Yearly Traffic Safety Analysis

83 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Shelby County, total traffic crashes increased by 7.8%, rising from 77 in 2020 to 83 in 2021. While the number of injuries remained unchanged at 30, the most notable year-over-year shift was a decrease in traffic fatalities from one in 2020 to zero in 2021.

83

▲ 7.8%was 77

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

30

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

The overall trend shows a slight increase in crash volume in Shelby County. Total crashes rose from 77 in 2020 to 83 in 2021. Despite this increase, the number of resulting injuries held steady at 30 for both years, and fatalities were eliminated, dropping from one to zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

30

Motorists Injured

Prior: 30→0.0%

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

The timing of crashes showed some changes year-over-year. The peak day for crashes shifted from Wednesday in 2020, which saw 20 incidents, to Tuesday in 2021 with 17 incidents. The peak hour for collisions remained consistent at 3 p.m. in both periods, though the volume in that hour increased from 12 crashes in 2020 to 14 in 2021.

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 outcomes improved from 2020 to 2021. The county recorded zero fatal crashes in 2021, down from one the previous year. The count of serious injury crashes also decreased, falling from 5 incidents (6.5% of all crashes) in 2020 to 2 incidents (2.4%) in 2021. Conversely, the number of crashes resulting in no injuries increased from 54 to 61 over the same period.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.4%
↓-60.0%prior 5
Minor Injury11minor injury crashes13.3%
↑37.5%prior 8
Possible Injury9possible injury crashes10.8%
→0.0%prior 9
No Injury61no injury crashes73.5%
↑13.0%prior 54

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 for crashes shifted between 2020 and 2021. In 2021, 'Lost Control' and 'Animal' were the most cited factors, each contributing to 10 crashes, an increase from 8 and 6 crashes respectively in 2020. The top factor from 2020, 'Driving too fast for conditions,' saw its count decrease from 9 crashes to 4. Incidents involving 'Ran Stop Sign' more than doubled, increasing from 3 crashes in 2020 to 7 in 2021.

Officer-Reported Primary Contributing Cause

Lost Control10 (12%)↑25.0%prior 8
Animal10 (12%)↑66.7%prior 6
Other (explain in narrative): Other9 (10.8%)↑50.0%prior 6
Ran Stop Sign7 (8.4%)
FTYROW: From stop sign5 (6%)↓-37.5%prior 8
Ran off road - straight5 (6%)
Driving too fast for conditions4 (4.8%)↓-55.6%prior 9
Made improper turn4 (4.8%)
Exceeded authorized speed3 (3.6%)
Swerving/Evasive Action2 (2.4%)

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 2020 and 2021, the majority of crashes occurred in clear weather and on dry road surfaces. However, there was a notable increase in crashes taking place in darkness on unlit roads, which rose from 7 incidents in 2020 to 13 in 2021. Crashes on roads with ice or frost also increased, from 2 in the prior year to 6 in the current year.

Weather

Clear56 (76.7%)
↑9.8%prior 51
Cloudy14 (19.2%)
↑55.6%prior 9
Snow2 (2.7%)
Blowing Snow1 (1.4%)

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

Lighting

Daylight53 (72.6%)
↓-1.9%prior 54
Dark - roadway not lighted13 (17.8%)
↑85.7%prior 7
Dark - roadway lighted3 (4.1%)
↓-57.1%prior 7
Dusk2 (2.7%)
Dawn1 (1.4%)
Dark - unknown roadway lighting1 (1.4%)

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

Road Surface

Dry52 (71.2%)
↑2.0%prior 51
Gravel7 (9.6%)
↑16.7%prior 6
Ice/frost6 (8.2%)
Wet5 (6.8%)
Snow2 (2.7%)
↓-75.0%prior 8
Mud, dirt1 (1.4%)

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

Vehicles & Demographics

Ford and Chevrolet remained the two most common vehicle makes involved in collisions, but their ranking changed; the count of Ford vehicles increased from 27 to 36, while Chevrolet vehicles decreased from 29 to 22. Analysis of persons involved in crashes shows a higher proportion of individuals in the 65+ age group, which accounted for 18.7% of persons in 2021 compared to 15.9% in 2020.

Top Vehicle Makes (131 vehicles)

1
FORD36 (27.5%)
↑33.3%prior 27
2
CHEV14 (10.7%)
↓-36.4%prior 22
3
CHEVROLET8 (6.1%)
↑14.3%prior 7
4
DODG8 (6.1%)
↑60.0%prior 5
5
DODGE6 (4.6%)
6
GMC5 (3.8%)
↓-16.7%prior 6
7
KEWT3 (2.3%)
8
NISSAN3 (2.3%)
9
CHRY3 (2.3%)
10
SUBA3 (2.3%)

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

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

Sex Distribution (108 persons with recorded sex)

Male63 (58.3%)
↓-17.1%prior 76
Female45 (41.7%)
↑12.5%prior 40

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: 83
  • Total persons involved: 166
  • Total vehicles involved: 131

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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