Yearly Traffic Safety Analysis

317 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Winneshiek County, total traffic crashes decreased by 15.5% from 375 in 2019 to 317 in 2020. This overall reduction was accompanied by a significant year-over-year drop in negative outcomes. The most notable shift was a 60% decrease in fatalities, which fell from 5 in the prior period to 2 in the current period.

317

▼ -15.5%was 375

Total Crash Events

2

▼ -60.0%was 5

Persons Killed

82

▼ -20.4%was 103

Persons Injured

2

▼ -60.0%was 5

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

Trend Summary

Traffic safety trends in Winneshiek County showed a notable improvement year-over-year. The total number of crashes fell from 375 to 317, a 15.5% decrease. Concurrently, the number of persons injured declined by 20.4% from 103 to 82, and fatalities dropped from 5 to 2.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 5↓-60.0%

1

Pedestrians Injured

Prior: 1→0.0%

1

Cyclists Injured

Prior: 0→%

80

Motorists Injured

Prior: 102↓-21.6%

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 Friday with 49 incidents, a change from 2019 when Saturday was the peak day with 69 crashes. The peak hour for collisions moved slightly later, from the 4 p.m. hour (32 crashes) in the prior period to the 5 p.m. hour (33 crashes) in the current period.

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

The severity of crashes decreased from 2019 to 2020. Fatal crashes fell from 5 to 2, reducing their share of all crashes from 1.3% to 0.6%. The number of serious injury crashes also declined from 14 to 10. The overall proportion of crashes involving any level of injury (Fatal, Serious, Minor, or Possible) remained relatively stable, accounting for 21.1% of crashes in 2020 compared to 22.1% in 2019.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
↓-60.0%prior 5
Serious Injury10serious injury crashes3.2%
↓-28.6%prior 14
Minor Injury33minor injury crashes10.4%
↓-2.9%prior 34
Possible Injury22possible injury crashes6.9%
↓-26.7%prior 30
No Injury250no injury crashes78.9%
↓-14.4%prior 292

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 involving an animal remained the leading contributing factor in both periods, though the count decreased from 138 incidents in 2019 to 131 in 2020. 'Lost Control' was the second-most cited factor in both years, with its count increasing slightly from 31 to 34. Crashes attributed to 'Driving too fast for conditions' saw a notable decrease in count, falling from 23 incidents in 2019 to 16 in 2020.

Officer-Reported Primary Contributing Cause

Animal131 (41.3%)↓-5.1%prior 138
Lost Control34 (10.7%)↑9.7%prior 31
Ran off road - straight17 (5.4%)↓-22.7%prior 22
Driving too fast for conditions16 (5%)↓-30.4%prior 23
Followed too close14 (4.4%)↑55.6%prior 9
Ran off road - left9 (2.8%)↓-35.7%prior 14
Failed to keep in proper lane7 (2.2%)
FTYROW: From stop sign7 (2.2%)↓-50.0%prior 14
Driver Distraction: Other interior distraction6 (1.9%)↓-40.0%prior 10
Other (explain in narrative): Other5 (1.6%)↓-54.5%prior 11

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

Road & Environmental Conditions

The environmental conditions at the time of crashes were broadly consistent year-over-year. In both 2020 and 2019, clear weather and dry road surfaces were the most common conditions, each accounting for approximately 45% of all crashes. There was a minor shift in lighting conditions, with the proportion of crashes in daylight decreasing from 44.5% in 2019 to 41.0% in 2020, while crashes in unlighted dark conditions increased slightly from 16.5% to 18.3%.

Weather

Clear145 (67.8%)
↓-13.7%prior 168
Cloudy34 (15.9%)
↓-30.6%prior 49
Snow18 (8.4%)
↓-10.0%prior 20
Rain7 (3.3%)
↓-36.4%prior 11
Blowing Snow4 (1.9%)
Freezing rain/drizzle3 (1.4%)
↓-50.0%prior 6
Fog, smoke, smog2 (0.9%)
↓-66.7%prior 6
Other (explain in narrative)1 (0.5%)

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

Lighting

Daylight130 (59.4%)
↓-22.2%prior 167
Dark - roadway not lighted58 (26.5%)
↓-6.5%prior 62
Dark - roadway lighted13 (5.9%)
↓-40.9%prior 22
Dawn7 (3.2%)
↑40.0%prior 5
Dusk7 (3.2%)
↓-12.5%prior 8
Dark - unknown roadway lighting4 (1.8%)

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

Road Surface

Dry142 (65.4%)
↓-16.5%prior 170
Snow26 (12.0%)
↓-13.3%prior 30
Gravel17 (7.8%)
↑21.4%prior 14
Wet15 (6.9%)
↓-25.0%prior 20
Ice/frost10 (4.6%)
↓-61.5%prior 26
Slush5 (2.3%)
Other (explain in narrative)1 (0.5%)
Mud, dirt1 (0.5%)

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

Vehicles & Demographics

Vehicle and person demographics showed some year-over-year shifts. The top three vehicle makes involved in crashes remained Ford, Chevrolet (listed as CHEV), and Chevrolet, though the count for each decreased in 2020. Among persons involved in crashes, the 16-20 age group remained the most represented despite a drop in count from 128 to 100. The number of persons aged 65 and older involved in crashes saw a more pronounced decline, falling from 111 in 2019 to 76 in 2020.

Top Vehicle Makes (413 vehicles)

1
FORD81 (19.6%)
↓-15.6%prior 96
2
CHEV67 (16.2%)
↓-15.2%prior 79
3
CHEVROLET36 (8.7%)
↓-29.4%prior 51
4
GMC21 (5.1%)
↓-34.4%prior 32
5
DODG19 (4.6%)
↑18.8%prior 16
6
PONT15 (3.6%)
↑66.7%prior 9
7
BUIC14 (3.4%)
↓-30.0%prior 20
8
JEEP13 (3.1%)
↓-13.3%prior 15
9
HONDA10 (2.4%)
↓-16.7%prior 12
10
TOYO8 (1.9%)
↑60.0%prior 5

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

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

Sex Distribution (395 persons with recorded sex)

Male233 (59.0%)
↓-12.1%prior 265
Female162 (41.0%)
↓-23.9%prior 213

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: 317
  • Total persons involved: 620
  • Total vehicles involved: 413

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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