Yearly Traffic Safety Analysis

84 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Mitchell County recorded 84 total vehicle crashes, a 20% increase from the 70 crashes documented in 2020. While the number of fatalities remained stable at two, total injuries decreased slightly from 34 to 31. A notable shift occurred in contributing factors, with failure to yield at an uncontrolled intersection increasing by 160% to become the leading cause of crashes, rising from 5 incidents in 2020 to 13 in 2021.

84

▲ 20.0%was 70

Total Crash Events

2

Persons Killed

31

▼ -8.8%was 34

Persons Injured

2

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

Crash trends in Mitchell County showed an increase in 2021 compared to the previous year. The total number of crashes rose by 20%, from 70 in 2020 to 84 in 2021. Despite the rise in collisions, the number of resulting fatalities held steady at two, and the total number of injuries saw a slight decrease from 34 to 31.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

31

Motorists Injured

Prior: 32↓-3.1%

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 in Mitchell County shifted between 2020 and 2021. The most frequent day for crashes moved from Monday (16 incidents) in the prior year to Friday (17 incidents) in the current year. The peak hour for collisions also shifted slightly, from 5 p.m. in 2020 (8 crashes) to a three-way tie at 2 p.m., 3 p.m., and 4 p.m. in 2021 (8 crashes each).

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 the total number of fatal crashes remained unchanged at two in both 2021 and 2020, the overall severity of crashes trended downward. The proportion of crashes resulting in serious injuries decreased from 10.0% in 2020 (7 crashes) to 4.8% in 2021 (4 crashes). Similarly, minor injury crashes fell from 14.3% to 8.3% of the total. Conversely, crashes involving possible injury or no injury increased as a share of all incidents, with no-injury crashes rising from 55.7% to 65.5% of the total.

Outcome by Severity (Crash Events)

Fatal2fatal crashes2.4%
→0.0%prior 2
Serious Injury4serious injury crashes4.8%
↓-42.9%prior 7
Minor Injury7minor injury crashes8.3%
↓-30.0%prior 10
Possible Injury16possible injury crashes19%
↑33.3%prior 12
No Injury55no injury crashes65.5%
↑41.0%prior 39

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 leading contributing factors for crashes shifted significantly between 2020 and 2021. 'Failure to yield at an uncontrolled intersection' became the top factor in 2021, with its count increasing by 160% from 5 to 13 incidents. The previous year's leading cause, 'Lost Control,' saw its count decrease from 13 to 11 crashes, moving it to the second-ranked position. Crashes involving animals also saw a notable increase in count, rising from 3 to 8 incidents year-over-year.

Officer-Reported Primary Contributing Cause

FTYROW: At uncontrolled intersection13 (15.5%)↑160.0%prior 5
Lost Control11 (13.1%)↓-15.4%prior 13
Animal8 (9.5%)
Other (explain in narrative): Other8 (9.5%)
Ran off road - left6 (7.1%)
FTYROW: From yield sign5 (6%)
Driving too fast for conditions5 (6%)↓-28.6%prior 7
Ran off road - straight4 (4.8%)
Ran Stop Sign4 (4.8%)
FTYROW: From stop sign4 (4.8%)↓-20.0%prior 5

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

Road & Environmental Conditions

Driving conditions for most crashes were clear and dry in both periods, but there was a notable increase in crashes occurring under adverse winter conditions and at dawn. Crashes on snowy road surfaces doubled from 6 in 2020 to 12 in 2021, and incidents on icy or frosty roads increased from 5 to 8. While most crashes occurred in daylight in both years (51 in 2021 and 50 in 2020), collisions during dawn hours saw a sharp rise from just 1 incident in 2020 to 11 in 2021.

Weather

Clear54 (68.4%)
↑17.4%prior 46
Cloudy17 (21.5%)
↑41.7%prior 12
Rain2 (2.5%)
Snow2 (2.5%)
Other (explain in narrative)1 (1.3%)
Fog, smoke, smog1 (1.3%)
Blowing Snow1 (1.3%)
Sleet, hail1 (1.3%)

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

Lighting

Daylight51 (63.7%)
↑2.0%prior 50
Dawn11 (13.8%)
Dark - roadway not lighted10 (12.5%)
↓-16.7%prior 12
Dark - roadway lighted6 (7.5%)
Dusk2 (2.5%)

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

Road Surface

Dry55 (68.8%)
↑17.0%prior 47
Snow12 (15.0%)
↑100.0%prior 6
Ice/frost8 (10.0%)
↑60.0%prior 5
Wet3 (3.8%)
↓-40.0%prior 5
Gravel2 (2.5%)

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 saw a shift in rankings between the two years. In 2021, Ford became the most common make with 29 vehicles involved, up from 12 in the prior year. Chevrolet, the top make in 2020 with 27 vehicles, was involved in 25 crashes in 2021. The age distribution of persons involved in crashes remained largely consistent, with individuals in the 16-20 and 35-44 age groups being the most frequently involved in both periods.

Top Vehicle Makes (134 vehicles)

1
FORD29 (21.6%)
↑141.7%prior 12
2
CHEV13 (9.7%)
↓-18.8%prior 16
3
CHEVROLET12 (9%)
↑9.1%prior 11
4
DODG8 (6%)
5
GMC6 (4.5%)
↓-14.3%prior 7
6
JEEP6 (4.5%)
→0.0%prior 6
7
BUICK5 (3.7%)
8
CHRY5 (3.7%)
9
DODGE3 (2.2%)
↓-40.0%prior 5
10
HONDA3 (2.2%)

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

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

Sex Distribution (114 persons with recorded sex)

Male70 (61.4%)
↑11.1%prior 63
Female44 (38.6%)
↑29.4%prior 34

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: 84
  • Total persons involved: 172
  • Total vehicles involved: 134

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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