Yearly Traffic Safety Analysis

372 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In Plymouth County, total crashes decreased from 422 in 2016 to 372 in 2017, a drop of nearly 12%. Despite the overall reduction in collisions, the number of fatalities increased from 3 to 4, and the number of fatal crashes rose from 3 to 4 during the same period.

372

▼ -11.8%was 422

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

180

▲ 1.1%was 178

Persons Injured

4

▲ 33.3%was 3

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

Crash data for Plymouth County indicates a downward trend in the total number of collisions, which fell from 422 in 2016 to 372 in 2017, a decrease of 11.9%. While the total number of crashes declined, total injuries saw a slight increase from 178 to 180, and fatalities rose from 3 to 4 year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

0

Other Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 3↓-33.3%

6

Cyclists Injured

Prior: 5↑20.0%

171

Motorists Injured

Prior: 170↑0.6%

1

Other Injured

Prior: 0→%

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 temporal patterns of crashes showed some shifts between 2016 and 2017. While Friday remained the peak day for crashes in both years, the count on that day decreased from 85 to 66. The peak hour for collisions moved from 3 p.m. in 2016 (39 crashes) to 7 a.m. in 2017 (28 crashes), indicating a shift in focus from the afternoon to the morning commute.

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

The severity of crashes increased in 2017 compared to the prior year. The fatal crash rate rose from 0.71% to 1.08%, with 4 fatal crashes in 2017 versus 3 in 2016. The proportion of crashes resulting in any level of injury also increased, from 30.5% in 2016 to 33.9% in 2017, driven by a rise in the share of serious injury crashes from 3.8% to 5.4%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.1%
↑33.3%prior 3
Serious Injury20serious injury crashes5.4%
↑25.0%prior 16
Minor Injury52minor injury crashes14%
↓-5.5%prior 55
Possible Injury54possible injury crashes14.5%
↓-6.9%prior 58
No Injury242no injury crashes65.1%
↓-16.6%prior 290

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 periods, with a nearly identical count of 87 crashes in 2017 compared to 88 in 2016. The count of crashes attributed to 'Lost Control' increased from 32 to 39, making it the second most common factor in 2017. Conversely, incidents of 'Followed too close' saw a notable decrease in count from 29 to 18, falling from the third-ranked factor in 2016 to seventh in 2017.

Officer-Reported Primary Contributing Cause

Animal87 (23.4%)↓-1.1%prior 88
Lost Control39 (10.5%)↑21.9%prior 32
FTYROW: From stop sign21 (5.6%)↓-12.5%prior 24
Other (explain in narrative): Other20 (5.4%)↑25.0%prior 16
Ran off road - left18 (4.8%)↓-35.7%prior 28
Ran off road - straight18 (4.8%)↓-14.3%prior 21
Followed too close18 (4.8%)↓-37.9%prior 29
Driving too fast for conditions15 (4%)↓-6.3%prior 16
FTYROW: At uncontrolled intersection12 (3.2%)↓-42.9%prior 21
Ran Stop Sign11 (3%)↑22.2%prior 9

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

Road & Environmental Conditions

The proportion of crashes occurring on dry road surfaces increased from 62.0% in 2016 to 73.8% in 2017, while the absolute number of crashes on adverse surfaces like snow, ice, and wet roads declined. Crashes during daylight hours decreased from 236 to 192, representing a smaller share of total incidents (51.6% in 2017 vs. 55.9% in 2016). Similarly, crashes reported during snowy weather conditions fell from 22 to 14.

Weather

Clear194 (65.5%)
↓-12.2%prior 221
Cloudy69 (23.3%)
↓-16.9%prior 83
Snow14 (4.7%)
↓-36.4%prior 22
Rain10 (3.4%)
↑11.1%prior 9
Fog, smoke, smog3 (1.0%)
Freezing rain/drizzle3 (1.0%)
↓-40.0%prior 5
Severe Winds1 (0.3%)
Other (explain in narrative)1 (0.3%)
Blowing Snow1 (0.3%)
↓-80.0%prior 5

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

Lighting

Daylight192 (64.9%)
↓-18.6%prior 236
Dark - roadway not lighted64 (21.6%)
↓-16.9%prior 77
Dark - roadway lighted25 (8.4%)
↓-7.4%prior 27
Dawn8 (2.7%)
↑14.3%prior 7
Dusk6 (2.0%)
↑20.0%prior 5
Dark - unknown roadway lighting1 (0.3%)

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

Road Surface

Dry223 (75.1%)
↓-6.3%prior 238
Snow24 (8.1%)
↓-22.6%prior 31
Wet20 (6.7%)
↓-35.5%prior 31
Gravel12 (4.0%)
↑33.3%prior 9
Ice/frost11 (3.7%)
↓-65.6%prior 32
Sand5 (1.7%)
↓-16.7%prior 6
Mud, dirt1 (0.3%)
Slush1 (0.3%)
↓-80.0%prior 5

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

Vehicles & Demographics

Ford and Chevrolet remained the two most common vehicle makes involved in crashes, though both saw a reduction in count from the previous year; Fords involved dropped from 109 to 90, and Chevrolets decreased from a combined 151 to 108. Analysis of person demographics shows a decrease in the involvement of the 16-20 age group, which fell from 125 individuals in 2016 to 94 in 2017. Conversely, the number of individuals aged 65 and older involved in crashes increased from 66 to 76.

Top Vehicle Makes (552 vehicles)

1
FORD90 (16.3%)
↓-17.4%prior 109
2
CHEV65 (11.8%)
↑10.2%prior 59
3
CHEVROLET43 (7.8%)
↓-53.3%prior 92
4
BUIC25 (4.5%)
↑56.3%prior 16
5
DODG25 (4.5%)
→0.0%prior 25
6
GMC20 (3.6%)
↓-23.1%prior 26
7
PONTIAC17 (3.1%)
↓-5.6%prior 18
8
DODGE15 (2.7%)
→0.0%prior 15
9
JEEP15 (2.7%)
↓-16.7%prior 18
10
CHRYSLER13 (2.4%)
↑18.2%prior 11

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

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

Sex Distribution (391 persons with recorded sex)

Male236 (60.4%)
↓-19.5%prior 293
Female155 (39.6%)
↓-16.7%prior 186

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: 372
  • Total persons involved: 698
  • Total vehicles involved: 552

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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