Yearly Traffic Safety Analysis

264 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In 2016, Delaware County recorded 264 total crashes, a 2.9% decrease from the 272 crashes reported in 2015. Despite the slight drop in total collisions, the number of fatalities doubled from 2 to 4. Conversely, the total number of injuries saw a substantial decrease of 44.6%, falling from 112 in 2015 to 62 in 2016.

264

▼ -2.9%was 272

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

62

▼ -44.6%was 112

Persons Injured

4

▲ 100.0%was 2

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 · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Delaware County saw a slight year-over-year decline, with total crashes decreasing by 2.9% from 272 in 2015 to 264 in 2016. However, the severity of outcomes shifted, as fatal crashes doubled from 2 to 4. In contrast, the number of people injured in crashes fell significantly from 112 to 62, a 44.6% reduction.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 1↑300.0%

1

Pedestrians Injured

Prior: 1→0.0%

3

Cyclists Injured

Prior: 0→%

58

Motorists Injured

Prior: 111↓-47.7%

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 showed some changes between 2015 and 2016. The most frequent day for crashes shifted from Monday (48 crashes) in 2015 to Saturday (50 crashes) in 2016. The peak hour for collisions remained consistent at 3 p.m. in both years, with crash counts of 21 in 2015 and 24 in 2016 during that hour.

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

Crash severity worsened in 2016, with the number of fatal crashes doubling from 2 to 4, increasing the fatal crash rate from 0.7% to 1.5% of all collisions. While fatal incidents rose, the total count of crashes resulting in any injury decreased slightly from 57 in 2015 to 54 in 2016. The proportion of crashes involving a serious injury fell from 1.5% to 1.1% year-over-year.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.5%
↑100.0%prior 2
Serious Injury3serious injury crashes1.1%
↓-25.0%prior 4
Minor Injury24minor injury crashes9.1%
↓-17.2%prior 29
Possible Injury27possible injury crashes10.2%
↑12.5%prior 24
No Injury206no injury crashes78%
↓-3.3%prior 213

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 in Delaware County remained consistent year-over-year, with collisions involving an "Animal" being the most common cause in both 2015 (82 crashes) and 2016 (79 crashes). "Lost Control" (33 down to 29 crashes) and "Ran off road - straight" (21 down to 19 crashes) also remained top factors, with slight decreases in their counts. A notable increase was observed in crashes where a driver "Ran Stop Sign," which rose from 3 incidents in 2015 to 11 in 2016, representing a 267% increase in count.

Officer-Reported Primary Contributing Cause

Animal79 (29.9%)↓-3.7%prior 82
Lost Control29 (11%)↓-12.1%prior 33
Ran off road - straight19 (7.2%)↓-9.5%prior 21
FTYROW: From stop sign12 (4.5%)↑9.1%prior 11
Followed too close12 (4.5%)↓-7.7%prior 13
Ran Stop Sign11 (4.2%)
Other (explain in narrative): Other11 (4.2%)↓-15.4%prior 13
Driving too fast for conditions8 (3%)↓-33.3%prior 12
Ran off road - left7 (2.7%)↑16.7%prior 6
FTYROW: Making left turn6 (2.3%)↓-25.0%prior 8

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 distribution of crashes across different environmental conditions remained largely stable between 2015 and 2016. Crashes in daylight accounted for approximately 49% of all incidents in both years. The proportion of collisions occurring on dry road surfaces increased slightly from 46.3% in 2015 to 49.2% in 2016. The number of crashes reported during adverse weather, such as rain (down from 15 to 9) and snow (down from 14 to 9), saw a decrease.

Weather

Clear133 (68.6%)
↑8.1%prior 123
Cloudy32 (16.5%)
↓-13.5%prior 37
Snow9 (4.6%)
↓-35.7%prior 14
Rain9 (4.6%)
↓-40.0%prior 15
Blowing Snow4 (2.1%)
Freezing rain/drizzle3 (1.5%)
Fog, smoke, smog2 (1.0%)
Severe Winds1 (0.5%)
Sleet, hail1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash

Lighting

Daylight130 (66.3%)
↓-3.0%prior 134
Dark - roadway not lighted42 (21.4%)
↑2.4%prior 41
Dark - roadway lighted11 (5.6%)
↓-26.7%prior 15
Dawn6 (3.1%)
Dusk6 (3.1%)
↓-14.3%prior 7
Dark - unknown roadway lighting1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field

Road Surface

Dry130 (66.7%)
↑3.2%prior 126
Wet20 (10.3%)
↓-20.0%prior 25
Snow16 (8.2%)
↓-27.3%prior 22
Gravel15 (7.7%)
↓-6.3%prior 16
Slush7 (3.6%)
Ice/frost6 (3.1%)
↓-40.0%prior 10
Mud, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet (101 vehicles), Ford (46), and Dodge (33) being the most frequent in 2016. While Chevrolet and Dodge involvement was stable, the number of Fords in crashes decreased from 70 in 2015. An analysis of persons involved shows a shift in age demographics; the proportion of individuals aged 16-20 decreased from 17.7% to 13.6%, while the 26-34 age group's representation increased from 9.3% to 15.5% of all persons involved.

Top Vehicle Makes (370 vehicles)

1
CHEVROLET54 (14.6%)
↑38.5%prior 39
2
CHEV47 (12.7%)
↓-24.2%prior 62
3
FORD46 (12.4%)
↓-34.3%prior 70
4
DODG18 (4.9%)
↑28.6%prior 14
5
GMC16 (4.3%)
↑166.7%prior 6
6
DODGE15 (4.1%)
↓-21.1%prior 19
7
BUIC11 (3%)
↑22.2%prior 9
8
PONT11 (3%)
↓-35.3%prior 17
9
TOYOTA10 (2.7%)
↑11.1%prior 9
10
JEEP8 (2.2%)
↑14.3%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records

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

Sex Distribution (285 persons with recorded sex)

Male163 (57.2%)
↓-26.2%prior 221
Female122 (42.8%)
↓-10.3%prior 136

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: 264
  • Total persons involved: 420
  • Total vehicles involved: 370

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