Yearly Traffic Safety Analysis

136 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Lyon County, total traffic crashes decreased by 6.9% from 146 in 2019 to 136 in 2020. This period saw a significant reduction in crash severity, with fatalities dropping from 4 to 1 and total injuries declining from 52 to 39. One of the most notable shifts was a fourfold increase in crashes involving a driver under the influence of alcohol, which rose from 2 incidents in 2019 to 8 in 2020.

136

▼ -6.8%was 146

Total Crash Events

1

▼ -75.0%was 4

Persons Killed

39

▼ -25.0%was 52

Persons Injured

1

▼ -75.0%was 4

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 · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Lyon County showed improvement from 2019 to 2020. The total number of crashes fell by 6.9%, from 146 to 136. More significantly, the number of people killed in crashes decreased from 4 to 1, and the number of people injured fell from 52 to 39.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

1

Motorists Killed

Prior: 3↓-66.7%

1

Pedestrians Injured

Prior: 0→%

38

Motorists Injured

Prior: 52↓-26.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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 2020, the peak day for crashes was Thursday with 25 incidents, a change from Tuesday (26 crashes) in 2019. The peak hour for collisions also moved from the 7 a.m. morning commute in 2019 (13 crashes) to the 5 p.m. evening commute in 2020 (13 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased from 2019 to 2020. The number of fatal crashes fell from 4 to 1, causing the fatal crash rate to decline from 2.74% to 0.74%. The proportion of collisions resulting in any type of injury (serious, minor, or possible) also decreased from 28.8% in 2019 to 21.4% in 2020. Consequently, the share of crashes with no reported injuries rose from 68.5% to 77.9%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
↓-75.0%prior 4
Serious Injury3serious injury crashes2.2%
→0.0%prior 3
Minor Injury13minor injury crashes9.6%
↓-31.6%prior 19
Possible Injury13possible injury crashes9.6%
↓-35.0%prior 20
No Injury106no injury crashes77.9%
↑6.0%prior 100

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with an animal remained the top contributing factor in both years, with the count of such incidents increasing by 41.2% from 34 in 2019 to 48 in 2020. In contrast, crashes attributed to "Driving too fast for conditions" and "Lost Control" both decreased; their counts fell from 19 each in 2019 to 12 and 10, respectively, in 2020. Incidents involving a driver running a stop sign tripled from 3 to 9.

Officer-Reported Primary Contributing Cause

Animal48 (35.3%)↑41.2%prior 34
Driving too fast for conditions12 (8.8%)↓-36.8%prior 19
Ran off road - straight11 (8.1%)→0.0%prior 11
Lost Control10 (7.4%)↓-47.4%prior 19
Ran Stop Sign9 (6.6%)
Followed too close6 (4.4%)↓-53.8%prior 13
Driver Distraction: Other interior distraction5 (3.7%)
FTYROW: From stop sign4 (2.9%)↓-42.9%prior 7
Other (explain in narrative): Other4 (2.9%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a shift in the conditions under which crashes occurred. The proportion of crashes on adverse road surfaces like snow, ice, or wet pavement decreased from 28.8% of all crashes in 2019 to 21.3% in 2020. Crashes in clear weather also made up a smaller share of the total, falling from 58.9% in 2019 to 48.5% in 2020. The proportion of collisions occurring in darkness on unlit roadways remained consistent at just over 20% in both years.

Weather

Clear66 (67.3%)
↓-23.3%prior 86
Cloudy10 (10.2%)
↓-41.2%prior 17
Snow6 (6.1%)
→0.0%prior 6
Blowing Snow5 (5.1%)
Freezing rain/drizzle5 (5.1%)
↓-28.6%prior 7
Rain3 (3.1%)
↓-40.0%prior 5
Fog, smoke, smog2 (2.0%)
Severe Winds1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight61 (61.6%)
↓-18.7%prior 75
Dark - roadway not lighted28 (28.3%)
↓-6.7%prior 30
Dark - roadway lighted6 (6.1%)
↓-33.3%prior 9
Dawn3 (3.0%)
↓-50.0%prior 6
Dusk1 (1.0%)
↓-83.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry63 (63.6%)
↓-19.2%prior 78
Snow13 (13.1%)
↑18.2%prior 11
Ice/frost10 (10.1%)
↓-47.4%prior 19
Gravel6 (6.1%)
Wet6 (6.1%)
↓-50.0%prior 12
Other (explain in narrative)1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

Chevrolet and Ford vehicles were the top two makes involved in crashes during both periods. The demographic profile of persons involved in crashes showed a notable change, with the 35-44 age group becoming the most represented in 2020 (49 people), a shift from the 65+ age group in 2019 (47 people). The number of individuals aged 65 and older involved in crashes saw a substantial decrease from 47 in 2019 to 28 in 2020.

Top Vehicle Makes (180 vehicles)

1
FORD37 (20.6%)
↑12.1%prior 33
2
CHEV21 (11.7%)
↓-41.7%prior 36
3
CHEVROLET19 (10.6%)
↓-17.4%prior 23
4
GMC16 (8.9%)
↑166.7%prior 6
5
JEEP7 (3.9%)
↑40.0%prior 5
6
DODG7 (3.9%)
↑40.0%prior 5
7
CHRY5 (2.8%)
8
DODGE4 (2.2%)
↓-20.0%prior 5
9
HOND4 (2.2%)
↓-33.3%prior 6
10
SUBARU4 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

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

Sex Distribution (167 persons with recorded sex)

Male104 (62.3%)
↓-16.8%prior 125
Female63 (37.7%)
↓-7.4%prior 68

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 136
  • Total persons involved: 265
  • Total vehicles involved: 180

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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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