Yearly Traffic Safety Analysis

42 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Winnebago County, total traffic crashes decreased by 26.3%, from 57 in 2019 to 42 in 2020. This downward trend was accompanied by a 53.8% reduction in total injuries, which fell from 39 to 18. Notably, there were no fatalities in either period. A significant shift occurred in contributing factors, with 'Operating vehicle in a reckless... manner' emerging as a leading cause in 2020 with 6 incidents, while 'Driving too fast for conditions' dropped from 9 crashes in 2019 to just 2 in 2020.

42

▼ -26.3%was 57

Total Crash Events

0

Persons Killed

18

▼ -53.8%was 39

Persons Injured

0

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

Trend Summary

Traffic safety trends in Winnebago County showed a significant improvement year-over-year. The total number of crashes fell by 26.3%, from 57 in 2019 to 42 in 2020. Similarly, the number of people injured in these incidents decreased by 53.8%, from 39 to 18, while fatalities remained at zero for both years.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 1↑100.0%

1

Cyclists Injured

Prior: 0→%

15

Motorists Injured

Prior: 38↓-60.5%

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 temporal patterns of crashes showed some changes between the two periods. Wednesday remained the peak day for crashes in both 2019 (13 crashes) and 2020 (9 crashes), though the volume decreased. However, the peak hour for crashes shifted from the afternoon commute at 2 p.m. in 2019 (6 crashes) to the late morning at 10 a.m. in 2020 (5 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

There were no fatal crashes recorded in either 2019 or 2020. The overall proportion of crashes involving any level of injury was nearly unchanged, accounting for 38.6% of crashes in 2019 and 38.1% in 2020. While the absolute number of injuries decreased, the share of crashes resulting in serious injuries saw a slight increase from 5.3% in 2019 to 7.1% in 2020, even as the count of such crashes remained stable at 3.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes7.1%
→0.0%prior 3
Minor Injury6minor injury crashes14.3%
↓-33.3%prior 9
Possible Injury7possible injury crashes16.7%
↓-30.0%prior 10
No Injury26no injury crashes61.9%
↓-25.7%prior 35

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

The leading contributing factors for crashes shifted significantly year-over-year. In 2019, 'Driving too fast for conditions' was the top cause with 9 crashes, but this factor's count dropped to 2 in 2020. In 2020, 'Operating vehicle in an reckless, erratic, careless, negligent manner' and 'Ran off road - left' became the leading factors, each accounting for 6 crashes. The count for reckless driving was up from not being a top factor in 2019, and running off the road to the left increased from 2 incidents in the prior year.

Officer-Reported Primary Contributing Cause

Operating vehicle in an reckless, erratic, careless, negligent manner6 (14.3%)
Ran off road - left6 (14.3%)
FTYROW: From stop sign5 (11.9%)
Lost Control3 (7.1%)↓-50.0%prior 6
Made improper turn3 (7.1%)
Animal2 (4.8%)↓-66.7%prior 6
Driving too fast for conditions2 (4.8%)↓-77.8%prior 9
Swerving/Evasive Action2 (4.8%)
FTYROW: Making left turn1 (2.4%)
FTYROW: To pedestrian1 (2.4%)

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

Road & Environmental Conditions

Crash conditions shifted notably between the two years, with a higher proportion of incidents in 2020 occurring in favorable conditions. Crashes on dry road surfaces increased from 33.3% of the total in 2019 to 64.3% in 2020. Correspondingly, crashes on snow or ice-covered roads decreased from 20 incidents in 2019 to 7 in 2020. The share of crashes occurring in daylight also rose from 61.4% to 71.4% year-over-year.

Weather

Clear24 (60.0%)
↓-14.3%prior 28
Cloudy10 (25.0%)
↓-9.1%prior 11
Fog, smoke, smog2 (5.0%)
Blowing Snow2 (5.0%)
Rain1 (2.5%)
Freezing rain/drizzle1 (2.5%)

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

Lighting

Daylight30 (75.0%)
↓-14.3%prior 35
Dark - roadway lighted7 (17.5%)
↑16.7%prior 6
Dark - roadway not lighted2 (5.0%)
↓-77.8%prior 9
Dawn1 (2.5%)

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

Road Surface

Dry27 (67.5%)
↑42.1%prior 19
Ice/frost4 (10.0%)
↓-55.6%prior 9
Wet4 (10.0%)
↓-55.6%prior 9
Snow3 (7.5%)
↓-72.7%prior 11
Gravel2 (5.0%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both years, though their counts and ranking shifted. The number of Fords involved decreased from 20 to 14, while Chevrolets (combining 'CHEV' and 'CHEVROLET') increased from 15 to 17. The age distribution of persons involved in crashes also changed; the share of individuals in the 16-20 and 65+ age groups decreased, while the share of those in the 35-64 age range collectively increased.

Top Vehicle Makes (65 vehicles)

1
FORD14 (21.5%)
↓-30.0%prior 20
2
CHEV11 (16.9%)
→0.0%prior 11
3
CHEVROLET6 (9.2%)
4
GMC5 (7.7%)
5
DODG4 (6.2%)
6
HOND3 (4.6%)
7
PONT2 (3.1%)
↓-66.7%prior 6
8
NISS2 (3.1%)
9
FREIGHTLINER2 (3.1%)
10
PETE1 (1.5%)

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

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

Sex Distribution (60 persons with recorded sex)

Male35 (58.3%)
↓-25.5%prior 47
Female25 (41.7%)
↓-34.2%prior 38

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: 42
  • Total persons involved: 91
  • Total vehicles involved: 65

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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