Yearly Traffic Safety Analysis

298 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Floyd County recorded 298 total crashes, a 26.3% increase from the 236 crashes documented in 2020. The most significant year-over-year change was in crash fatalities, which rose from one in 2020 to four in 2021. Correspondingly, the number of fatal crashes increased from one to three during the same period.

298

▲ 26.3%was 236

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

70

▲ 4.5%was 67

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 Floyd County showed an upward trajectory from 2020 to 2021. Total crashes rose by 26.3%, from 236 to 298 incidents. While the number of people injured increased slightly from 67 to 70, the number of fatalities increased from one to four.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

70

Motorists Injured

Prior: 66↑6.1%

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 shifted between the two periods. In 2021, the peak day for crashes was Monday with 52 incidents, a change from Friday being the peak day in 2020 with 47 crashes. The peak hour also moved an hour later, from 5 p.m. in 2020 (19 crashes) to 6 p.m. in 2021, which saw a higher concentration of 28 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, with fatal crashes rising from one to three, and the fatality rate per 100 crashes increasing from 0.42 to 1.01. The number of serious injury crashes increased from five to six, while crashes involving possible injuries decreased from 25 to 23. The proportion of crashes resulting in no injuries grew from 78.4% in 2020 to 81.5% in 2021.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1%
↑200.0%prior 1
Serious Injury6serious injury crashes2%
↑20.0%prior 5
Minor Injury23minor injury crashes7.7%
↑15.0%prior 20
Possible Injury23possible injury crashes7.7%
↓-8.0%prior 25
No Injury243no injury crashes81.5%
↑31.4%prior 185

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 years, with the count increasing by 18.8% from 96 in 2020 to 114 in 2021. Crashes where a driver 'Ran off road - left' doubled in count from 10 to 20 incidents, moving from the third-ranked factor to the second. Incidents involving 'Failure to yield right of way from a stop sign' also more than doubled, rising from 9 to 19, to become the third most frequent cause in 2021.

Officer-Reported Primary Contributing Cause

Animal114 (38.3%)↑18.8%prior 96
Ran off road - left20 (6.7%)↑100.0%prior 10
FTYROW: From stop sign19 (6.4%)↑111.1%prior 9
FTYROW: At uncontrolled intersection13 (4.4%)↑116.7%prior 6
Driving too fast for conditions13 (4.4%)↑116.7%prior 6
Ran Stop Sign12 (4%)↑33.3%prior 9
Made improper turn11 (3.7%)
Lost Control10 (3.4%)↓-9.1%prior 11
Followed too close10 (3.4%)→0.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner8 (2.7%)↑14.3%prior 7

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

Road & Environmental Conditions

While most crashes in both years occurred in clear weather on dry roads, there was a notable increase in incidents under adverse conditions in 2021. The number of crashes during snow, freezing rain, or rain rose from 8 in 2020 to 28 in 2021. Similarly, collisions on icy, snowy, or wet road surfaces increased from 30 to 48 year-over-year. The proportion of crashes occurring in daylight remained relatively stable at 46.3% in 2021 compared to 44.5% in 2020.

Weather

Clear124 (66.7%)
↑17.0%prior 106
Cloudy32 (17.2%)
→0.0%prior 32
Snow9 (4.8%)
Freezing rain/drizzle9 (4.8%)
Rain7 (3.8%)
Fog, smoke, smog2 (1.1%)
Blowing Snow2 (1.1%)
Sleet, hail1 (0.5%)

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

Lighting

Daylight138 (73.4%)
↑31.4%prior 105
Dark - roadway not lighted23 (12.2%)
↑43.8%prior 16
Dark - roadway lighted17 (9.0%)
↓-15.0%prior 20
Dawn6 (3.2%)
Dusk4 (2.1%)

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

Road Surface

Dry128 (68.1%)
↑17.4%prior 109
Ice/frost18 (9.6%)
↑157.1%prior 7
Snow15 (8.0%)
↑66.7%prior 9
Gravel12 (6.4%)
↑140.0%prior 5
Wet12 (6.4%)
→0.0%prior 12
Slush3 (1.6%)

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 saw some shifts, with Ford and Chevrolet remaining the most common. The number of Fords involved rose from 51 to 74, and Chevrolets increased from 72 to 91 between 2020 and 2021. An analysis of persons involved shows a notable increase in the 26-34 and 65+ age groups; their representation grew from 14.8% to 16.7% and 11.9% to 14.4%, respectively. Conversely, the share of persons aged 16-20 involved in crashes decreased from 12.7% to 10.7%.

Top Vehicle Makes (432 vehicles)

1
FORD74 (17.1%)
↑45.1%prior 51
2
CHEV59 (13.7%)
↑9.3%prior 54
3
CHEVROLET32 (7.4%)
↑77.8%prior 18
4
GMC24 (5.6%)
↑84.6%prior 13
5
DODG19 (4.4%)
↑11.8%prior 17
6
JEEP15 (3.5%)
↑50.0%prior 10
7
CHRYSLER13 (3%)
8
FREIGHTLINER13 (3%)
↑160.0%prior 5
9
BUIC11 (2.5%)
↑10.0%prior 10
10
CHRY10 (2.3%)
↓-16.7%prior 12

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

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

Sex Distribution (328 persons with recorded sex)

Male198 (60.4%)
↑15.8%prior 171
Female130 (39.6%)
↓-3.0%prior 134

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: 298
  • Total persons involved: 569
  • Total vehicles involved: 432

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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