Yearly Traffic Safety Analysis

170 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Louisa County, total traffic crashes decreased from 206 in 2020 to 170 in 2021, a 17.5% reduction. Despite this overall decline, the number of total fatalities and injuries remained unchanged at 2 and 45, respectively, for both years. A notable shift occurred in the timing of collisions, with the peak crash hour moving from 5 a.m. in 2020 to 6 p.m. in 2021.

170

▼ -17.5%was 206

Total Crash Events

2

Persons Killed

45

Persons Injured

2

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

Overall, traffic collisions in Louisa County saw a downward trend year-over-year, decreasing by 17.5% from 206 incidents in 2020 to 170 in 2021. However, the severity of outcomes remained stable, with both total fatalities (2) and total injuries (45) holding constant between the two periods.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

45

Motorists Injured

Prior: 45→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 temporal patterns of crashes shifted between 2020 and 2021. The most frequent day for crashes moved from Sunday (35 incidents) in 2020 to Friday (31 incidents) in 2021. Similarly, the peak hour for collisions changed from 5 a.m. in the prior year, which saw 19 crashes, to 6 p.m. in the current year, with 17 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

While the number of fatal crashes remained constant at two for both years, the fatal crash rate per 100 crashes increased from 0.97 in 2020 to 1.18 in 2021 due to the lower overall crash volume. The proportion of crashes resulting in serious injuries decreased from 2.9% to 2.4% year-over-year. Conversely, crashes involving minor injuries saw a proportional increase, rising from 5.3% of all crashes in 2020 to 9.4% in 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.2%
→0.0%prior 2
Serious Injury4serious injury crashes2.4%
↓-33.3%prior 6
Minor Injury16minor injury crashes9.4%
↑45.5%prior 11
Possible Injury17possible injury crashes10%
↓-15.0%prior 20
No Injury131no injury crashes77.1%
↓-21.6%prior 167

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 by 19.8% from 111 in 2020 to 89 in 2021. 'Lost Control' was the second-most cited factor in both years, with its count falling from 19 to 13 crashes. Similarly, 'Ran off road - straight' ranked third in both periods, dropping from 11 incidents in 2020 to 7 in 2021.

Officer-Reported Primary Contributing Cause

Animal89 (52.4%)↓-19.8%prior 111
Lost Control13 (7.6%)↓-31.6%prior 19
Ran off road - straight7 (4.1%)↓-36.4%prior 11
Driver Distraction: Other interior distraction5 (2.9%)↓-16.7%prior 6
Ran off road - left5 (2.9%)↓-16.7%prior 6
Other (explain in narrative): Other4 (2.4%)↓-20.0%prior 5
FTYROW: From stop sign4 (2.4%)↓-42.9%prior 7
Ran off road - right3 (1.8%)
Driving too fast for conditions3 (1.8%)
FTYROW: From driveway3 (1.8%)

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

Road & Environmental Conditions

The number of crashes reported on dry roads decreased from 85 in 2020 to 68 in 2021, consistent with the overall drop in collisions. Crashes occurring on roads with ice or frost saw a notable reduction, falling from 10 incidents in 2020 to just 2 in 2021. Regarding lighting, collisions in daylight conditions decreased from 73 to 50, while crashes on unlit dark roadways increased from 27 to 31.

Weather

Clear59 (64.8%)
↓-27.2%prior 81
Cloudy22 (24.2%)
↓-18.5%prior 27
Rain4 (4.4%)
Sleet, hail1 (1.1%)
Snow1 (1.1%)
Blowing sand, soil, dirt1 (1.1%)
Blowing Snow1 (1.1%)
Fog, smoke, smog1 (1.1%)
Freezing rain/drizzle1 (1.1%)

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

Lighting

Daylight50 (54.9%)
↓-31.5%prior 73
Dark - roadway not lighted31 (34.1%)
↑14.8%prior 27
Dark - roadway lighted6 (6.6%)
↓-40.0%prior 10
Dawn4 (4.4%)
↓-55.6%prior 9

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

Road Surface

Dry68 (73.9%)
↓-20.0%prior 85
Wet11 (12.0%)
↓-26.7%prior 15
Gravel7 (7.6%)
→0.0%prior 7
Snow3 (3.3%)
Ice/frost2 (2.2%)
↓-80.0%prior 10
Slush1 (1.1%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year, with Ford, Chevrolet, and Dodge being the most frequent in both 2020 and 2021. The number of persons involved in crashes from the 35-44 age group saw a significant decrease, dropping from 86 individuals in 2020 to 42 in 2021. In contrast, the 26-34 age group saw an increase in representation, growing from 55 individuals in 2020 to 61 in 2021.

Top Vehicle Makes (214 vehicles)

1
FORD44 (20.6%)
↓-18.5%prior 54
2
CHEV28 (13.1%)
↓-31.7%prior 41
3
DODG16 (7.5%)
↑33.3%prior 12
4
CHEVROLET13 (6.1%)
↑30.0%prior 10
5
HOND12 (5.6%)
6
TOYT11 (5.1%)
↓-8.3%prior 12
7
JEEP7 (3.3%)
↓-41.7%prior 12
8
CHRY7 (3.3%)
↓-36.4%prior 11
9
DODGE7 (3.3%)
→0.0%prior 7
10
GMC6 (2.8%)
↓-40.0%prior 10

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 (153 persons with recorded sex)

Male91 (59.5%)
↓-41.3%prior 155
Female62 (40.5%)
↓-29.5%prior 88

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: 170
  • Total persons involved: 294
  • Total vehicles involved: 214

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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