Yearly Traffic Safety Analysis

289 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Floyd County recorded 289 total crashes, a 3.0% decrease from the 298 crashes reported in 2021. The most significant year-over-year change was the reduction in traffic fatalities, which dropped from 4 in the prior period to 0 in the current period. Overall injuries also declined from 70 to 63.

289

-3.0%was 298

Total Crash Events

0

-100.0%was 4

Persons Killed

63

-10.0%was 70

Persons Injured

0

-100.0%was 3

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic collisions in Floyd County showed a slight downward trend from 2021 to 2022. Total crashes decreased by 3.0%, from 298 to 289 incidents. The number of people injured in these collisions also declined by 10.0% from 70 to 63, while fatalities were eliminated, falling from 4 to 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 4-100.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

60

Motorists Injured

Prior: 70-14.3%

1

Other Injured

Prior: 0%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between 2021 and 2022. While Monday remained the peak day for crashes in both periods (52 in 2021 vs. 48 in 2022), the peak hour for incidents moved three hours earlier, from 6 p.m. in the prior year to 3 p.m. in the current year. Crashes during the last two months of the year increased from 72 in 2021 to 83 in 2022.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes improved notably in 2022 compared to the prior year. Fatal crashes were eliminated, dropping from 3 incidents in 2021 to 0 in 2022, and the number of fatalities fell from 4 to 0. The count of serious injury crashes also decreased by 50%, from 6 to 3. Crashes resulting only in possible injuries increased from 23 to 31 incidents.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1%
-50.0%prior 6
Minor Injury21minor injury crashes7.3%
-8.7%prior 23
Possible Injury31possible injury crashes10.7%
34.8%prior 23
No Injury234no injury crashes81%
-3.7%prior 243

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, though the count fell from 114 in 2021 to 98 in 2022. 'Driving too fast for conditions' became a more prominent factor, with its count increasing from 13 to 22 incidents, making it the second-most cited cause in 2022. Conversely, incidents attributed to 'Ran off road - left' decreased from 20 to 9, and crashes involving 'Failure to yield from a stop sign' fell from 19 to 11.

Officer-Reported Primary Contributing Cause

Animal98 (33.9%)-14.0%prior 114
Driving too fast for conditions22 (7.6%)69.2%prior 13
Followed too close20 (6.9%)100.0%prior 10
Other (explain in narrative): Other14 (4.8%)75.0%prior 8
Lost Control13 (4.5%)30.0%prior 10
FTYROW: From stop sign11 (3.8%)-42.1%prior 19
Ran Stop Sign10 (3.5%)-16.7%prior 12
Ran off road - left9 (3.1%)-55.0%prior 20
FTYROW: At uncontrolled intersection9 (3.1%)-30.8%prior 13
Made improper turn9 (3.1%)-18.2%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions were largely consistent year-over-year, with most incidents in both periods occurring in daylight (152 in 2022 vs. 138 in 2021) and on dry roads (129 vs. 128). There was a notable increase in crashes on roads with ice or frost, which rose from 18 in 2021 to 26 in 2022. Crashes occurring in cloudy conditions also increased from 32 to 43 incidents.

Weather

Clear118 (59.6%)
-4.8%prior 124
Cloudy43 (21.7%)
34.4%prior 32
Snow10 (5.1%)
11.1%prior 9
Freezing rain/drizzle10 (5.1%)
11.1%prior 9
Rain8 (4.0%)
14.3%prior 7
Blowing Snow6 (3.0%)
Fog, smoke, smog1 (0.5%)
Other (explain in narrative)1 (0.5%)
Severe Winds1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight152 (77.2%)
10.1%prior 138
Dark - roadway lighted18 (9.1%)
5.9%prior 17
Dark - roadway not lighted17 (8.6%)
-26.1%prior 23
Dawn4 (2.0%)
-33.3%prior 6
Dusk4 (2.0%)
Dark - unknown roadway lighting2 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry129 (65.5%)
0.8%prior 128
Ice/frost26 (13.2%)
44.4%prior 18
Wet18 (9.1%)
50.0%prior 12
Snow16 (8.1%)
6.7%prior 15
Gravel6 (3.0%)
-50.0%prior 12
Slush2 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet and Ford leading in both 2021 and 2022. An analysis of the persons involved shows a shift in age demographics year-over-year. The 35-44 age group saw a significant increase in involvement, growing from 64 individuals in 2021 to 104 in 2022, becoming the largest group. Conversely, the 26-34 age group, which was the largest in the prior period with 95 individuals, saw its involvement decrease to 85.

Top Vehicle Makes (424 vehicles)

1
FORD78 (18.4%)
5.4%prior 74
2
CHEV67 (15.8%)
13.6%prior 59
3
DODG29 (6.8%)
52.6%prior 19
4
CHEVROLET24 (5.7%)
-25.0%prior 32
5
JEEP17 (4%)
13.3%prior 15
6
GMC15 (3.5%)
-37.5%prior 24
7
BUIC14 (3.3%)
27.3%prior 11
8
CHRY14 (3.3%)
40.0%prior 10
9
FREIGHTLINER12 (2.8%)
-7.7%prior 13
10
HOND11 (2.6%)
83.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (407 persons with recorded sex)

Male243 (59.7%)
22.7%prior 198
Female164 (40.3%)
26.2%prior 130

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 289
  • Total persons involved: 594
  • Total vehicles involved: 424

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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

ThatCarHitMe.com · An Injuria.ai Company

Floyd County, IA Crash Report — 2022 | ThatCarHitMe.com