Yearly Traffic Safety Analysis

2,606 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In Johnson County, a total of 2,606 vehicle crashes were recorded in 2019, a slight increase of 0.9% from the 2,583 crashes documented in 2018. While the total number of incidents remained relatively stable, the most notable year-over-year shift was an increase in crash severity. The number of fatalities rose from 7 in 2018 to 9 in 2019, and the number of fatal crashes increased from 5 to 7.

2,606

▲ 0.9%was 2,583

Total Crash Events

9

▲ 28.6%was 7

Persons Killed

693

▼ -1.8%was 706

Persons Injured

7

▲ 40.0%was 5

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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

Overall crash trends in Johnson County showed relative stability in volume but an increase in severity year-over-year. Total crashes increased by 23 incidents, from 2,583 to 2,606. In contrast, total reported injuries saw a slight decrease from 706 to 693, while fatalities increased from 7 to 9.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

1

Cyclists Killed

Prior: 0→%

8

Motorists Killed

Prior: 6↑33.3%

0

Other Killed

Prior: 0→0.0%

18

Pedestrians Injured

Prior: 28↓-35.7%

34

Cyclists Injured

Prior: 38↓-10.5%

640

Motorists Injured

Prior: 638↑0.3%

1

Other Injured

Prior: 2↓-50.0%

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

The temporal patterns of crashes remained consistent between 2018 and 2019. Friday was the day with the most crashes in both years, with the count increasing from 470 in 2018 to 503 in 2019. Similarly, the 5 PM hour was the peak time for collisions in both periods, though the count decreased slightly from 259 crashes in 2018 to 245 in 2019.

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 worsened from 2018 to 2019. The number of fatal crashes increased from 5 to 7, raising the fatal crash rate from 0.19% to 0.27% of all crashes. While the count of serious injury crashes decreased from 35 to 32 and minor injury crashes fell from 224 to 193, the number of crashes involving possible injuries rose from 365 to 372.

Severity is per crash event (most severe injury). 7 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.3%
↑40.0%prior 5
Serious Injury32serious injury crashes1.2%
↓-8.6%prior 35
Minor Injury193minor injury crashes7.4%
↓-13.8%prior 224
Possible Injury372possible injury crashes14.3%
↑1.9%prior 365
No Injury2,002no injury crashes76.8%
↑2.5%prior 1,954

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

The leading contributing factors for crashes remained largely the same year-over-year, with 'Followed too close' being the primary cause in both 2019 (474 incidents) and 2018 (479 incidents). A notable shift was observed in crashes attributed to 'Lost Control,' which increased by 53.3% from 60 incidents in 2018 to 92 in 2019. Crashes involving 'Ran Traffic Signal' also saw an increase in count, from 65 to 78.

Officer-Reported Primary Contributing Cause

Followed too close474 (18.2%)↓-1.0%prior 479
Driving too fast for conditions237 (9.1%)↑6.3%prior 223
Animal164 (6.3%)↓-2.4%prior 168
Other (explain in narrative): Other163 (6.3%)↓-12.4%prior 186
Ran off road - left139 (5.3%)↓-7.9%prior 151
FTYROW: From stop sign101 (3.9%)↓-9.8%prior 112
Improper or erratic lane changing97 (3.7%)↓-4.9%prior 102
FTYROW: Making left turn92 (3.5%)→0.0%prior 92
Lost Control92 (3.5%)↑53.3%prior 60
Made improper turn89 (3.4%)↑20.3%prior 74

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

Road & Environmental Conditions

While crash distributions across most conditions were similar year-over-year, there was a significant increase in collisions occurring on icy or frosty road surfaces, which rose from 96 incidents in 2018 to 174 in 2019. Crashes in dark, unlighted conditions also increased from 233 to 281. Conversely, crashes on wet roads decreased from 387 to 312, and those in rainy weather fell from 170 to 148.

Weather

Clear1,563 (61.9%)
↑3.3%prior 1,513
Cloudy555 (22.0%)
↓-2.6%prior 570
Snow161 (6.4%)
↑20.1%prior 134
Rain148 (5.9%)
↓-12.9%prior 170
Freezing rain/drizzle48 (1.9%)
↓-17.2%prior 58
Blowing Snow26 (1.0%)
↑116.7%prior 12
Fog, smoke, smog10 (0.4%)
→0.0%prior 10
Severe Winds7 (0.3%)
Sleet, hail4 (0.2%)
↓-42.9%prior 7
Other (explain in narrative)2 (0.1%)
↓-66.7%prior 6

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

Lighting

Daylight1,812 (71.4%)
↓-0.8%prior 1,826
Dark - roadway lighted319 (12.6%)
↑5.6%prior 302
Dark - roadway not lighted281 (11.1%)
↑20.6%prior 233
Dusk67 (2.6%)
↓-4.3%prior 70
Dawn50 (2.0%)
↑16.3%prior 43
Dark - unknown roadway lighting9 (0.4%)
↓-18.2%prior 11

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

Road Surface

Dry1,781 (70.5%)
↑2.0%prior 1,746
Wet312 (12.4%)
↓-19.4%prior 387
Snow209 (8.3%)
↑7.2%prior 195
Ice/frost174 (6.9%)
↑81.3%prior 96
Slush34 (1.3%)
↑3.0%prior 33
Gravel10 (0.4%)
↓-33.3%prior 15
Other (explain in narrative)4 (0.2%)
↓-20.0%prior 5
Mud, dirt1 (0.0%)
Water (standing or moving)1 (0.0%)

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

Vehicles & Demographics

The ranking of the top three vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, and Toyota leading in both years. The number of Fords involved in collisions increased from 608 in 2018 to 714 in 2019. An analysis of persons involved shows an increase in participation across most age groups, with notable growth in the 35-44, 45-54, and 55-64 age brackets.

Top Vehicle Makes (4,865 vehicles)

1
FORD714 (14.7%)
↑17.4%prior 608
2
CHEV440 (9%)
↓-7.0%prior 473
3
TOYT419 (8.6%)
↓-6.5%prior 448
4
HOND283 (5.8%)
↑0.7%prior 281
5
CHEVROLET211 (4.3%)
↑14.7%prior 184
6
TOYOTA190 (3.9%)
↑7.3%prior 177
7
JEEP158 (3.2%)
↑9.7%prior 144
8
NISS149 (3.1%)
↓-2.0%prior 152
9
HONDA136 (2.8%)
↑22.5%prior 111
10
NR131 (2.7%)
↓-2.2%prior 134

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

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

Sex Distribution (4,445 persons with recorded sex)

Male2,494 (56.1%)
↑18.3%prior 2,108
Female1,951 (43.9%)
↑10.3%prior 1,769

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: 2,606
  • Total persons involved: 5,987
  • Total vehicles involved: 4,865

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