Yearly Traffic Safety Analysis

271 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Delaware County, total traffic crashes increased by 24.3%, rising from 218 in 2017 to 271 in 2018. This period also saw a doubling in traffic fatalities, from 2 to 4. The most significant contributing factor to crashes in both years was collisions with animals, though the number of crashes attributed to running off the road and failure to yield from a stop sign saw substantial increases in 2018.

271

▲ 24.3%was 218

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

69

▲ 23.2%was 56

Persons Injured

4

▲ 100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

Year-over-year data indicates a rising trend in traffic collisions in Delaware County. The total number of crashes grew from 218 in 2017 to 271 in 2018, a 24.3% increase. Correspondingly, the number of people injured rose by 23.2% from 56 to 69, and total fatalities doubled from two to four.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 2↑100.0%

1

Pedestrians Injured

Prior: 1→0.0%

2

Cyclists Injured

Prior: 0→%

66

Motorists Injured

Prior: 54↑22.2%

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 broadly similar year-over-year, though with higher volumes in 2018. Monday was the peak day for crashes in both 2017 (41 crashes) and 2018 (55 crashes). The peak hour for collisions shifted slightly, moving from 5 p.m. in 2017 (23 crashes) to 6 p.m. in 2018 (24 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

The severity of crashes shifted in 2018 compared to the prior year. The number of fatal crashes doubled from 2 to 4, increasing their share of all crashes from 0.9% to 1.5%. While the count of serious injury crashes decreased from 8 to 5, minor injury crashes saw a significant rise, increasing from 15 in 2017 to 28 in 2018. Consequently, minor injury crashes accounted for 10.3% of all incidents in 2018, up from 6.9% in the previous year.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.5%
↑100.0%prior 2
Serious Injury5serious injury crashes1.8%
↓-37.5%prior 8
Minor Injury28minor injury crashes10.3%
↑86.7%prior 15
Possible Injury24possible injury crashes8.9%
↓-7.7%prior 26
No Injury210no injury crashes77.5%
↑25.7%prior 167

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 an animal remained the leading contributing factor in both periods, with a slight increase in count from 86 incidents in 2017 to 89 in 2018. However, other factors saw more substantial growth. Crashes attributed to 'Ran off road - straight' increased from 7 to 19 incidents. Similarly, crashes involving 'Failure to yield right-of-way from a stop sign' increased by 150% in count, from 6 to 15, and those related to 'Driving too fast for conditions' rose from 6 to 13.

Officer-Reported Primary Contributing Cause

Animal89 (32.8%)↑3.5%prior 86
Lost Control24 (8.9%)↓-11.1%prior 27
Ran off road - straight19 (7%)↑171.4%prior 7
FTYROW: From stop sign15 (5.5%)↑150.0%prior 6
Followed too close13 (4.8%)→0.0%prior 13
Driving too fast for conditions13 (4.8%)↑116.7%prior 6
Other (explain in narrative): Other11 (4.1%)↑57.1%prior 7
Made improper turn8 (3%)
FTYROW: Making left turn7 (2.6%)↑40.0%prior 5
Ran off road - left7 (2.6%)

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 crashes in clear weather and on dry roads increased in line with the overall trend, there was a notable shift in collisions involving adverse road conditions. The number of crashes occurring on snowy road surfaces increased from 2 incidents in 2017 to 18 in 2018. In contrast, crashes on icy or frosty roads decreased from 13 to 9. The proportion of crashes in daylight (45.4% in 2018 vs. 44.0% in 2017) and darkness without streetlights (18.5% vs. 16.5%) remained relatively stable.

Weather

Clear140 (70.0%)
↑38.6%prior 101
Cloudy35 (17.5%)
↑29.6%prior 27
Snow11 (5.5%)
↑83.3%prior 6
Rain9 (4.5%)
↑50.0%prior 6
Freezing rain/drizzle3 (1.5%)
Sleet, hail1 (0.5%)
Blowing Snow1 (0.5%)

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

Lighting

Daylight123 (61.2%)
↑28.1%prior 96
Dark - roadway not lighted50 (24.9%)
↑38.9%prior 36
Dusk10 (5.0%)
Dark - roadway lighted10 (5.0%)
↑42.9%prior 7
Dawn6 (3.0%)
Dark - unknown roadway lighting2 (1.0%)

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

Road Surface

Dry138 (68.7%)
↑25.5%prior 110
Snow18 (9.0%)
Wet15 (7.5%)
↑50.0%prior 10
Gravel11 (5.5%)
↑37.5%prior 8
Ice/frost9 (4.5%)
↓-30.8%prior 13
Slush8 (4.0%)
Other (explain in narrative)1 (0.5%)
Mud, dirt1 (0.5%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Chevrolet and Ford, maintained their top rankings in 2018 with increased counts reflecting the overall rise in collisions. A significant demographic shift occurred in the age of persons involved in crashes. The number of people in the 55-64 age group involved in collisions more than doubled, from 32 in 2017 to 65 in 2018. The 65+ age group also saw a substantial increase in involvement, rising from 47 to 65 persons.

Top Vehicle Makes (381 vehicles)

1
CHEV79 (20.7%)
↑58.0%prior 50
2
FORD74 (19.4%)
↑57.4%prior 47
3
DODG26 (6.8%)
↑136.4%prior 11
4
CHEVROLET17 (4.5%)
↓-37.0%prior 27
5
GMC16 (4.2%)
↑33.3%prior 12
6
JEEP14 (3.7%)
↑16.7%prior 12
7
CHRY13 (3.4%)
↑116.7%prior 6
8
PONT12 (3.1%)
9
TOYT9 (2.4%)
↑80.0%prior 5
10
BUIC9 (2.4%)
↓-35.7%prior 14

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

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

Sex Distribution (310 persons with recorded sex)

Male182 (58.7%)
↑49.2%prior 122
Female128 (41.3%)
↑48.8%prior 86

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: 271
  • Total persons involved: 479
  • Total vehicles involved: 381

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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