Yearly Traffic Safety Analysis

239 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In 2019, Carroll County recorded 239 total crashes, a 3.0% increase from the 232 crashes reported in 2018. While total fatalities remained stable at one death in each period, the number of people injured rose significantly by 32.9%, from 76 in 2018 to 101 in 2019. The most notable shift in contributing factors was a 180% increase in the count of crashes attributed to running a stop sign.

239

▲ 3.0%was 232

Total Crash Events

1

Persons Killed

101

▲ 32.9%was 76

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, traffic crashes in Carroll County saw a slight upward trend, increasing by 3.0% from 232 incidents in 2018 to 239 in 2019. This rise in crash volume was accompanied by a more substantial 32.9% increase in total injuries year-over-year, climbing from 76 to 101.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

101

Motorists Injured

Prior: 72↑40.3%

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 shifted between the two periods. In 2019, the peak day for crashes was Tuesday with 41 incidents, a change from 2018 when Wednesday was the peak day with 47 crashes. The busiest hour also moved earlier in the day, from 5 p.m. in 2018 (22 crashes) to 3 p.m. in 2019 (23 crashes). The afternoon hours remained the time with the highest crash frequency 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

Crash severity distributions shifted, even as the number of fatal crashes remained constant at one in both 2018 and 2019. The proportion of crashes resulting in minor injuries increased from 9.9% of all crashes in 2018 to 17.2% in 2019. Concurrently, the share of crashes with no injuries decreased from 71.1% to 67.8% year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
→0.0%prior 1
Serious Injury4serious injury crashes1.7%
↓-33.3%prior 6
Minor Injury41minor injury crashes17.2%
↑78.3%prior 23
Possible Injury31possible injury crashes13%
↓-16.2%prior 37
No Injury162no injury crashes67.8%
↓-1.8%prior 165

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 showed some changes between 2018 and 2019. 'Failure to yield right of way from a stop sign' remained a top cause, though its count decreased slightly from 21 to 20 crashes. Notably, incidents attributed to 'Ran Stop Sign' increased significantly, with the count rising from 5 crashes in 2018 to 14 in 2019. Conversely, crashes involving 'Lost Control' decreased from a count of 19 to 11.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign20 (8.4%)↓-4.8%prior 21
Ran off road - left19 (7.9%)↑11.8%prior 17
Followed too close16 (6.7%)↑23.1%prior 13
Driving too fast for conditions16 (6.7%)↑14.3%prior 14
Ran Stop Sign14 (5.9%)↑180.0%prior 5
FTYROW: Making left turn13 (5.4%)↑62.5%prior 8
Other (explain in narrative): Other13 (5.4%)↓-27.8%prior 18
Made improper turn11 (4.6%)↑83.3%prior 6
Lost Control11 (4.6%)↓-42.1%prior 19
Other (explain in narrative): No improper action11 (4.6%)→0.0%prior 11

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

Road & Environmental Conditions

Crashes in both 2018 and 2019 predominantly occurred in clear weather and daylight conditions, with no significant year-over-year shifts in these proportions. In 2019, 69.9% of crashes happened during daylight, compared to 70.3% in 2018. There was a change in road surface conditions, as the share of crashes on dry roads increased from 59.9% in 2018 to 66.1% in 2019, while crashes on adverse surfaces like wet or icy roads decreased proportionally.

Weather

Clear155 (65.1%)
↑8.4%prior 143
Cloudy49 (20.6%)
↑22.5%prior 40
Rain11 (4.6%)
↑57.1%prior 7
Snow10 (4.2%)
↓-23.1%prior 13
Freezing rain/drizzle6 (2.5%)
↓-62.5%prior 16
Blowing Snow4 (1.7%)
Severe Winds1 (0.4%)
Sleet, hail1 (0.4%)
Fog, smoke, smog1 (0.4%)

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

Lighting

Daylight167 (70.5%)
↑2.5%prior 163
Dark - roadway not lighted30 (12.7%)
↓-9.1%prior 33
Dark - roadway lighted26 (11.0%)
↑13.0%prior 23
Dusk7 (3.0%)
Dawn6 (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

Dry158 (66.7%)
↑13.7%prior 139
Wet24 (10.1%)
↓-17.2%prior 29
Snow23 (9.7%)
↓-4.2%prior 24
Ice/frost20 (8.4%)
↓-23.1%prior 26
Gravel9 (3.8%)
↑80.0%prior 5
Other (explain in narrative)2 (0.8%)
Slush1 (0.4%)

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

Vehicles & Demographics

Analysis of persons involved shows shifts in age distribution, as the total number of people in crashes grew from 482 to 559. The representation of the 16-20 age group increased from 11.6% of all persons in 2018 to 15.6% in 2019. Similarly, the share of individuals aged 65 and older grew from 12.4% to 16.3%. Conversely, the 45-54 age group's share of persons involved in crashes decreased from 14.9% to 7.0%.

Top Vehicle Makes (424 vehicles)

1
FORD77 (18.2%)
↑24.2%prior 62
2
CHEV73 (17.2%)
↓-18.0%prior 89
3
CHEVROLET29 (6.8%)
↓-14.7%prior 34
4
GMC18 (4.2%)
↑20.0%prior 15
5
DODG18 (4.2%)
↓-10.0%prior 20
6
TOYT17 (4%)
↑54.5%prior 11
7
BUIC16 (3.8%)
↑6.7%prior 15
8
CHRY14 (3.3%)
↑16.7%prior 12
9
JEEP13 (3.1%)
↑30.0%prior 10
10
TOYO12 (2.8%)
↑33.3%prior 9

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

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

Sex Distribution (392 persons with recorded sex)

Male207 (52.8%)
↑15.0%prior 180
Female185 (47.2%)
↑28.5%prior 144

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: 239
  • Total persons involved: 559
  • Total vehicles involved: 424

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

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