Yearly Traffic Safety Analysis

181 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Franklin County, total traffic crashes remained relatively stable, increasing slightly from 177 in 2020 to 181 in 2021, a change of 2.3%. While the overall crash volume was steady, the number of fatalities doubled from one to two. Conversely, the total number of injuries reported saw a significant decrease of 20.4%, falling from 49 in the prior year to 39 in the current period.

181

▲ 2.3%was 177

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

39

▼ -20.4%was 49

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data indicates a stable trend in the total number of crashes, with a minor 2.3% increase from 177 to 181 incidents. However, the severity of outcomes shifted, as fatalities increased from one to two, while total injuries decreased from 49 to 39. This suggests a slight increase in crash frequency but a reduction in non-fatal injury outcomes.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 1↑100.0%

39

Motorists Injured

Prior: 48↓-18.8%

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

The temporal patterns of crashes shifted between the two periods. In 2021, the peak day for crashes was Saturday with 34 incidents, a change from 2020 when Wednesday was the peak day with 36 crashes. The peak hour also shifted later into the evening, from 4 p.m. in 2020 (16 crashes) to 6 p.m. in 2021 (16 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 showed a mixed change year-over-year. The number of fatal crashes doubled from one in 2020 to two in 2021, and the number of serious injury crashes increased from two to three. Despite this, the total number of people injured fell from 49 to 39, driven by a decrease in minor and possible injury crashes, which fell from 15 to 10 and 24 to 14, respectively. Consequently, the share of no-injury crashes grew from 76.3% to 84.0% of all incidents.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
↑100.0%prior 1
Serious Injury3serious injury crashes1.7%
↑50.0%prior 2
Minor Injury10minor injury crashes5.5%
↓-33.3%prior 15
Possible Injury14possible injury crashes7.7%
↓-41.7%prior 24
No Injury152no injury crashes84%
↑12.6%prior 135

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 with animals remained the leading contributing factor in both years, with the count of such incidents increasing by 25.5% from 47 crashes in 2020 to 59 in 2021. 'Lost Control' was the second-most cited factor in both periods, rising from 19 to 22 incidents. The count of crashes attributed to 'Driving too fast for conditions' decreased from 8 in the prior year to 6 in the current year.

Officer-Reported Primary Contributing Cause

Animal59 (32.6%)↑25.5%prior 47
Lost Control22 (12.2%)↑15.8%prior 19
Ran off road - left10 (5.5%)↑25.0%prior 8
FTYROW: From stop sign9 (5%)↑28.6%prior 7
Other (explain in narrative): Other9 (5%)↓-43.8%prior 16
FTYROW: At uncontrolled intersection8 (4.4%)↑60.0%prior 5
Other (explain in narrative): No improper action8 (4.4%)↑33.3%prior 6
Ran off road - straight8 (4.4%)→0.0%prior 8
Driving too fast for conditions6 (3.3%)↓-25.0%prior 8
Driver Distraction: Inattentive/lost in thought5 (2.8%)

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

Road & Environmental Conditions

Crash conditions remained broadly consistent year-over-year, with clear weather and dry roads accounting for the majority of incidents in both periods. In 2021, 90 crashes occurred on dry roads and 90 in clear weather, compared to 85 and 86, respectively, in 2020. Crashes on roads with ice or frost decreased from 19 in 2020 to 13 in 2021, while incidents during freezing rain or drizzle doubled from 4 to 8.

Weather

Clear90 (67.7%)
↑4.7%prior 86
Cloudy18 (13.5%)
↑12.5%prior 16
Freezing rain/drizzle8 (6.0%)
Snow5 (3.8%)
↓-37.5%prior 8
Rain4 (3.0%)
↓-50.0%prior 8
Blowing Snow3 (2.3%)
↓-57.1%prior 7
Severe Winds3 (2.3%)
Fog, smoke, smog1 (0.8%)
Other (explain in narrative)1 (0.8%)

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

Lighting

Daylight78 (58.6%)
↓-2.5%prior 80
Dark - roadway not lighted39 (29.3%)
↑8.3%prior 36
Dark - roadway lighted11 (8.3%)
↓-15.4%prior 13
Dawn3 (2.3%)
↓-40.0%prior 5
Dusk2 (1.5%)

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

Road Surface

Dry90 (67.2%)
↑5.9%prior 85
Ice/frost13 (9.7%)
↓-31.6%prior 19
Wet11 (8.2%)
↓-26.7%prior 15
Snow11 (8.2%)
→0.0%prior 11
Gravel8 (6.0%)
↑60.0%prior 5
Slush1 (0.7%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes during both years. The number of Ford vehicles remained constant at 40, while Chevrolet vehicles increased from 46 to 62. The demographic distribution of persons involved in crashes also remained similar, with the 26-34 age group being the largest in both 2020 (64 persons) and 2021 (66 persons). A notable change was seen in the 45-54 age group, whose involvement decreased from 58 persons to 39.

Top Vehicle Makes (252 vehicles)

1
FORD40 (15.9%)
→0.0%prior 40
2
CHEV39 (15.5%)
↑39.3%prior 28
3
CHEVROLET23 (9.1%)
↑27.8%prior 18
4
DODG11 (4.4%)
↓-15.4%prior 13
5
GMC9 (3.6%)
↓-10.0%prior 10
6
FREIGHTLINER8 (3.2%)
↓-42.9%prior 14
7
TOYOTA8 (3.2%)
↑33.3%prior 6
8
TOYT7 (2.8%)
→0.0%prior 7
9
KIA7 (2.8%)
10
JEEP6 (2.4%)
↓-50.0%prior 12

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

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

Sex Distribution (207 persons with recorded sex)

Male137 (66.2%)
↓-5.5%prior 145
Female70 (33.8%)
↓-23.1%prior 91

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: 181
  • Total persons involved: 324
  • Total vehicles involved: 252

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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