Yearly Traffic Safety Analysis

55 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In Wayne County, total traffic crashes increased by 12.2%, from 49 incidents in 2016 to 55 in 2017. While the overall number of injuries decreased, the most significant year-over-year change was the emergence of fatal crashes, with four recorded in 2017 compared to none in the prior year.

55

▲ 12.2%was 49

Total Crash Events

4

Persons Killed

23

▼ -17.9%was 28

Persons Injured

4

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 · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Wayne County showed a mixed picture year-over-year. The total number of crashes rose from 49 to 55, and tragically, fatalities increased from zero to four. In contrast, the total number of people injured in crashes declined by 17.9%, from 28 in 2016 to 23 in 2017.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

23

Motorists Injured

Prior: 28↓-17.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2017, Saturday was the most frequent day for crashes with 13 incidents, a change from 2016 when Wednesday was the peak day with 12 crashes. The peak hour for collisions also changed, moving from 4 p.m. in 2016 (6 crashes) to a dual peak at 7 a.m. and 12 p.m. in 2017, each with 5 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened significantly in 2017 compared to 2016. Fatal crashes, which were absent in 2016, accounted for 4 incidents (7.3% of all crashes) in 2017. The number of serious injury crashes also increased from one to three. Conversely, crashes resulting in minor injuries decreased from 11 in 2016 to 5 in 2017.

Outcome by Severity (Crash Events)

Fatal4fatal crashes7.3%
Serious Injury3serious injury crashes5.5%
↑200.0%prior 1
Minor Injury5minor injury crashes9.1%
↓-54.5%prior 11
Possible Injury10possible injury crashes18.2%
↑11.1%prior 9
No Injury33no injury crashes60%
↑17.9%prior 28

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, increasing from 9 incidents in 2016 to 11 in 2017. The count of crashes attributed to 'Lost Control' also grew, rising from 5 to 9 incidents. In contrast, crashes where 'Driving too fast for conditions' was a factor decreased from 6 incidents in 2016 to 3 in 2017.

Officer-Reported Primary Contributing Cause

Animal11 (20%)↑22.2%prior 9
Lost Control9 (16.4%)↑80.0%prior 5
Ran off road - straight4 (7.3%)↓-20.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner3 (5.5%)
Driving too fast for conditions3 (5.5%)↓-50.0%prior 6
Swerving/Evasive Action3 (5.5%)
FTYROW: At uncontrolled intersection3 (5.5%)
Followed too close2 (3.6%)
Other (explain in narrative): Other2 (3.6%)
Passing: Other passing (explain in narrative)2 (3.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While most crashes in both years occurred in clear weather and on dry roads, there was a notable shift in incidents during cloudy conditions. The number of crashes in cloudy weather more than tripled, increasing from 3 in 2016 to 10 in 2017. Consequently, their share of total crashes rose from 6.1% to 18.2%. The distribution of crashes by lighting and road surface conditions remained relatively stable year-over-year.

Weather

Clear39 (75.0%)
↑8.3%prior 36
Cloudy10 (19.2%)
Fog, smoke, smog2 (3.8%)
Rain1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight35 (67.3%)
↑20.7%prior 29
Dark - roadway not lighted13 (25.0%)
↑18.2%prior 11
Dark - roadway lighted2 (3.8%)
Dawn2 (3.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry32 (61.5%)
↑23.1%prior 26
Gravel12 (23.1%)
↑20.0%prior 10
Wet3 (5.8%)
Slush2 (3.8%)
Snow2 (3.8%)
Other (explain in narrative)1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, remained consistent across both years. A significant demographic shift occurred among persons involved in crashes; the 45-54 age group saw its representation more than double, from 9 individuals in 2016 to 23 in 2017. Conversely, the number of individuals in the 16-20 age group decreased from 23 to 20.

Top Vehicle Makes (80 vehicles)

1
FORD17 (21.3%)
↑21.4%prior 14
2
CHEVROLET13 (16.3%)
↑44.4%prior 9
3
CHEV9 (11.3%)
↓-10.0%prior 10
4
DODG6 (7.5%)
5
DODGE4 (5%)
6
DEER3 (3.8%)
7
TOYT3 (3.8%)
8
INTERNATIONA2 (2.5%)
9
KIA2 (2.5%)
10
PETERBILT2 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records

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

Sex Distribution (57 persons with recorded sex)

Male39 (68.4%)
↑25.8%prior 31
Female18 (31.6%)
↓-5.3%prior 19

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 55
  • Total persons involved: 90
  • Total vehicles involved: 80

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: 2017." Published September 9, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2017-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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