ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · 2016
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2016-annual-report
Yearly Traffic Safety Analysis
176 CRASHES IN
IOWA, IA
2016
In 2016, O'Brien County recorded 176 total crashes, a 24.8% increase from the 141 crashes reported in 2015. While total crashes and injuries (84 in 2016 vs. 59 in 2015) rose, the number of fatalities decreased from 4 to 1 over the same period. The most significant year-over-year shift was the nearly 25% rise in overall crash incidents.
176
▲ 24.8%was 141
Total Crash Events
1
▼ -75.0%was 4
Persons Killed
84
▲ 42.4%was 59
Persons Injured
1
▼ -66.7%was 3
Fatal Crash Events
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in O'Brien County showed a notable increase year-over-year. Total crashes rose by 24.8%, from 141 in 2015 to 176 in 2016. This increase was accompanied by a 42.4% rise in total injuries, from 59 to 84, although fatalities declined from 4 to 1.
Vulnerable Road User Casualties
1
Cyclists Killed
0
Motorists Killed
0
Cyclists Injured
84
Motorists Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · 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 largely consistent between 2015 and 2016. The peak day for crashes was Friday in both years (30 in 2015, 33 in 2016), and the peak hour was the 4 PM hour (15 in 2015, 19 in 2016). While the peak times were stable, there was a notable increase in crashes occurring on Tuesdays, which rose from 18 to 32 incidents year-over-year.
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the severity of those crashes shifted. The number of fatal crashes decreased from 3 in 2015 to 1 in 2016, with the fatal crash rate dropping from 2.13% to 0.57%. Conversely, the number and proportion of crashes resulting in minor or possible injuries increased. Minor injury crashes rose from 15 to 25, and possible injury crashes grew from 22 to 31, contributing to an overall rise in the percentage of crashes involving any injury from 31.2% to 35.2%.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes shifted between 2015 and 2016. In 2016, 'Failure to yield from a stop sign' became the most cited factor with 18 crashes, an increase from 13 incidents in the prior year. Incidents attributed to 'Lost Control' more than doubled, rising from 6 to 14 crashes, while 'Improper Backing' also saw a significant increase from 3 to 11 crashes. Conversely, 'Ran off road - left,' which was the top factor in 2015 with 18 crashes, decreased to 13 crashes in 2016.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring during daylight and in clear weather remained stable year-over-year. However, there was a notable shift in road surface conditions at the time of crashes. The percentage of incidents on dry roads decreased from 68.1% in 2015 to 60.8% in 2016. Correspondingly, the number of crashes on adverse road surfaces like ice, wet, snow, or slush increased from 30 in 2015 to 53 in 2016, representing a rise in share from 21.3% to 30.1% of all crashes.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes saw some shifts between periods. While Ford and Chevrolet remained the top two makes involved in both years, the number of Dodge vehicles involved increased from 16 in 2015 to 29 in 2016. Regarding persons involved, there was a notable increase in the 26-34 age group (from 47 to 62 individuals) and the 55-64 age group (from 30 to 48 individuals). The overall increase in persons involved was driven primarily by males, whose count rose from 112 to 135, while the number of females involved remained stable.
Top Vehicle Makes (298 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (222 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-12-31 (366 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 176
- Total persons involved: 346
- Total vehicles involved: 298
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: 2016." Published September 9, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2016-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2016-01-01 – 2016-12-31
Generated: September 9, 2026 · All rights reserved