Yearly Traffic Safety Analysis

62 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Wayne County, total traffic crashes decreased by 16.2%, from 74 in 2019 to 62 in 2020. This decline was accompanied by a positive shift in crash outcomes, as the number of fatalities dropped from one in the prior year to zero in the current period. The most notable change in crash circumstances was a 150% increase in incidents involving driving under the influence (DUI), which rose from 2 to 5 events.

62

▼ -16.2%was 74

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

33

▲ 3.1%was 32

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

The overall trend in traffic incidents shows a year-over-year decrease. Total crashes fell from 74 in 2019 to 62 in 2020, representing a 16.2% reduction. While the number of total injuries remained stable, increasing by one from 32 to 33, total fatalities were eliminated, dropping from one to zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

0

Other Killed

Prior: 0→0.0%

32

Motorists Injured

Prior: 31↑3.2%

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 timing of crashes shifted between the two periods. In 2020, the peak day for crashes was Friday with 12 incidents, a change from 2019 when Monday was the peak day with 17 incidents. Similarly, the peak hour for collisions moved from the afternoon to the evening, with the 2 PM hour being most common in 2019 (7 crashes) and the 8 PM hour becoming the new peak in 2020 (6 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 improved year-over-year. Fatal crashes were eliminated in 2020, down from one fatal incident in 2019. The number of serious injury crashes also decreased, falling from 6 in the prior period to 3 in the current period. While the count of minor injury crashes was unchanged at 12, their share of total crashes increased from 16.2% to 19.4% due to the lower overall crash volume.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes4.8%
↓-50.0%prior 6
Minor Injury12minor injury crashes19.4%
→0.0%prior 12
Possible Injury9possible injury crashes14.5%
→0.0%prior 9
No Injury38no injury crashes61.3%
↓-17.4%prior 46

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 remained the leading contributing factor in both periods, with the count increasing by 26.7% from 15 crashes in 2019 to 19 in 2020. The share of crashes attributed to animals also grew from 20.3% to 30.6%. The count of crashes involving a driver operating their vehicle in a reckless, erratic, careless, or negligent manner doubled, rising from 3 to 6 incidents. Conversely, crashes attributed to a driver losing control decreased from 7 to 5.

Officer-Reported Primary Contributing Cause

Animal19 (30.6%)↑26.7%prior 15
Operating vehicle in an reckless, erratic, careless, negligent manner6 (9.7%)
Lost Control5 (8.1%)↓-28.6%prior 7
Ran off road - left4 (6.5%)
Ran off road - straight4 (6.5%)
Other (explain in narrative): Other3 (4.8%)↓-62.5%prior 8
Driving too fast for conditions3 (4.8%)
Exceeded authorized speed3 (4.8%)
Driver Distraction: Other interior distraction3 (4.8%)
Ran Stop Sign2 (3.2%)

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 notable shift in lighting conditions for crashes, with the proportion of incidents occurring in daylight decreasing from 55.4% in 2019 to 45.2% in 2020. Correspondingly, the share of crashes in dark, unlit roadway conditions increased from 24.3% to 35.5%. While most crashes in both years occurred in clear weather, the proportion of crashes during snow grew from 1.4% in 2019 (1 crash) to 6.5% in 2020 (4 crashes).

Weather

Clear42 (76.4%)
↓-14.3%prior 49
Snow4 (7.3%)
Rain3 (5.5%)
Cloudy3 (5.5%)
↓-75.0%prior 12
Freezing rain/drizzle2 (3.6%)
Fog, smoke, smog1 (1.8%)

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

Lighting

Daylight28 (50.9%)
↓-31.7%prior 41
Dark - roadway not lighted22 (40.0%)
↑22.2%prior 18
Dusk2 (3.6%)
↓-60.0%prior 5
Dawn1 (1.8%)
Dark - unknown roadway lighting1 (1.8%)
Dark - roadway lighted1 (1.8%)

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

Road Surface

Dry41 (74.5%)
↓-8.9%prior 45
Wet7 (12.7%)
↓-12.5%prior 8
Ice/frost3 (5.5%)
↓-40.0%prior 5
Snow3 (5.5%)
Gravel1 (1.8%)
↓-85.7%prior 7

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 two most common vehicle makes involved in crashes in both years, though their counts declined from 24 to 16 and 21 to 12, respectively. Among persons involved in crashes, the 16-20 age group saw its representation increase, accounting for 16.9% of individuals in 2020 compared to 10.6% in 2019. Conversely, the 26-34 age group's share decreased from 19.2% to 15.3%.

Top Vehicle Makes (81 vehicles)

1
FORD16 (19.8%)
↓-33.3%prior 24
2
CHEV12 (14.8%)
↓-42.9%prior 21
3
JEEP6 (7.4%)
4
DODG6 (7.4%)
↓-50.0%prior 12
5
DODGE5 (6.2%)
↓-28.6%prior 7
6
CHEVROLET5 (6.2%)
↓-28.6%prior 7
7
KIA3 (3.7%)
8
CHRYSLER2 (2.5%)
9
PONT2 (2.5%)
10
BUIC2 (2.5%)

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

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

Sex Distribution (79 persons with recorded sex)

Male47 (59.5%)
↓-20.3%prior 59
Female32 (40.5%)
↓-23.8%prior 42

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: 62
  • Total persons involved: 124
  • Total vehicles involved: 81

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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