Yearly Traffic Safety Analysis

339 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In 2019, Clay County recorded 339 total crashes, a slight decrease of 1.2% from the 343 crashes reported in 2018. While overall crash volume remained stable, the most significant year-over-year change was the increase in traffic fatalities, which rose from zero in 2018 to four in 2019. Total injuries also saw an increase, rising from 102 to 114 during the same period.

339

▼ -1.2%was 343

Total Crash Events

4

Persons Killed

114

▲ 11.8%was 102

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 · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Clay County was relatively stable, with a minor 1.2% decrease from 343 incidents in 2018 to 339 in 2019. However, the severity of these incidents worsened, as total injuries increased by 11.8% from 102 to 114, and fatalities rose from zero to four.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 0→%

5

Cyclists Injured

Prior: 2↑150.0%

109

Motorists Injured

Prior: 99↑10.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns of crashes showed some shifts between the two periods. In 2019, the peak day for crashes was Tuesday with 71 incidents, a change from 2018 when Monday and Wednesday were the busiest days with 61 crashes each. The peak time for crashes remained in the afternoon commute, with 5 p.m. being a peak hour in 2019 (29 crashes), similar to the 4 p.m. peak in 2018 (29 crashes). November was the month with the highest number of crashes in both years.

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased notably in 2019, with the county recording 3 fatal crashes resulting in 4 deaths, compared to zero in 2018. While the number of serious injury crashes decreased from 9 in 2018 to 4 in 2019, crashes involving minor injuries rose from 30 to 43. Overall, the proportion of crashes resulting in any form of injury (possible, minor, or serious) increased from 25.6% of all crashes in 2018 to 26.9% in 2019.

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

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
Serious Injury4serious injury crashes1.2%
↓-55.6%prior 9
Minor Injury43minor injury crashes12.7%
↑43.3%prior 30
Possible Injury44possible injury crashes13%
↓-10.2%prior 49
No Injury245no injury crashes72.3%
↓-3.9%prior 255

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both years, with the count of such incidents increasing by 14.3% from 63 in 2018 to 72 in 2019. A significant shift occurred in crashes related to failure to yield from a stop sign, which fell by 47.4% from 38 incidents in 2018 to 20 in 2019, dropping it from the second-ranked cause to the fourth. Conversely, crashes attributed to 'Improper Backing' more than tripled, rising from 3 in 2018 to 10 in 2019.

Officer-Reported Primary Contributing Cause

Animal72 (21.2%)↑14.3%prior 63
Other (explain in narrative): Other34 (10%)↑61.9%prior 21
Driving too fast for conditions22 (6.5%)↓-24.1%prior 29
FTYROW: From stop sign20 (5.9%)↓-47.4%prior 38
FTYROW: Making left turn16 (4.7%)↓-11.1%prior 18
Followed too close14 (4.1%)↓-26.3%prior 19
Ran Stop Sign14 (4.1%)↓-17.6%prior 17
Ran off road - left12 (3.5%)↓-25.0%prior 16
FTYROW: At uncontrolled intersection11 (3.2%)↓-8.3%prior 12
Ran off road - straight10 (2.9%)→0.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both 2019 and 2018 occurring in clear weather (186 and 197 crashes, respectively) and during daylight hours (210 and 226 crashes). There was a notable decrease in crashes on icy or frosty roads, which fell from 32 in 2018 to 25 in 2019. Crashes on snow-covered roads were comparable, with 31 in 2018 and 34 in 2019.

Weather

Clear186 (67.6%)
↓-5.6%prior 197
Cloudy53 (19.3%)
↓-3.6%prior 55
Snow13 (4.7%)
↑62.5%prior 8
Rain12 (4.4%)
→0.0%prior 12
Blowing Snow4 (1.5%)
↓-20.0%prior 5
Fog, smoke, smog3 (1.1%)
Freezing rain/drizzle2 (0.7%)
↓-71.4%prior 7
Severe Winds1 (0.4%)
Sleet, hail1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash

Lighting

Daylight210 (75.3%)
↓-7.1%prior 226
Dark - roadway not lighted28 (10.0%)
↓-17.6%prior 34
Dark - roadway lighted23 (8.2%)
↑15.0%prior 20
Dusk10 (3.6%)
↑66.7%prior 6
Dawn7 (2.5%)
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field

Road Surface

Dry174 (62.8%)
↓-3.3%prior 180
Snow34 (12.3%)
↑9.7%prior 31
Ice/frost25 (9.0%)
↓-21.9%prior 32
Wet24 (8.7%)
↓-14.3%prior 28
Gravel14 (5.1%)
↓-6.7%prior 15
Slush4 (1.4%)
Mud, dirt2 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes were consistent across both years, with Ford and Chevrolet variants being the most frequently recorded in both 2019 and 2018. Analysis of the demographics of persons involved in crashes shows a shift in age distribution; the number of individuals aged 16-20 involved in crashes rose from 85 to 113, and the 65+ age group increased from 96 to 118. In contrast, the 26-34 age group, which had high involvement in 2018 with 99 persons, saw a decrease to 91 persons in 2019.

Top Vehicle Makes (559 vehicles)

1
FORD102 (18.2%)
↑10.9%prior 92
2
CHEV88 (15.7%)
↑12.8%prior 78
3
CHEVROLET51 (9.1%)
↑2.0%prior 50
4
DODG31 (5.5%)
↓-20.5%prior 39
5
BUIC25 (4.5%)
↑13.6%prior 22
6
CHRY24 (4.3%)
↑26.3%prior 19
7
JEEP22 (3.9%)
↑83.3%prior 12
8
GMC19 (3.4%)
↓-9.5%prior 21
9
PONT18 (3.2%)
↑20.0%prior 15
10
DODGE15 (2.7%)
↓-31.8%prior 22

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records

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

Sex Distribution (520 persons with recorded sex)

Male294 (56.5%)
↑22.5%prior 240
Female226 (43.5%)
↑13.6%prior 199

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 339
  • Total persons involved: 774
  • Total vehicles involved: 559

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: 2019." Published September 9, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2019-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

ThatCarHitMe.com · An Injuria.ai Company