Yearly Traffic Safety Analysis

238 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Jefferson County, traffic crashes increased from 177 in 2020 to 238 in 2021, a 34.5% rise. This increase was accompanied by a 39.6% rise in injuries, from 53 to 74. The most notable year-over-year shift was the increase in crashes involving animals, which grew by 49.1% from 57 incidents in 2020 to 85 in 2021.

238

▲ 34.5%was 177

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

74

▲ 39.6%was 53

Persons Injured

0

▼ -100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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, Jefferson County experienced a significant upward trend in traffic collisions in 2021 compared to the prior year. Total crashes rose by 34.5%, from 177 to 238. Similarly, the number of people injured in these incidents increased by 39.6%, from 53 to 74, even as the single fatality from 2020 was not repeated in 2021.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

2

Pedestrians Injured

Prior: 2→0.0%

1

Cyclists Injured

Prior: 3↓-66.7%

71

Motorists Injured

Prior: 48↑47.9%

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 timing of crashes shifted between the two periods. In 2021, the peak day for crashes was Saturday with 39 incidents, closely followed by Friday with 38. This contrasts with 2020, when Tuesday and Saturday shared the peak with 29 crashes each. The peak hour also moved earlier, from 5 p.m. in 2020 (25 crashes) to 3 p.m. in 2021 (20 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

While total crashes increased, the severity distribution saw mixed changes. The county recorded zero fatal crashes in 2021, an improvement from the one fatal crash in 2020. The number of serious injury crashes increased from 6 to 8, though their share of all crashes remained stable at 3.4%. Crashes resulting in possible injury increased in both count (from 24 to 37) and proportion (from 13.6% to 15.5% of all crashes).

Outcome by Severity (Crash Events)

Serious Injury8serious injury crashes3.4%
↑33.3%prior 6
Minor Injury21minor injury crashes8.8%
↑16.7%prior 18
Possible Injury37possible injury crashes15.5%
↑54.2%prior 24
No Injury172no injury crashes72.3%
↑34.4%prior 128

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

The primary contributing factors remained consistent in ranking, but their counts increased. Collisions with animals were the leading factor in both years, growing by 49.1% from 57 crashes in 2020 to 85 in 2021. The second-ranked factor, failure to yield from a stop sign, also increased by 38.5% from 13 to 18 incidents. Crashes attributed to following too closely saw a 55.6% increase in count, rising from 9 to 14 incidents.

Officer-Reported Primary Contributing Cause

Animal85 (35.7%)↑49.1%prior 57
FTYROW: From stop sign18 (7.6%)↑38.5%prior 13
Lost Control14 (5.9%)↑16.7%prior 12
Followed too close14 (5.9%)↑55.6%prior 9
Ran off road - left12 (5%)↑140.0%prior 5
Driving too fast for conditions9 (3.8%)
Ran off road - straight9 (3.8%)↑12.5%prior 8
Other (explain in narrative): Other7 (2.9%)→0.0%prior 7
Ran Traffic Signal6 (2.5%)
FTYROW: Making left turn5 (2.1%)

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

Road & Environmental Conditions

Year-over-year, a larger proportion of crashes occurred in adverse conditions. In 2021, 19.7% of crashes happened on non-dry road surfaces (wet, snow, ice), compared to 11.9% in 2020. Similarly, crashes during non-clear weather conditions rose from 12.4% of the total in 2020 to 16.8% in 2021. Conversely, the share of crashes occurring in darkness decreased from 25.4% in 2020 to 17.2% in 2021.

Weather

Clear113 (69.3%)
↑11.9%prior 101
Cloudy27 (16.6%)
↑145.5%prior 11
Rain10 (6.1%)
↑66.7%prior 6
Snow7 (4.3%)
Fog, smoke, smog2 (1.2%)
Freezing rain/drizzle2 (1.2%)
Blowing Snow2 (1.2%)

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

Lighting

Daylight119 (72.1%)
↑54.5%prior 77
Dark - roadway not lighted25 (15.2%)
↓-3.8%prior 26
Dusk8 (4.8%)
↓-20.0%prior 10
Dark - roadway lighted7 (4.2%)
↓-22.2%prior 9
Dawn5 (3.0%)
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry117 (71.3%)
↑13.6%prior 103
Wet14 (8.5%)
↑100.0%prior 7
Snow13 (7.9%)
Ice/frost11 (6.7%)
Gravel6 (3.7%)
→0.0%prior 6
Mud, dirt2 (1.2%)
Slush1 (0.6%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes showed a consistent pattern, with Ford and Chevrolet remaining the most common in both 2020 and 2021, with counts for both increasing year-over-year. An analysis of persons involved in crashes shows a notable shift in age demographics. The number of individuals in the 35-44 age group increased from 31 to 52, and the 45-54 age group grew from 44 to 62. Meanwhile, involvement of persons in the 16-20 age group decreased from 54 to 48.

Top Vehicle Makes (342 vehicles)

1
FORD60 (17.5%)
↑39.5%prior 43
2
CHEV43 (12.6%)
↑59.3%prior 27
3
CHEVROLET27 (7.9%)
↑50.0%prior 18
4
TOYT16 (4.7%)
↓-5.9%prior 17
5
JEEP14 (4.1%)
↑75.0%prior 8
6
GMC14 (4.1%)
↑75.0%prior 8
7
DODG13 (3.8%)
↑30.0%prior 10
8
HOND12 (3.5%)
↑33.3%prior 9
9
TOYO11 (3.2%)
↑57.1%prior 7
10
TOYOTA11 (3.2%)
↑83.3%prior 6

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

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

Sex Distribution (257 persons with recorded sex)

Male140 (54.5%)
↑2.2%prior 137
Female117 (45.5%)
↑8.3%prior 108

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: 238
  • Total persons involved: 455
  • Total vehicles involved: 342

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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