Yearly Traffic Safety Analysis

281 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Clay County, total vehicle crashes decreased by 17.1% from 339 in 2019 to 281 in 2020. While total injuries also saw a 13.2% decline from 114 to 99, the number of fatalities remained unchanged at four. One of the most significant year-over-year shifts was a 49.2% reduction in rear-end collisions, which fell from 63 incidents in the prior period to 32 in the current period.

281

▼ -17.1%was 339

Total Crash Events

4

Persons Killed

99

▼ -13.2%was 114

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 safety trends in Clay County showed improvement, with a notable 17.1% decrease in total crashes from 339 to 281 year-over-year. This downward trend was also reflected in the number of injuries, which fell by 13.2% from 114 to 99. However, the number of fatalities held steady at four for both periods, indicating that while crash frequency decreased, the number of deaths did not.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 4→0.0%

2

Pedestrians Injured

Prior: 0→%

3

Cyclists Injured

Prior: 5↓-40.0%

94

Motorists Injured

Prior: 109↓-13.8%

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 showed some shifts between the two periods. While the peak hour for collisions remained 5 p.m. in both years, the peak day moved from Tuesday (71 crashes) in 2019 to Wednesday (56 crashes) in 2020. The volume of crashes during the peak hour also decreased from 29 in the prior year to 23 in the current year, mirroring the overall decline in crash incidents.

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

While the total number of crashes decreased, the fatal crash rate per 100 crashes increased from 0.88 to 1.07, as the count of fatal crashes remained stable at three despite fewer overall incidents. The number of serious injury crashes increased from four to six, representing a proportional rise from 1.2% to 2.1% of all crashes. Conversely, minor injury crashes decreased in both count (from 43 to 31) and as a share of total crashes (from 12.7% to 11.0%).

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.1%
→0.0%prior 3
Serious Injury6serious injury crashes2.1%
↑50.0%prior 4
Minor Injury31minor injury crashes11%
↓-27.9%prior 43
Possible Injury42possible injury crashes14.9%
↓-4.5%prior 44
No Injury199no injury crashes70.8%
↓-18.8%prior 245

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 animals remained the top contributing factor in both years, though the count decreased from 72 to 64. A significant change was observed in crashes attributed to 'Driving too fast for conditions,' which saw a 40.9% drop in count from 22 incidents to 13, falling from the third to the fifth-ranked cause. Conversely, crashes due to 'Failure to yield row from stop sign' increased in count by 25%, from 20 to 25, making it the third most common factor in the current period.

Officer-Reported Primary Contributing Cause

Animal64 (22.8%)↓-11.1%prior 72
Other (explain in narrative): Other28 (10%)↓-17.6%prior 34
FTYROW: From stop sign25 (8.9%)↑25.0%prior 20
Ran off road - left13 (4.6%)↑8.3%prior 12
Driving too fast for conditions13 (4.6%)↓-40.9%prior 22
Ran Stop Sign12 (4.3%)↓-14.3%prior 14
FTYROW: Making left turn11 (3.9%)↓-31.3%prior 16
Other (explain in narrative): No improper action10 (3.6%)
Lost Control9 (3.2%)↓-10.0%prior 10
Followed too close7 (2.5%)↓-50.0%prior 14

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 distribution of crashes across different environmental conditions remained largely consistent year-over-year. In both periods, a majority of crashes occurred in clear weather (54.9% in 2019 vs. 54.4% in 2020) and during daylight hours (61.9% vs. 62.6%). The proportion of crashes on dry road surfaces was also stable, accounting for 51.3% of crashes in the prior period and 52.7% in the current period, indicating no major shift in how conditions influenced crash frequency.

Weather

Clear153 (68.9%)
↓-17.7%prior 186
Cloudy31 (14.0%)
↓-41.5%prior 53
Snow11 (5.0%)
↓-15.4%prior 13
Rain9 (4.1%)
↓-25.0%prior 12
Severe Winds8 (3.6%)
Freezing rain/drizzle6 (2.7%)
Blowing Snow3 (1.4%)
Fog, smoke, smog1 (0.5%)

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

Lighting

Daylight176 (79.3%)
↓-16.2%prior 210
Dark - roadway not lighted24 (10.8%)
↓-14.3%prior 28
Dark - roadway lighted14 (6.3%)
↓-39.1%prior 23
Dusk4 (1.8%)
↓-60.0%prior 10
Dawn3 (1.4%)
↓-57.1%prior 7
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry148 (66.7%)
↓-14.9%prior 174
Wet21 (9.5%)
↓-12.5%prior 24
Snow21 (9.5%)
↓-38.2%prior 34
Ice/frost19 (8.6%)
↓-24.0%prior 25
Gravel12 (5.4%)
↓-14.3%prior 14
Slush1 (0.5%)

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, Ford and Chevrolet, maintained their rankings in both periods, although the total number of vehicles involved for each make decreased in line with the overall drop in crashes. Regarding driver demographics, the representation of individuals in the 16-20 age group among those involved in crashes saw a notable decline, dropping from a 14.6% share (113 persons) in 2019 to a 12.0% share (76 persons) in 2020.

Top Vehicle Makes (448 vehicles)

1
FORD82 (18.3%)
↓-19.6%prior 102
2
CHEV51 (11.4%)
↓-42.0%prior 88
3
CHEVROLET44 (9.8%)
↓-13.7%prior 51
4
DODG26 (5.8%)
↓-16.1%prior 31
5
GMC21 (4.7%)
↑10.5%prior 19
6
JEEP18 (4%)
↓-18.2%prior 22
7
DODGE18 (4%)
↑20.0%prior 15
8
BUIC16 (3.6%)
↓-36.0%prior 25
9
PONT13 (2.9%)
↓-27.8%prior 18
10
NISS11 (2.5%)
↑57.1%prior 7

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 (413 persons with recorded sex)

Male241 (58.4%)
↓-18.0%prior 294
Female172 (41.6%)
↓-23.9%prior 226

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: 281
  • Total persons involved: 633
  • Total vehicles involved: 448

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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