Yearly Traffic Safety Analysis

94 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In 2016, Davis County recorded 94 total crashes, a 16.1% decrease from the 112 crashes documented in 2015. While overall crashes and resulting injuries declined, the number of fatalities increased from two to three. One of the most significant year-over-year shifts was a 38.5% reduction in the count of crashes attributed to animals, which fell from 39 incidents in 2015 to 24 in 2016.

94

▼ -16.1%was 112

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

41

▼ -32.8%was 61

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (3) 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 · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic collisions in Davis County showed a general downward trend, with total crashes falling by 16.1% from 112 in 2015 to 94 in 2016. This was accompanied by a significant 32.8% decrease in total injuries, from 61 to 41. However, bucking the overall trend, total fatalities rose from two in the prior year to three in the current year.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 1↑200.0%

0

Other Killed

Prior: 1↓-100.0%

38

Motorists Injured

Prior: 54↓-29.6%

3

Other Injured

Prior: 5↓-40.0%

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 distribution of crashes showed some consistency and some shifts between the two periods. Friday remained the peak day for crashes in both 2016 (22 crashes) and 2015 (23 crashes). The peak hour for collisions shifted earlier, moving from a three-way tie at 1 p.m., 3 p.m., and 6 p.m. in 2015 (11 crashes each) to a more distinct peak at 5 p.m. in 2016 (12 crashes).

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 was unchanged at two incidents in both years, the fatality rate per crash increased from 1.79% in 2015 to 2.13% in 2016. The total number of injury-related crashes (Serious, Minor, and Possible) decreased from 30 to 27. However, as a proportion of all crashes, injury-involved incidents rose slightly from 26.8% in 2015 to 28.7% in 2016.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes2.1%
→0.0%prior 2
Serious Injury6serious injury crashes6.4%
↓-25.0%prior 8
Minor Injury6minor injury crashes6.4%
↓-25.0%prior 8
Possible Injury15possible injury crashes16%
↑7.1%prior 14
No Injury65no injury crashes69.1%
↓-18.8%prior 80

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 with animals were the leading contributing factor in both periods, although the count of these incidents decreased by 38.5%, from 39 in 2015 to 24 in 2016. Consequently, the share of crashes attributed to animals fell from 34.8% to 25.5%. In contrast, crashes caused by 'Followed too close' increased in count from 8 to 11, moving up in the rankings to become the second most frequent cause in 2016.

Officer-Reported Primary Contributing Cause

Animal24 (25.5%)↓-38.5%prior 39
Followed too close11 (11.7%)↑37.5%prior 8
Lost Control6 (6.4%)
Ran off road - left5 (5.3%)
FTYROW: From stop sign5 (5.3%)→0.0%prior 5
FTYROW: Making left turn4 (4.3%)
Ran off road - straight4 (4.3%)↓-20.0%prior 5
Ran Stop Sign4 (4.3%)
Swerving/Evasive Action4 (4.3%)
Improper Backing3 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both years predominantly occurred in clear weather and on dry roads. However, the proportion of crashes on roads with ice or frost more than doubled, increasing from 3.6% of total crashes in 2015 (4 incidents) to 8.5% in 2016 (8 incidents). Conversely, the share of crashes occurring in darkness on unlighted roadways decreased from 17.0% in the prior year to 11.7% in the current year.

Weather

Clear58 (73.4%)
↓-19.4%prior 72
Cloudy15 (19.0%)
↓-11.8%prior 17
Freezing rain/drizzle2 (2.5%)
Snow2 (2.5%)
Rain1 (1.3%)
Sleet, hail1 (1.3%)

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

Lighting

Daylight59 (74.7%)
↓-4.8%prior 62
Dark - roadway not lighted11 (13.9%)
↓-42.1%prior 19
Dusk5 (6.3%)
Dark - roadway lighted2 (2.5%)
Dawn2 (2.5%)

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

Road Surface

Dry56 (70.9%)
↓-20.0%prior 70
Ice/frost8 (10.1%)
Gravel8 (10.1%)
→0.0%prior 8
Wet4 (5.1%)
↓-42.9%prior 7
Slush2 (2.5%)
Snow1 (1.3%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet and Ford leading in both years; Chevrolet-branded vehicles decreased from 40 to 33, while Ford vehicles held steady at 31. The total number of people involved in crashes fell from 229 to 163. The largest decreases in involvement by age group were seen among individuals aged 16-20 (from 45 to 28) and 45-54 (from 37 to 19).

Top Vehicle Makes (140 vehicles)

1
FORD31 (22.1%)
→0.0%prior 31
2
CHEV17 (12.1%)
↓-22.7%prior 22
3
CHEVROLET16 (11.4%)
↓-11.1%prior 18
4
DODGE9 (6.4%)
↑28.6%prior 7
5
DODG8 (5.7%)
↓-20.0%prior 10
6
BUIC5 (3.6%)
→0.0%prior 5
7
BUICK5 (3.6%)
8
PONTIAC4 (2.9%)
9
TOYT4 (2.9%)
↓-33.3%prior 6
10
TOYOTA3 (2.1%)

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

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

Sex Distribution (101 persons with recorded sex)

Male56 (55.4%)
↓-27.3%prior 77
Female45 (44.6%)
↓-36.6%prior 71

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: 94
  • Total persons involved: 163
  • Total vehicles involved: 140

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

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