2%)
↓-20.6%prior 34
Snow7 (3.4%)
↓-22.2%prior 9
Rain6 (2.9%)
↓-14.3%prior 7
Fog, smoke, smog3 (1.5%)
Freezing rain/drizzle3 (1.5%)
↓-50.0%prior 6
Blowing Snow2 (1.0%)
Other (explain in narrative)1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight130 (63.1%)
↓-3.0%prior 134
Dark - roadway not lighted51 (24.8%)
↑50.0%prior 34
Dark - roadway lighted11 (5.3%)
↑10.0%prior 10
Dawn7 (3.4%)
Dusk6 (2.9%)
↓-14.3%prior 7
Dark - unknown roadway lighting1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry146 (71.2%)
↑13.2%prior 129
Wet21 (10.2%)
↑40.0%prior 15
Ice/frost14 (6.8%)
↑16.7%prior 12
Snow13 (6.3%)
↓-23.5%prior 17
Gravel8 (3.9%)
↓-42.9%prior 14
Other (explain in narrative)2 (1.0%)
Mud, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet and Ford vehicles accounting for the highest numbers in both 2020 and 2021. An analysis of persons involved shows a shift in age demographics; the proportion of individuals aged 16-20 increased from 14.2% of all persons in 2020 to 18.0% in 2021. In contrast, the representation of the 55-64 age group decreased from 15.3% to 9.2% year-over-year.

Top Vehicle Makes (370 vehicles)

1
FORD84 (22.7%)
↑12.0%prior 75
2
CHEV55 (14.9%)
↓-43.3%prior 97
3
CHEVROLET32 (8.6%)
↑3.2%prior 31
4
DODG14 (3.8%)
↓-6.7%prior 15
5
BUIC14 (3.8%)
↑16.7%prior 12
6
DODGE12 (3.2%)
↑50.0%prior 8
7
GMC12 (3.2%)
↓-36.8%prior 19
8
JEEP10 (2.7%)
↓-23.1%prior 13
9
CHRYSLER9 (2.4%)
↑12.5%prior 8
10
PONTIAC6 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (293 persons with recorded sex)

Male179 (61.1%)
↓-24.2%prior 236
Female114 (38.9%)
↓-18.0%prior 139

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 266
  • Total persons involved: 500
  • Total vehicles involved: 370

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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