Yearly Traffic Safety Analysis

822 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Webster County recorded 822 total crashes, a 9.7% decrease from the 910 crashes reported in 2017. While overall collisions and injuries declined, the number of fatal crashes more than doubled from 4 to 9, and total fatalities increased from 5 to 9 year-over-year.

822

▼ -9.7%was 910

Total Crash Events

9

▲ 80.0%was 5

Persons Killed

201

▼ -29.2%was 284

Persons Injured

9

▲ 125.0%was 4

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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 collisions in Webster County showed a general downward trend, with total crashes falling by 9.7% from 910 to 822. The number of people injured also decreased by 29.2%, from 284 in 2017 to 201 in 2018. In contrast to this trend, the number of fatalities rose from 5 to 9 during the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

9

Motorists Killed

Prior: 5↑80.0%

0

Other Killed

Prior: 0→0.0%

6

Pedestrians Injured

Prior: 8↓-25.0%

5

Cyclists Injured

Prior: 7↓-28.6%

189

Motorists Injured

Prior: 268↓-29.5%

1

Other Injured

Prior: 1→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 pattern of crashes shifted between periods. In 2018, Monday was the peak day for crashes with 144 incidents, a change from 2017 when Friday was the peak with 167 crashes. The 3 p.m. hour remained the single busiest time in both years, although the crash volume during that hour decreased from 83 to 63.

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

Although total crashes decreased, their severity increased from 2017 to 2018. Fatal crashes rose from 4 to 9, increasing their share of all collisions from 0.4% to 1.1%. In contrast, crashes resulting in serious, minor, and possible injuries all decreased in both their absolute numbers and their respective percentages of the total.

Outcome by Severity (Crash Events)

Fatal9fatal crashes1.1%
↑125.0%prior 4
Serious Injury13serious injury crashes1.6%
↓-35.0%prior 20
Minor Injury56minor injury crashes6.8%
↓-20.0%prior 70
Possible Injury125possible injury crashes15.2%
↓-19.9%prior 156
No Injury619no injury crashes75.3%
↓-6.2%prior 660

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 ranking of top contributing factors changed year-over-year. Crashes involving animals became the primary factor in 2018, with the count increasing from 84 to 95 incidents. Crashes attributed to 'Driving too fast for conditions' also saw their count rise from 58 to 67. The broad 'Other' category, which led with 122 crashes in 2017, fell to the second position with 86 crashes in 2018.

Officer-Reported Primary Contributing Cause

Animal95 (11.6%)↑13.1%prior 84
Other (explain in narrative): Other86 (10.5%)↓-29.5%prior 122
Driving too fast for conditions67 (8.2%)↑15.5%prior 58
Followed too close53 (6.4%)→0.0%prior 53
FTYROW: From stop sign43 (5.2%)↓-14.0%prior 50
Ran off road - left40 (4.9%)↓-9.1%prior 44
Lost Control39 (4.7%)↑5.4%prior 37
FTYROW: Other (explain in narrative)27 (3.3%)↑200.0%prior 9
Driver Distraction: Other interior distraction26 (3.2%)↓-18.8%prior 32
FTYROW: Making left turn23 (2.8%)↓-20.7%prior 29

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

Road & Environmental Conditions

Crash conditions in 2018 showed a greater prevalence of winter-weather incidents compared to the prior year. Crashes on roads with snow or ice increased from 123 in 2017 to 162 in 2018. These incidents accounted for 19.7% of all crashes in 2018, up from a 13.5% share in 2017. Correspondingly, crashes occurring in clear weather and on dry roads decreased in total count.

Weather

Clear461 (63.4%)
↓-11.7%prior 522
Cloudy156 (21.5%)
↓-20.8%prior 197
Snow49 (6.7%)
↑16.7%prior 42
Rain31 (4.3%)
↓-29.5%prior 44
Freezing rain/drizzle17 (2.3%)
↑6.3%prior 16
Blowing Snow8 (1.1%)
↑33.3%prior 6
Fog, smoke, smog5 (0.7%)

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

Lighting

Daylight530 (73.0%)
↓-8.5%prior 579
Dark - roadway lighted89 (12.3%)
↓-34.1%prior 135
Dark - roadway not lighted67 (9.2%)
↓-15.2%prior 79
Dawn21 (2.9%)
↑40.0%prior 15
Dusk19 (2.6%)
↑11.8%prior 17

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

Road Surface

Dry449 (61.4%)
↓-23.6%prior 588
Wet94 (12.9%)
↓-6.9%prior 101
Ice/frost82 (11.2%)
↑20.6%prior 68
Snow80 (10.9%)
↑45.5%prior 55
Slush12 (1.6%)
↑100.0%prior 6
Gravel10 (1.4%)
↓-16.7%prior 12
Other (explain in narrative)2 (0.3%)
Mud, dirt2 (0.3%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles remained the two most common makes involved in crashes across both years, with both seeing a slight decrease in their total counts in 2018. An analysis of persons involved in crashes shows a 20.6% decrease for the 21-25 age group (from 170 to 135) and a 12.1% decrease for the 65+ age group (from 215 to 189). Conversely, the 45-54 age group saw a 12.1% increase in persons involved, from 157 to 176.

Top Vehicle Makes (1,422 vehicles)

1
FORD214 (15%)
↓-8.5%prior 234
2
CHEV212 (14.9%)
↑1.4%prior 209
3
DODG82 (5.8%)
↑1.2%prior 81
4
CHEVROLET77 (5.4%)
↓-36.4%prior 121
5
BUIC72 (5.1%)
↑24.1%prior 58
6
GMC68 (4.8%)
↑25.9%prior 54
7
NR65 (4.6%)
↓-18.8%prior 80
8
CHRY65 (4.6%)
↓-1.5%prior 66
9
TOYO61 (4.3%)
↓-4.7%prior 64
10
JEEP46 (3.2%)
↓-13.2%prior 53

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

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

Sex Distribution (1,068 persons with recorded sex)

Male583 (54.6%)
↓-0.3%prior 585
Female485 (45.4%)
↓-8.5%prior 530

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: 822
  • Total persons involved: 1,728
  • Total vehicles involved: 1,422

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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