Yearly Traffic Safety Analysis

123 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In 2017, Hancock County recorded 123 total crashes, a 30.9% increase from the 94 crashes reported in 2016. The most significant year-over-year change was the occurrence of two fatalities in 2017, whereas none were recorded in the prior year. Total injuries also increased by 50%, rising from 50 in 2016 to 75 in 2017.

123

▲ 30.9%was 94

Total Crash Events

2

Persons Killed

75

▲ 50.0%was 50

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 totals in Hancock County showed an upward trend, increasing by 30.9% from 94 in 2016 to 123 in 2017. This increase was also reflected in personal harm, with total injuries rising 50% from 50 to 75 and fatalities increasing from zero to two.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 0→%

75

Motorists Injured

Prior: 49↑53.1%

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 shifted between the two periods. In 2017, the peak day for crashes was Friday with 25 incidents, a change from 2016 when Saturday was the peak day with 17 crashes. The peak hour also shifted slightly later in the day, from 3 p.m. in 2016 (10 crashes) to 4 p.m. in 2017 (13 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

In 2017, Hancock County experienced two fatal crashes, accounting for 1.6% of all incidents, compared to zero fatal crashes in 2016. While the total number of injuries rose, the proportion of crashes resulting in serious injury decreased from a 6.4% share (6 crashes) in 2016 to a 2.4% share (3 crashes) in 2017. The share of no-injury crashes increased from 56.4% to 60.2% of all incidents year-over-year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.6%
Serious Injury3serious injury crashes2.4%
↓-50.0%prior 6
Minor Injury22minor injury crashes17.9%
↑37.5%prior 16
Possible Injury22possible injury crashes17.9%
↑15.8%prior 19
No Injury74no injury crashes60.2%
↑39.6%prior 53

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

The leading contributing factors shifted between 2016 and 2017. 'Lost Control' became the top factor in 2017 with 17 crashes, an increase from 15 in the prior year. Crashes attributed to 'Driving too fast for conditions' decreased from 16 to 15. Notably, incidents where a driver 'Ran off road - straight' doubled in count from 6 to 12, and crashes linked to 'Driver Distraction: Other interior distraction' increased from 1 to 6.

Officer-Reported Primary Contributing Cause

Lost Control17 (13.8%)↑13.3%prior 15
Other (explain in narrative): Other16 (13%)
Driving too fast for conditions15 (12.2%)↓-6.3%prior 16
Ran off road - straight12 (9.8%)↑100.0%prior 6
Ran off road - left10 (8.1%)
Driver Distraction: Other interior distraction6 (4.9%)
Ran Stop Sign6 (4.9%)
FTYROW: From stop sign5 (4.1%)↓-16.7%prior 6
FTYROW: At uncontrolled intersection4 (3.3%)
FTYROW: Making left turn3 (2.4%)

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

Road & Environmental Conditions

In both 2016 and 2017, the majority of crashes occurred in clear weather and during daylight hours. However, the number of crashes under adverse conditions saw an increase; incidents on icy or frosty roads rose from 12 to 18, and crashes in darkness on unlighted roadways increased from 16 to 26. The proportion of crashes on dry roads decreased from a 57.4% share in 2016 to a 55.3% share in 2017.

Weather

Clear69 (59.0%)
↑19.0%prior 58
Cloudy24 (20.5%)
↑41.2%prior 17
Rain6 (5.1%)
Freezing rain/drizzle5 (4.3%)
Blowing Snow4 (3.4%)
Snow4 (3.4%)
↓-20.0%prior 5
Severe Winds4 (3.4%)
Fog, smoke, smog1 (0.9%)

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

Lighting

Daylight81 (68.6%)
↑30.6%prior 62
Dark - roadway not lighted26 (22.0%)
↑62.5%prior 16
Dark - roadway lighted6 (5.1%)
↓-25.0%prior 8
Dusk3 (2.5%)
Dawn1 (0.8%)
Dark - unknown roadway lighting1 (0.8%)

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

Road Surface

Dry68 (56.7%)
↑25.9%prior 54
Ice/frost18 (15.0%)
↑50.0%prior 12
Snow13 (10.8%)
↑62.5%prior 8
Wet11 (9.2%)
↑22.2%prior 9
Gravel7 (5.8%)
→0.0%prior 7
Oil2 (1.7%)
Mud, dirt1 (0.8%)

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 top two vehicle makes involved in crashes in both periods, with the count of Fords increasing from 37 to 49 and Chevrolets increasing from 38 to 44. An analysis of persons involved shows a shift in the most represented age group, moving from 16-20 year olds in 2016 (35 people) to 21-25 year olds in 2017 (39 people). The number of individuals aged 26-34 involved in crashes increased from 13 to 34.

Top Vehicle Makes (194 vehicles)

1
FORD49 (25.3%)
↑32.4%prior 37
2
CHEV28 (14.4%)
↑40.0%prior 20
3
CHEVROLET16 (8.2%)
↓-11.1%prior 18
4
PONT10 (5.2%)
5
BUIC8 (4.1%)
6
TOYT7 (3.6%)
7
CHRY6 (3.1%)
8
HOND6 (3.1%)
9
DODG5 (2.6%)
10
GMC5 (2.6%)
→0.0%prior 5

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

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

Sex Distribution (138 persons with recorded sex)

Male76 (55.1%)
↓-7.3%prior 82
Female62 (44.9%)
↑106.7%prior 30

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: 123
  • Total persons involved: 245
  • Total vehicles involved: 194

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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