Yearly Traffic Safety Analysis

224 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In 2016, Crawford County recorded 224 total crashes, a 3.9% decrease from the 233 crashes reported in 2015. During this period, total injuries also saw a slight decline from 99 to 95, and fatalities fell from 4 to 3. The most significant year-over-year change was a 50% reduction in fatal crashes, which fell from 4 in 2015 to 2 in 2016.

224

▼ -3.9%was 233

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

95

▼ -4.0%was 99

Persons Injured

2

▼ -50.0%was 4

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

Overall traffic safety trends in Crawford County showed a modest improvement from 2015 to 2016. Total crashes decreased by 3.9%, falling from 233 to 224. This downward trend was also reflected in casualties, with total injuries declining by 4.0% and fatalities decreasing from 4 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 4↓-25.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

94

Motorists Injured

Prior: 97↓-3.1%

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 Crawford County showed some shifts between 2015 and 2016. Friday remained the peak day for crashes in both years, with the count increasing from 47 to 55. The peak hour for collisions shifted an hour earlier, from 4 p.m. in 2015 (19 crashes) to 3 p.m. in 2016 (25 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

Crash severity in Crawford County decreased from 2015 to 2016. The number of fatal crashes was halved, falling from 4 to 2, and the fatal crash rate dropped from 1.7% to 0.9% of all collisions. The number of crashes resulting in any level of injury also declined, with serious injury crashes decreasing from 11 to 9 and possible injury crashes falling from 47 to 39. Correspondingly, the share of crashes with no reported injuries increased from 65.7% to 70.5%.

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

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
↓-50.0%prior 4
Serious Injury9serious injury crashes4%
↓-18.2%prior 11
Minor Injury16minor injury crashes7.1%
↓-11.1%prior 18
Possible Injury39possible injury crashes17.4%
↓-17.0%prior 47
No Injury158no injury crashes70.5%
↑3.3%prior 153

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 animals remained the leading contributing factor in both periods, with the count increasing from 31 in 2015 to 35 in 2016. 'Lost Control' also remained a top cause, though its count decreased from 23 to 19. Notably, crashes attributed to 'Followed too close' dropped by 38%, from 21 incidents in 2015 to 13 in 2016. Conversely, crashes involving 'Failure to Yield Right of Way from a stop sign' increased in count from 11 to 17.

Officer-Reported Primary Contributing Cause

Animal35 (15.6%)↑12.9%prior 31
Lost Control19 (8.5%)↓-17.4%prior 23
FTYROW: From stop sign17 (7.6%)↑54.5%prior 11
Followed too close13 (5.8%)↓-38.1%prior 21
Ran off road - left13 (5.8%)↑18.2%prior 11
Ran off road - straight11 (4.9%)↑22.2%prior 9
FTYROW: Making left turn9 (4%)→0.0%prior 9
Improper Backing9 (4%)↑80.0%prior 5
Other (explain in narrative): Other7 (3.1%)↓-36.4%prior 11
Ran Stop Sign5 (2.2%)↓-61.5%prior 13

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 consistent year-over-year. The proportion of crashes occurring in daylight (65.2% in 2016 vs. 65.7% in 2015) and clear weather (60.3% vs. 58.4%) saw minimal change. There was a notable shift in road surface conditions, with the share of crashes on dry roads increasing from 57.5% to 63.8%, while crashes on wet, snow, or ice-covered roads all saw decreases in their respective counts.

Weather

Clear135 (69.6%)
↓-0.7%prior 136
Cloudy36 (18.6%)
↑24.1%prior 29
Rain11 (5.7%)
↓-35.3%prior 17
Snow6 (3.1%)
↓-60.0%prior 15
Freezing rain/drizzle4 (2.1%)
↓-20.0%prior 5
Blowing Snow2 (1.0%)

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

Lighting

Daylight146 (75.3%)
↓-4.6%prior 153
Dark - roadway not lighted24 (12.4%)
↑9.1%prior 22
Dark - roadway lighted13 (6.7%)
↓-38.1%prior 21
Dusk6 (3.1%)
↓-14.3%prior 7
Dark - unknown roadway lighting3 (1.5%)
Dawn2 (1.0%)

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

Road Surface

Dry143 (73.7%)
↑6.7%prior 134
Wet21 (10.8%)
↓-22.2%prior 27
Snow13 (6.7%)
↓-23.5%prior 17
Ice/frost10 (5.2%)
↓-28.6%prior 14
Gravel6 (3.1%)
↓-25.0%prior 8
Slush1 (0.5%)
↓-83.3%prior 6

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

Vehicles & Demographics

Analysis of involved vehicles and persons shows consistent patterns with some year-over-year shifts. Combining spelling variations, Chevrolet, Ford, and Dodge were the top three vehicle makes involved in crashes in both 2015 and 2016, with Chevrolet and Ford both seeing a decrease in their involvement counts from 88 to 77 and 66 to 59, respectively. Examining the age of persons involved in crashes, the 16-20 age group saw a notable reduction from 85 individuals in 2015 to 66 in 2016, though it remained one of the most frequently involved age groups.

Top Vehicle Makes (374 vehicles)

1
FORD59 (15.8%)
↓-10.6%prior 66
2
CHEV41 (11%)
↓-30.5%prior 59
3
CHEVROLET36 (9.6%)
↑24.1%prior 29
4
DODG22 (5.9%)
↓-15.4%prior 26
5
DODGE22 (5.9%)
↑37.5%prior 16
6
GMC16 (4.3%)
↓-30.4%prior 23
7
JEEP15 (4%)
↑25.0%prior 12
8
NR12 (3.2%)
↑100.0%prior 6
9
CHRYSLER11 (2.9%)
10
TOYOTA11 (2.9%)
↑37.5%prior 8

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

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

Sex Distribution (280 persons with recorded sex)

Male169 (60.4%)
↓-20.7%prior 213
Female111 (39.6%)
↓-14.6%prior 130

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: 224
  • Total persons involved: 437
  • Total vehicles involved: 374

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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