Yearly Traffic Safety Analysis

75 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Audubon County recorded 75 vehicle crashes, a 15.4% increase from the 65 crashes documented in 2019. While total crashes and injuries (25, up from 17) increased, there were no fatalities in 2020, compared to one in the prior year. The most significant change in contributing factors was a 92% rise in the count of crashes involving animals, which increased from 13 incidents in 2019 to 25 in 2020.

75

▲ 15.4%was 65

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

25

▲ 47.1%was 17

Persons Injured

0

▼ -100.0%was 1

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

Overall, Audubon County saw an upward trend in traffic collisions in 2020 compared to the previous year. The total number of crashes rose by 15.4%, from 65 in 2019 to 75 in 2020. This increase was accompanied by a 47% rise in the number of people injured, which grew from 17 to 25, although fatalities fell from one to zero.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

23

Motorists Injured

Prior: 17↑35.3%

1

Other Injured

Prior: 0→%

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 in Audubon County shifted between 2019 and 2020. In 2020, Wednesday was the most frequent day for crashes with 18 incidents, whereas in 2019, crashes peaked on both Monday and Wednesday with 13 incidents each. The peak hour for collisions also shifted later into the evening, from 7 p.m. in 2019 (7 crashes) to 8 p.m. in 2020 (10 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

In 2020, crash severity outcomes showed a mixed change compared to 2019. The county recorded zero fatal crashes, a decrease from one fatal crash in the prior year. However, the proportion of crashes resulting in any injury increased from 21.5% (14 crashes) in 2019 to 26.7% (20 crashes) in 2020. Specifically, the share of crashes with serious injuries rose from 1.5% to 5.3% year-over-year.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes5.3%
↑300.0%prior 1
Minor Injury8minor injury crashes10.7%
→0.0%prior 8
Possible Injury8possible injury crashes10.7%
↑60.0%prior 5
No Injury55no injury crashes73.3%
↑10.0%prior 50

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 animals were the leading contributing factor in both periods, but the count increased by 92%, from 13 crashes in 2019 to 25 in 2020. 'Lost Control' incidents also saw a significant rise, increasing from 4 crashes to 14, becoming the second most common factor in 2020. Conversely, crashes attributed to 'Driving too fast for conditions' decreased from 4 incidents in 2019 to 2 in 2020.

Officer-Reported Primary Contributing Cause

Animal25 (33.3%)↑92.3%prior 13
Lost Control14 (18.7%)
Ran off road - left6 (8%)
Ran off road - straight5 (6.7%)↓-16.7%prior 6
FTYROW: Making left turn4 (5.3%)
Followed too close3 (4%)
Made improper turn2 (2.7%)
Swerving/Evasive Action2 (2.7%)
Driving too fast for conditions2 (2.7%)
Other (explain in narrative): Other1 (1.3%)↓-85.7%prior 7

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 on dry road surfaces remained unchanged with 36 incidents in both 2019 and 2020. However, the number of crashes occurring in daylight increased from 34 to 39, while collisions in dark, unlighted conditions decreased from 15 to 11. The number of crashes on gravel roads increased significantly, from 2 in 2019 to 8 in 2020.

Weather

Clear39 (70.9%)
↓-2.5%prior 40
Cloudy11 (20.0%)
Rain2 (3.6%)
Snow2 (3.6%)
Blowing Snow1 (1.8%)

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

Lighting

Daylight39 (72.2%)
↑14.7%prior 34
Dark - roadway not lighted11 (20.4%)
↓-26.7%prior 15
Dark - roadway lighted2 (3.7%)
↓-60.0%prior 5
Dusk2 (3.7%)

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

Road Surface

Dry36 (65.5%)
→0.0%prior 36
Gravel8 (14.5%)
Snow5 (9.1%)
↓-28.6%prior 7
Ice/frost4 (7.3%)
↓-33.3%prior 6
Wet2 (3.6%)
↓-71.4%prior 7

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, led by Chevrolet and Ford in both years. The number of Chevrolet vehicles involved decreased from 32 in 2019 to 27 in 2020, while Ford vehicles increased from 8 to 12. A significant demographic shift occurred among persons involved in crashes: the 16-20 age group saw its involvement increase from 18 individuals in 2019 to 31 in 2020, while the number of individuals aged 65 and older fell from 26 to 15.

Top Vehicle Makes (99 vehicles)

1
CHEV25 (25.3%)
↑38.9%prior 18
2
FORD12 (12.1%)
↑50.0%prior 8
3
GMC10 (10.1%)
↑66.7%prior 6
4
JEEP8 (8.1%)
5
DODG6 (6.1%)
↓-33.3%prior 9
6
BUIC5 (5.1%)
7
SUBA3 (3%)
8
DODGE3 (3%)
9
FREIGHTLINER2 (2%)
10
HYUN2 (2%)

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

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

Sex Distribution (96 persons with recorded sex)

Male62 (64.6%)
↑29.2%prior 48
Female34 (35.4%)
↑9.7%prior 31

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: 75
  • Total persons involved: 145
  • Total vehicles involved: 99

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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