Yearly Traffic Safety Analysis

171 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Louisa County, total crashes remained nearly stable, with 171 incidents in 2022 compared to 170 in 2021, a change of less than one percent. Despite the consistent crash volume, the human toll saw a notable decrease. The number of people injured fell by 24.4% from 45 to 34, and total fatalities were halved, dropping from two in the prior year to one in the current year.

171

▲ 0.6%was 170

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

34

▼ -24.4%was 45

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

The overall crash trend in Louisa County was stable year-over-year, with total collisions increasing by just one incident from 170 in 2021 to 171 in 2022. However, the severity of these crashes decreased. The number of reported injuries declined by 24.4% from 45 to 34, and total fatalities decreased from two to one.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

32

Motorists Injured

Prior: 45↓-28.9%

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

Temporal patterns for crashes in Louisa County showed some shifts between 2021 and 2022. While Friday remained a peak day for crashes in both years (31 in 2021, 30 in 2022), Tuesday also emerged as a high-frequency day in 2022 with 30 incidents. The most significant change was in the peak hour of crashes, which moved from the 6 p.m. evening hour in 2021 (17 crashes) to the 5 a.m. morning hour in 2022 (17 crashes).

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 in Louisa County decreased from 2021 to 2022. The number of fatal crashes was cut in half, from two in 2021 to one in 2022, and the fatal crash rate dropped from 1.2% to 0.6% of all crashes. The proportion of crashes resulting in any injury also fell, from 21.8% in the prior year (37 crashes) to 17.5% in the current year (30 crashes). Consequently, the share of property-damage-only crashes increased from 77.1% to 81.9%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
↓-50.0%prior 2
Serious Injury3serious injury crashes1.8%
↓-25.0%prior 4
Minor Injury12minor injury crashes7%
↓-25.0%prior 16
Possible Injury15possible injury crashes8.8%
↓-11.8%prior 17
No Injury140no injury crashes81.9%
↑6.9%prior 131

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 with animals remained the primary contributing factor for crashes in Louisa County in both periods, with the count increasing slightly from 89 incidents in 2021 to 92 in 2022. 'Lost Control' was the second-most cited factor in both years, though its count decreased from 13 to 10. A notable increase was observed in crashes attributed to 'Failure to Yield Right of Way while Making a Left Turn,' which tripled from 2 incidents in 2021 to 6 in 2022. Conversely, incidents involving 'Driver Distraction: Other interior distraction' decreased from 5 to 3.

Officer-Reported Primary Contributing Cause

Animal92 (53.8%)↑3.4%prior 89
Lost Control10 (5.8%)↓-23.1%prior 13
Ran off road - left8 (4.7%)↑60.0%prior 5
Other (explain in narrative): Other6 (3.5%)
FTYROW: Making left turn6 (3.5%)
Ran off road - straight6 (3.5%)↓-14.3%prior 7
Swerving/Evasive Action5 (2.9%)
Driver Distraction: Other interior distraction3 (1.8%)↓-40.0%prior 5
Driver Distraction: Exterior distraction3 (1.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (1.8%)

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

Road & Environmental Conditions

The environmental conditions surrounding crashes showed some year-over-year changes. In 2022, a greater proportion of crashes occurred during daylight hours (60.2%) compared to 2021 (54.9%). While the number of crashes on dry roads was identical at 68 in both years, incidents on adverse road surfaces increased. Specifically, crashes on roads with ice or frost more than tripled, rising from 2 in 2021 to 7 in 2022.

Weather

Clear65 (67.7%)
↑10.2%prior 59
Cloudy22 (22.9%)
→0.0%prior 22
Snow4 (4.2%)
Rain3 (3.1%)
Severe Winds1 (1.0%)
Blowing Snow1 (1.0%)

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

Lighting

Daylight59 (60.2%)
↑18.0%prior 50
Dark - roadway not lighted27 (27.6%)
↓-12.9%prior 31
Dark - roadway lighted8 (8.2%)
↑33.3%prior 6
Dawn3 (3.1%)
Dusk1 (1.0%)

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

Road Surface

Dry68 (70.1%)
→0.0%prior 68
Wet9 (9.3%)
↓-18.2%prior 11
Ice/frost7 (7.2%)
Gravel7 (7.2%)
→0.0%prior 7
Snow4 (4.1%)
Mud, dirt2 (2.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford, Chevrolet, and Dodge being the most common in both 2021 and 2022. Ford-made vehicles increased from 44 to 49, while the count for Chevrolet vehicles was stable at 41. The age demographics of persons involved in crashes shifted, with the 26-34 age group's share decreasing from 20.7% of all persons in 2021 to 13.6% in 2022. Conversely, the representation of younger drivers (16-20) and older individuals (65+) increased, rising from 9.9% to 12.1% and 10.5% to 13.6%, respectively.

Top Vehicle Makes (219 vehicles)

1
FORD49 (22.4%)
↑11.4%prior 44
2
CHEV34 (15.5%)
↑21.4%prior 28
3
DODG23 (10.5%)
↑43.8%prior 16
4
TOYT8 (3.7%)
↓-27.3%prior 11
5
DODGE8 (3.7%)
↑14.3%prior 7
6
HOND8 (3.7%)
↓-33.3%prior 12
7
GMC8 (3.7%)
↑33.3%prior 6
8
KIA7 (3.2%)
↑16.7%prior 6
9
CHEVROLET7 (3.2%)
↓-46.2%prior 13
10
BUIC5 (2.3%)

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

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

Sex Distribution (207 persons with recorded sex)

Male126 (60.9%)
↑38.5%prior 91
Female81 (39.1%)
↑30.6%prior 62

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: 171
  • Total persons involved: 330
  • Total vehicles involved: 219

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

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