Yearly Traffic Safety Analysis

261 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Mills County recorded 261 total crashes, a 6.8% decrease from the 280 crashes reported in 2017. Despite the overall reduction in collisions, the number of fatalities doubled, increasing from 3 in the prior year to 6 in the current year.

261

▼ -6.8%was 280

Total Crash Events

6

▲ 100.0%was 3

Persons Killed

106

▲ 1.9%was 104

Persons Injured

5

▲ 66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in crashes in Mills County shows a year-over-year decrease. Total collisions fell by 6.8%, from 280 in 2017 to 261 in 2018. However, this decline in crash volume was accompanied by a rise in severe outcomes, as total injuries increased slightly from 104 to 106 and fatalities doubled from 3 to 6.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 2↑200.0%

2

Pedestrians Injured

Prior: 1↑100.0%

1

Cyclists Injured

Prior: 0→%

103

Motorists Injured

Prior: 103→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · 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 largely consistent year-over-year. Sunday was the day with the most crashes in both 2018 (42 crashes) and 2017 (48 crashes). The 5 p.m. hour was a peak time for collisions in both periods, with 22 crashes recorded during that hour in each year. The highest volume of crashes occurred in the later months of the year for both periods, with November being the peak month in 2018 (33 crashes) and December in 2017 (33 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of outcomes shifted in 2018. The number of fatal crashes increased from 3 to 5, and total fatalities doubled from 3 to 6, causing the fatal crash rate to rise from 1.1% to 1.9% of all crashes. There was a notable decrease in crashes resulting in serious injuries, which fell from 25 in 2017 to 9 in 2018, while minor injury crashes increased from 25 to 33.

Severity is per crash event (most severe injury). 5 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal5fatal crashes1.9%
↑66.7%prior 3
Serious Injury9serious injury crashes3.4%
↓-64.0%prior 25
Minor Injury33minor injury crashes12.6%
↑32.0%prior 25
Possible Injury45possible injury crashes17.2%
↑18.4%prior 38
No Injury169no injury crashes64.8%
↓-10.6%prior 189

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between the two periods. Collisions involving an animal, the top factor in 2017 with 44 incidents, decreased by 34% to 29 incidents in 2018, falling to the third-ranked cause. 'Ran off road - straight' and 'Lost Control' became the top two factors in 2018, each cited in 30 crashes, down from 32 and 38 respectively in the prior year. Notably, crashes attributed to 'Failure to yield right-of-way from a stop sign' increased from 12 to 18 incidents.

Officer-Reported Primary Contributing Cause

Ran off road - straight30 (11.5%)↓-6.3%prior 32
Lost Control30 (11.5%)↓-21.1%prior 38
Animal29 (11.1%)↓-34.1%prior 44
Other (explain in narrative): Other23 (8.8%)↑21.1%prior 19
FTYROW: From stop sign18 (6.9%)↑50.0%prior 12
Driving too fast for conditions18 (6.9%)→0.0%prior 18
Ran off road - left14 (5.4%)→0.0%prior 14
Followed too close10 (3.8%)↓-41.2%prior 17
Operating vehicle in an reckless, erratic, careless, negligent manner9 (3.4%)↓-10.0%prior 10
Improper Backing7 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both 2018 and 2017 occurred in clear weather and daylight conditions on dry roads. However, there was a notable increase in crashes under adverse winter conditions in 2018. Crashes on snowy road surfaces more than tripled, rising from 8 to 25, and collisions on icy or frosty roads increased from 19 to 24. Similarly, crashes during snowy weather more than doubled from 9 to 20 incidents year-over-year.

Weather

Clear151 (61.6%)
↓-8.5%prior 165
Cloudy46 (18.8%)
↓-19.3%prior 57
Snow20 (8.2%)
↑122.2%prior 9
Rain11 (4.5%)
↓-31.3%prior 16
Blowing Snow10 (4.1%)
Freezing rain/drizzle3 (1.2%)
↓-62.5%prior 8
Sleet, hail2 (0.8%)
Severe Winds1 (0.4%)
Fog, smoke, smog1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight145 (59.9%)
↓-4.0%prior 151
Dark - roadway not lighted59 (24.4%)
↓-14.5%prior 69
Dark - roadway lighted19 (7.9%)
↑46.2%prior 13
Dusk10 (4.1%)
↓-16.7%prior 12
Dawn8 (3.3%)
↓-20.0%prior 10
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry165 (67.1%)
↓-12.2%prior 188
Snow25 (10.2%)
↑212.5%prior 8
Ice/frost24 (9.8%)
↑26.3%prior 19
Wet22 (8.9%)
↓-26.7%prior 30
Slush4 (1.6%)
Gravel4 (1.6%)
↓-55.6%prior 9
Sand2 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved makes in crashes during both periods. In 2018, involvement of Ford vehicles increased to 75 from 65 in the prior year, while Chevrolet vehicles decreased from 86 to 80. A notable shift occurred in the age distribution of persons involved in crashes; the 16-20 age group saw its count rise from 70 to 80, making it the largest group in 2018. In contrast, involvement of persons aged 35-44 dropped from 86 in 2017 to 48 in 2018.

Top Vehicle Makes (384 vehicles)

1
FORD75 (19.5%)
↑15.4%prior 65
2
CHEV41 (10.7%)
↓-18.0%prior 50
3
CHEVROLET39 (10.2%)
↑8.3%prior 36
4
KIA16 (4.2%)
↑23.1%prior 13
5
NR15 (3.9%)
6
JEEP14 (3.6%)
↓-17.6%prior 17
7
HONDA14 (3.6%)
↑27.3%prior 11
8
DODGE13 (3.4%)
→0.0%prior 13
9
NISS10 (2.6%)
→0.0%prior 10
10
TOYT10 (2.6%)
↓-28.6%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

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

Sex Distribution (279 persons with recorded sex)

Male167 (59.9%)
↑4.4%prior 160
Female112 (40.1%)
↓-13.2%prior 129

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 261
  • Total persons involved: 497
  • Total vehicles involved: 384

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: 2018." Published September 9, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2018-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