Yearly Traffic Safety Analysis

319 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Harrison County, total traffic crashes decreased by 8.6% from 349 in 2017 to 319 in 2018. While the number of fatalities remained constant at five, the most notable year-over-year change was a 32.4% reduction in total injuries, which fell from 139 to 94. Crashes involving driving under the influence also declined from 17 to 12.

319

▼ -8.6%was 349

Total Crash Events

5

Persons Killed

94

▼ -32.4%was 139

Persons Injured

3

▼ -25.0%was 4

Fatal Crash Events

Note: "Persons Killed" (5) 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 · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Harrison County showed improvement from 2017 to 2018. The total number of crashes fell by 8.6%, from 349 to 319. This positive trend was accompanied by a significant 32.4% decrease in persons injured, dropping from 139 to 94, while total fatalities were unchanged at five for both years.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 5→0.0%

1

Pedestrians Injured

Prior: 3↓-66.7%

1

Cyclists Injured

Prior: 0→%

92

Motorists Injured

Prior: 136↓-32.4%

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 showed a notable shift between the two years. While the peak day for crashes remained mid-week (shifting from a Wednesday/Thursday tie at 59 crashes in 2017 to solely Wednesday in 2018 with 56 crashes), the peak hour changed significantly. In 2017, the most crashes occurred at 3 p.m. (35 incidents), whereas in 2018 the peak shifted to 9 p.m. (25 incidents).

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

The severity of crashes lessened from 2017 to 2018. The number of fatal crashes decreased from 4 to 3, and the fatal crash rate dipped from 1.1% to 0.9% of all crashes. Crashes resulting in any form of injury (serious, minor, or possible) declined from 96 incidents in 2017 to 67 in 2018. Consequently, the proportion of crashes with no injuries increased from 71.3% in 2017 to 78.1% in 2018, even though the absolute count of such crashes was identical at 249 in both years.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
↓-25.0%prior 4
Serious Injury12serious injury crashes3.8%
↓-25.0%prior 16
Minor Injury28minor injury crashes8.8%
↓-24.3%prior 37
Possible Injury27possible injury crashes8.5%
↓-37.2%prior 43
No Injury249no injury crashes78.1%
→0.0%prior 249

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

Collisions with animals remained the leading contributing factor for crashes in both 2017 and 2018, though the count of these incidents decreased by 15.7% from 89 to 75. The second-ranked factor, 'Lost Control,' saw its count remain nearly stable, declining from 41 to 40 incidents. 'Followed too close' moved into the top three factors in 2018 with 23 crashes, a slight increase from 21 in the prior year. Meanwhile, crashes attributed to 'Driving too fast for conditions' decreased from 21 to 18.

Officer-Reported Primary Contributing Cause

Animal75 (23.5%)↓-15.7%prior 89
Lost Control40 (12.5%)↓-2.4%prior 41
Followed too close23 (7.2%)↑9.5%prior 21
Ran off road - left22 (6.9%)↑46.7%prior 15
Driving too fast for conditions18 (5.6%)↓-14.3%prior 21
Ran off road - straight17 (5.3%)↓-26.1%prior 23
Operating vehicle in an reckless, erratic, careless, negligent manner16 (5%)↑100.0%prior 8
Other (explain in narrative): Other14 (4.4%)↑27.3%prior 11
Ran Stop Sign7 (2.2%)
FTYROW: From stop sign6 (1.9%)↓-45.5%prior 11

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

Road & Environmental Conditions

While overall crash numbers declined, there was a notable shift in the conditions under which they occurred. Crashes on wet roads increased by 77.3%, from 22 incidents in 2017 to 39 in 2018. Correspondingly, crashes during rain doubled from 11 to 22. Despite this, the majority of collisions in both years happened in clear weather (172 in 2018 vs. 182 in 2017) and on dry roads (177 in 2018 vs. 200 in 2017).

Weather

Clear172 (64.4%)
↓-5.5%prior 182
Cloudy48 (18.0%)
→0.0%prior 48
Rain22 (8.2%)
↑100.0%prior 11
Snow14 (5.2%)
↑55.6%prior 9
Blowing Snow4 (1.5%)
Freezing rain/drizzle2 (0.7%)
↓-80.0%prior 10
Sleet, hail2 (0.7%)
Fog, smoke, smog2 (0.7%)
Severe Winds1 (0.4%)

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

Lighting

Daylight172 (63.9%)
↓-2.8%prior 177
Dark - roadway not lighted61 (22.7%)
↓-7.6%prior 66
Dark - roadway lighted19 (7.1%)
↑5.6%prior 18
Dusk13 (4.8%)
↑85.7%prior 7
Dawn4 (1.5%)
↓-42.9%prior 7

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

Road Surface

Dry177 (66.3%)
↓-11.5%prior 200
Wet39 (14.6%)
↑77.3%prior 22
Ice/frost18 (6.7%)
↓-18.2%prior 22
Snow12 (4.5%)
↑71.4%prior 7
Gravel11 (4.1%)
↓-35.3%prior 17
Slush9 (3.4%)
Mud, dirt1 (0.4%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford and Chevrolet being the most frequent in both years. The number of Fords involved decreased from 82 to 72, and Chevrolets (including 'CHEV' and 'CHEVROLET' variants) decreased from 111 to 85. Analysis of persons involved shows a demographic shift; the number of individuals in the 16-20 age group decreased from 91 to 70, while those in the 26-34 age group increased from 79 to 93.

Top Vehicle Makes (443 vehicles)

1
FORD72 (16.3%)
↓-12.2%prior 82
2
CHEV49 (11.1%)
↓-10.9%prior 55
3
CHEVROLET36 (8.1%)
↓-35.7%prior 56
4
DODG19 (4.3%)
↑46.2%prior 13
5
TOYOTA17 (3.8%)
↑13.3%prior 15
6
DODGE15 (3.4%)
↓-42.3%prior 26
7
GMC14 (3.2%)
↓-6.7%prior 15
8
JEEP14 (3.2%)
↓-22.2%prior 18
9
INTERNATIONA11 (2.5%)
↑37.5%prior 8
10
FREIGHTLINER11 (2.5%)
→0.0%prior 11

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

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

Sex Distribution (322 persons with recorded sex)

Male205 (63.7%)
↓-4.2%prior 214
Female117 (36.3%)
↑4.5%prior 112

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: 319
  • Total persons involved: 544
  • Total vehicles involved: 443

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

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