Yearly Traffic Safety Analysis

379 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Iowa County recorded 379 vehicle crashes, a 16.2% decrease from the 452 crashes reported in 2019. Despite the overall reduction in collisions and a 23.1% drop in injuries from 134 to 103, the number of fatalities increased by 50% from 4 to 6 year-over-year. The most significant contributing factor in both periods was collisions with animals.

379

▼ -16.2%was 452

Total Crash Events

6

▲ 50.0%was 4

Persons Killed

103

▼ -23.1%was 134

Persons Injured

6

▲ 100.0%was 3

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

Overall, traffic crashes in Iowa County saw a downward trend from 2019 to 2020, with total collisions falling by 16.2% from 452 to 379. This decline was also reflected in the number of people injured, which dropped by 23.1% from 134 to 103. However, fatalities increased by 50%, rising from 4 to 6 persons killed.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 3↑100.0%

1

Cyclists Injured

Prior: 1→0.0%

102

Motorists Injured

Prior: 133↓-23.3%

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 shifts between 2019 and 2020. The most frequent day for crashes changed from Monday (79 crashes) in 2019 to Friday (67 crashes) in 2020. The peak hour for collisions remained consistent year-over-year, with the 3 p.m. hour having the highest volume in both periods, recording 32 crashes each year.

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 worsened in 2020 compared to the prior year, despite a lower total number of crashes. The fatal crash rate more than doubled, increasing from 0.66 per 100 crashes in 2019 to 1.58 in 2020, as the number of fatal crashes rose from 3 to 6. Conversely, the share of crashes resulting in any injury decreased from 23.7% of all crashes in 2019 to 20.1% in 2020.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1.6%
↑100.0%prior 3
Serious Injury14serious injury crashes3.7%
↑40.0%prior 10
Minor Injury26minor injury crashes6.9%
↓-38.1%prior 42
Possible Injury36possible injury crashes9.5%
↓-34.5%prior 55
No Injury297no injury crashes78.4%
↓-13.2%prior 342

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 primary contributing factors for crashes remained consistent, with 'Animal' being the most cited cause in both 2019 (136 crashes) and 2020 (140 crashes). While the top three factors—'Animal,' 'Ran off road - straight,' and 'Lost Control'—retained their rankings, their counts shifted. Crashes attributed to 'Driving too fast for conditions' dropped by 51.2% from 43 to 21 incidents. In contrast, crashes where a driver 'Ran Stop Sign' increased from 3 in 2019 to 12 in 2020.

Officer-Reported Primary Contributing Cause

Animal140 (36.9%)↑2.9%prior 136
Ran off road - straight36 (9.5%)↓-23.4%prior 47
Lost Control34 (9%)↓-24.4%prior 45
Driving too fast for conditions21 (5.5%)↓-51.2%prior 43
Followed too close16 (4.2%)↓-52.9%prior 34
Other (explain in narrative): No improper action13 (3.4%)↑116.7%prior 6
Ran Stop Sign12 (3.2%)
Ran off road - left10 (2.6%)↓-50.0%prior 20
Other (explain in narrative): Other9 (2.4%)↓-50.0%prior 18
FTYROW: From stop sign8 (2.1%)↓-20.0%prior 10

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

Road & Environmental Conditions

Crashes were less frequently associated with adverse environmental conditions in 2020 compared to 2019. The proportion of crashes occurring on adverse road surfaces like ice, snow, or wet pavement fell from 29.9% of all crashes in 2019 to 19.0% in 2020. Similarly, collisions during adverse weather conditions (such as snow or rain) decreased from representing 22.8% of all crashes in 2019 to 14.5% in 2020. The distribution of crashes by lighting conditions remained relatively stable between the two periods.

Weather

Clear132 (53.4%)
↓-9.6%prior 146
Cloudy60 (24.3%)
↓-22.1%prior 77
Snow21 (8.5%)
↓-36.4%prior 33
Freezing rain/drizzle17 (6.9%)
↑54.5%prior 11
Rain13 (5.3%)
↓-38.1%prior 21
Fog, smoke, smog2 (0.8%)
↓-60.0%prior 5
Blowing Snow1 (0.4%)
↓-96.3%prior 27
Severe Winds1 (0.4%)

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

Lighting

Daylight145 (58.7%)
↓-22.0%prior 186
Dark - roadway not lighted82 (33.2%)
↓-26.8%prior 112
Dusk9 (3.6%)
↑12.5%prior 8
Dawn6 (2.4%)
↓-25.0%prior 8
Dark - roadway lighted5 (2.0%)
↓-54.5%prior 11

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

Road Surface

Dry161 (65.2%)
↓-12.0%prior 183
Ice/frost30 (12.1%)
↓-50.0%prior 60
Wet27 (10.9%)
↓-10.0%prior 30
Gravel14 (5.7%)
↑75.0%prior 8
Snow14 (5.7%)
↓-68.2%prior 44
Slush1 (0.4%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Chevrolet and Ford, maintained their top rankings in 2020, although the count of vehicles from both makes decreased from the prior year. An analysis of persons involved in crashes shows a shift in age demographics. The share of individuals aged 65 and older decreased from making up 12.5% of all persons involved in 2019 to 8.1% in 2020. Conversely, the representation of younger individuals aged 16-25 increased from 20.6% to 24.0% of the total.

Top Vehicle Makes (499 vehicles)

1
FORD81 (16.2%)
↓-19.8%prior 101
2
CHEV72 (14.4%)
↓-8.9%prior 79
3
TOYO28 (5.6%)
↑86.7%prior 15
4
CHEVROLET28 (5.6%)
↓-26.3%prior 38
5
DODG22 (4.4%)
→0.0%prior 22
6
JEEP22 (4.4%)
↑22.2%prior 18
7
FREIGHTLINER15 (3%)
↓-11.8%prior 17
8
HONDA14 (2.8%)
↑16.7%prior 12
9
GMC14 (2.8%)
↓-44.0%prior 25
10
DODGE12 (2.4%)
↓-25.0%prior 16

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

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

Sex Distribution (471 persons with recorded sex)

Male299 (63.5%)
↓-11.8%prior 339
Female172 (36.5%)
↓-25.2%prior 230

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: 379
  • Total persons involved: 766
  • Total vehicles involved: 499

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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