Yearly Traffic Safety Analysis

696 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In Warren County, total traffic crashes decreased slightly from 707 in 2015 to 696 in 2016, a change of -1.6%. Despite the drop in total incidents, the number of people injured increased by 7.0% from 227 to 243. The most significant shift in crash causation was a decrease in collisions involving animals, which fell from 148 to 129 incidents, though it remained the top contributing factor.

696

▼ -1.6%was 707

Total Crash Events

8

▼ -27.3%was 11

Persons Killed

243

▲ 7.0%was 227

Persons Injured

8

▼ -11.1%was 9

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 traffic safety trends in Warren County showed a slight improvement in the total number of crashes, which fell by 1.6% from 707 in 2015 to 696 in 2016. The number of fatalities also decreased from 11 to 8. However, this was contrasted by a 7.0% year-over-year increase in the number of people injured, which rose from 227 to 243.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

8

Motorists Killed

Prior: 11↓-27.3%

0

Other Killed

Prior: 0→0.0%

2

Cyclists Injured

Prior: 5↓-60.0%

239

Motorists Injured

Prior: 218↑9.6%

2

Other Injured

Prior: 1↑100.0%

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 in Warren County remained highly consistent year-over-year. Friday was the peak day for crashes in both 2016 (123 crashes) and 2015 (127 crashes). Similarly, the 4 p.m. hour was the most frequent time for incidents in both periods, with 65 crashes in 2016 and 61 in 2015. The morning and afternoon commute hours continued to be the periods with the highest crash volumes in both years.

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 the number of fatal crashes decreased from 9 in 2015 to 8 in 2016, the proportion of crashes resulting in serious or minor injuries increased. Serious injury crashes rose from 18 incidents (2.5% of total) to 22 incidents (3.2% of total). In parallel, the share of no-injury crashes fell from 73.4% in 2015 to 71.7% in 2016, indicating a higher likelihood of injury when a crash occurred.

Outcome by Severity (Crash Events)

Fatal8fatal crashes1.1%
↓-11.1%prior 9
Serious Injury22serious injury crashes3.2%
↑22.2%prior 18
Minor Injury77minor injury crashes11.1%
↑18.5%prior 65
Possible Injury90possible injury crashes12.9%
↓-6.3%prior 96
No Injury499no injury crashes71.7%
↓-3.9%prior 519

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

Collisions involving an animal remained the top contributing factor in both periods, although the count of such incidents decreased from 148 in 2015 to 129 in 2016. 'Lost Control' was the second-most common factor and also saw a decrease in count from 65 to 59 crashes. Conversely, incidents attributed to 'Driving too fast for conditions' increased from 22 to 38, and crashes where a driver 'Followed too close' rose from 34 to 45.

Officer-Reported Primary Contributing Cause

Animal129 (18.5%)↓-12.8%prior 148
Lost Control59 (8.5%)↓-9.2%prior 65
FTYROW: From stop sign47 (6.8%)↑9.3%prior 43
Followed too close45 (6.5%)↑32.4%prior 34
Ran off road - left40 (5.7%)↓-4.8%prior 42
Driving too fast for conditions38 (5.5%)↑72.7%prior 22
Ran off road - straight36 (5.2%)↓-10.0%prior 40
FTYROW: Making left turn30 (4.3%)↓-30.2%prior 43
Other (explain in narrative): Other29 (4.2%)↓-9.4%prior 32
Driver Distraction: Other interior distraction21 (3%)↑40.0%prior 15

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 majority of crashes in both periods occurred in daylight on dry roads, with the proportions remaining stable year-over-year. However, there was a shift in reported weather conditions, as the share of crashes in clear weather decreased from 58.4% in 2015 to 54.0% in 2016. Concurrently, the proportion of crashes during cloudy conditions rose from 16.1% to 21.4%, and incidents on icy or frosty roads increased from 3.5% to 4.6% of the total.

Weather

Clear376 (61.8%)
↓-9.0%prior 413
Cloudy149 (24.5%)
↑30.7%prior 114
Snow29 (4.8%)
↑70.6%prior 17
Rain29 (4.8%)
↓-27.5%prior 40
Freezing rain/drizzle11 (1.8%)
Fog, smoke, smog10 (1.6%)
↑100.0%prior 5
Blowing Snow2 (0.3%)
↓-75.0%prior 8
Severe Winds1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Lighting

Daylight403 (66.2%)
↓-2.2%prior 412
Dark - roadway not lighted125 (20.5%)
↑15.7%prior 108
Dark - roadway lighted54 (8.9%)
↑22.7%prior 44
Dawn13 (2.1%)
↓-31.6%prior 19
Dusk13 (2.1%)
↓-35.0%prior 20
Dark - unknown roadway lighting1 (0.2%)

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

Road Surface

Dry448 (73.3%)
↓-1.8%prior 456
Wet72 (11.8%)
↑4.3%prior 69
Ice/frost32 (5.2%)
↑28.0%prior 25
Snow28 (4.6%)
↑3.7%prior 27
Gravel25 (4.1%)
↑38.9%prior 18
Slush5 (0.8%)
→0.0%prior 5
Sand1 (0.2%)

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

Vehicles & Demographics

The primary vehicle makes involved in crashes remained consistent, with Chevrolet, Ford, and Dodge being the top three in both 2016 and 2015. While the number of Chevrolets and Fords involved in crashes decreased year-over-year, the count for Dodge vehicles increased from 79 to 103. The age distribution of persons involved in crashes showed little change, with all major age brackets from 16 to 65+ representing a similar proportion of the total in both years.

Top Vehicle Makes (1,114 vehicles)

1
FORD198 (17.8%)
↓-7.5%prior 214
2
CHEV140 (12.6%)
↓-23.1%prior 182
3
CHEVROLET95 (8.5%)
↓-6.9%prior 102
4
DODG53 (4.8%)
↓-1.9%prior 54
5
DODGE50 (4.5%)
↑100.0%prior 25
6
JEEP44 (3.9%)
↓-12.0%prior 50
7
TOYOTA34 (3.1%)
↑70.0%prior 20
8
GMC30 (2.7%)
→0.0%prior 30
9
TOYT30 (2.7%)
↓-9.1%prior 33
10
HONDA27 (2.4%)
↑42.1%prior 19

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

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

Sex Distribution (874 persons with recorded sex)

Male494 (56.5%)
↓-13.9%prior 574
Female380 (43.5%)
↓-19.1%prior 470

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: 696
  • Total persons involved: 1,263
  • Total vehicles involved: 1,114

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