Yearly Traffic Safety Analysis

156 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Chickasaw County recorded 156 total crashes, a 16.4% increase from the 134 crashes reported in 2020. During this period, the number of fatalities doubled from one to two, and total injuries remained nearly stable at 46 compared to 45 in the prior year. The most notable change was the increase in crashes resulting in serious injuries, which rose from 3 incidents in 2020 to 7 in 2021.

156

▲ 16.4%was 134

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

46

▲ 2.2%was 45

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

Crash trends in Chickasaw County show an increase year-over-year, with total collisions rising from 134 in 2020 to 156 in 2021. The number of fatal crashes doubled from one to two, resulting in two fatalities compared to one in the prior year. The total number of people injured remained nearly unchanged, increasing by one from 45 to 46.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 1↑100.0%

46

Motorists Injured

Prior: 44↑4.5%

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 2020 and 2021. The peak day for collisions moved from a tie between Thursday and Friday (22 crashes each) in 2020 to Saturday (28 crashes) in 2021. The peak crash hour also shifted slightly earlier, moving from 6 p.m. in the prior year (17 crashes) to 5 p.m. in the current year (19 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

Crash severity increased in 2021 compared to the previous year. The number of fatal crashes doubled from one to two, and the corresponding fatal crash rate rose from 0.75 to 1.28 per 100 crashes. Crashes resulting in serious injuries also more than doubled, increasing from 3 incidents (2.2% of total) in 2020 to 7 incidents (4.5% of total) in 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.3%
↑100.0%prior 1
Serious Injury7serious injury crashes4.5%
↑133.3%prior 3
Minor Injury15minor injury crashes9.6%
↓-6.3%prior 16
Possible Injury12possible injury crashes7.7%
↑33.3%prior 9
No Injury120no injury crashes76.9%
↑14.3%prior 105

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 an animal remained the top contributing factor in both periods, though the count of these incidents decreased from 62 in 2020 to 56 in 2021. Several other factors saw notable increases in their crash counts year-over-year. Incidents where a driver ran a stop sign increased from one to five, and crashes attributed to an inattentive or distracted driver rose from two to five. Conversely, crashes due to a loss of control decreased from eight in 2020 to six in 2021.

Officer-Reported Primary Contributing Cause

Animal56 (35.9%)↓-9.7%prior 62
Other (explain in narrative): Other8 (5.1%)↑14.3%prior 7
Ran off road - left7 (4.5%)
Other (explain in narrative): No improper action6 (3.8%)
Lost Control6 (3.8%)↓-25.0%prior 8
Ran Stop Sign5 (3.2%)
Driver Distraction: Inattentive/lost in thought5 (3.2%)
FTYROW: From stop sign5 (3.2%)
Ran off road - straight4 (2.6%)↓-42.9%prior 7
Swerving/Evasive Action4 (2.6%)

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

Road & Environmental Conditions

In both 2021 and 2020, the majority of crashes occurred in clear weather and during daylight on dry roads. However, there was a notable increase in crashes on adverse road surfaces year-over-year. The number of crashes on roads with ice or frost doubled from 5 in 2020 to 10 in 2021. Similarly, crashes on snow-covered roads increased from 6 to 9 over the same period.

Weather

Clear86 (77.5%)
↑36.5%prior 63
Cloudy12 (10.8%)
↓-7.7%prior 13
Snow4 (3.6%)
Freezing rain/drizzle4 (3.6%)
Fog, smoke, smog2 (1.8%)
Rain1 (0.9%)
↓-80.0%prior 5
Severe Winds1 (0.9%)
Blowing Snow1 (0.9%)

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

Lighting

Daylight75 (67.0%)
↑21.0%prior 62
Dark - roadway not lighted20 (17.9%)
↑53.8%prior 13
Dark - roadway lighted9 (8.0%)
↑28.6%prior 7
Dawn4 (3.6%)
Dark - unknown roadway lighting3 (2.7%)
Dusk1 (0.9%)

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

Road Surface

Dry79 (70.5%)
↑27.4%prior 62
Ice/frost10 (8.9%)
↑100.0%prior 5
Snow9 (8.0%)
↑50.0%prior 6
Gravel7 (6.3%)
↑40.0%prior 5
Wet7 (6.3%)
↓-12.5%prior 8

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, Chevrolet and Ford, remained consistent across both years. The age distribution of persons involved in crashes, however, shifted significantly. The number of people in the 16-20 age group more than doubled from 15 in 2020 to 38 in 2021. Conversely, involvement for the 26-34 age group was more than halved, dropping from 68 people to 29. The 35-44 age group also saw a substantial increase in persons involved, rising from 27 in 2020 to 49 in 2021.

Top Vehicle Makes (223 vehicles)

1
CHEV44 (19.7%)
↑22.2%prior 36
2
FORD38 (17%)
↑52.0%prior 25
3
CHEVROLET21 (9.4%)
↓-12.5%prior 24
4
DODG12 (5.4%)
↑140.0%prior 5
5
GMC11 (4.9%)
↓-31.3%prior 16
6
BUIC6 (2.7%)
7
CHRY6 (2.7%)
8
JEEP6 (2.7%)
↓-14.3%prior 7
9
HYUN5 (2.2%)
10
DODGE5 (2.2%)
↓-16.7%prior 6

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

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

Sex Distribution (169 persons with recorded sex)

Male99 (58.6%)
↑11.2%prior 89
Female70 (41.4%)
↓-12.5%prior 80

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: 156
  • Total persons involved: 299
  • Total vehicles involved: 223

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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