Monthly Traffic Safety Analysis

5,014 CRASHES IN
IOWA, IA
JANUARY 2016

All metrics benchmarked againstJanuary 2015

In January 2016, there were 5,014 total crashes, a 4.8% decrease from the 5,268 crashes recorded in January 2015. Despite the overall reduction in collisions, the number of fatalities rose significantly, increasing 55.6% from 18 in the prior year to 28 in the current period.

5,014

▼ -4.8%was 5,268

Total Crash Events

28

▲ 55.6%was 18

Persons Killed

1,510

▲ 3.0%was 1,466

Persons Injured

24

▲ 41.2%was 17

Fatal Crash Events

Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) 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 2016-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in January 2016 decreased by 4.8% compared to the same month in the previous year, falling from 5,268 to 5,014. However, this downward trend in total crashes was accompanied by a 3.0% increase in total injuries (from 1,466 to 1,510) and a 55.6% increase in fatalities (from 18 to 28).

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

27

Motorists Killed

Prior: 18↑50.0%

0

Other Killed

Prior: 0→0.0%

45

Pedestrians Injured

Prior: 43↑4.7%

4

Cyclists Injured

Prior: 3↑33.3%

1,457

Motorists Injured

Prior: 1,413↑3.1%

4

Other Injured

Prior: 7↓-42.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · 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 a shift year-over-year. The peak day for crashes moved from Tuesday (915 crashes) in the prior period to Friday (932 crashes) in the current period. Similarly, the peak hour for collisions shifted from the 3 p.m. hour (442 crashes) to the 5 p.m. hour (452 crashes), aligning with the evening commute.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of crashes worsened year-over-year. The number of fatal crashes increased from 17 to 24, and the fatal crash rate rose from 0.32% to 0.48% of all collisions. The proportion of crashes resulting in any injury (serious, minor, or possible) also increased slightly, from 23.6% of all crashes in the prior year to 24.8% in the current year.

Severity is per crash event (most severe injury). 24 fatal crash events resulted in 28 persons killed.

Outcome by Severity (Crash Events)

Fatal24fatal crashes0.5%
↑41.2%prior 17
Serious Injury80serious injury crashes1.6%
↑5.3%prior 76
Minor Injury353minor injury crashes7%
↑5.7%prior 334
Possible Injury812possible injury crashes16.2%
↓-2.9%prior 836
No Injury3,745no injury crashes74.7%
↓-6.5%prior 4,005

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between the two periods. 'Driving too fast for conditions' remained the top factor, but its count decreased by 15.4% from 683 to 578 incidents. Crashes involving an 'Animal' increased by 16.8% from 452 to 528, moving this factor from the third to the second-ranked cause. 'Followed too close' also saw a 22.2% increase in count, from 361 to 441 incidents, moving it into the top three.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions578 (11.5%)↓-15.4%prior 683
Animal528 (10.5%)↑16.8%prior 452
Followed too close441 (8.8%)↑22.2%prior 361
Ran off road - left387 (7.7%)↓-15.7%prior 459
Lost Control374 (7.5%)↓-15.2%prior 441
Other (explain in narrative): Other273 (5.4%)↑27.6%prior 214
Ran off road - straight259 (5.2%)↓-13.7%prior 300
FTYROW: From stop sign222 (4.4%)↓-11.6%prior 251
Ran Traffic Signal193 (3.8%)↑22.9%prior 157
FTYROW: Making left turn193 (3.8%)↓-21.5%prior 246

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

Road & Environmental Conditions

There was a notable change in road surface conditions between the two periods. Crashes on snowy roads decreased from 1,395 to 697, while collisions on dry roads increased from 1,825 to 2,085. Correspondingly, crashes during snowy weather fell from 746 to 566. This suggests that January 2016 had different weather patterns than January 2015, which altered the conditions under which crashes occurred.

Weather

Clear2,157 (47.5%)
↓-11.0%prior 2,423
Cloudy1,281 (28.2%)
↑1.2%prior 1,266
Snow566 (12.5%)
↓-24.1%prior 746
Freezing rain/drizzle218 (4.8%)
↑120.2%prior 99
Blowing Snow110 (2.4%)
↓-40.9%prior 186
Rain107 (2.4%)
↑18.9%prior 90
Fog, smoke, smog71 (1.6%)
↑222.7%prior 22
Other (explain in narrative)14 (0.3%)
Sleet, hail11 (0.2%)
Severe Winds6 (0.1%)
↓-40.0%prior 10

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

Lighting

Daylight2,497 (54.7%)
↓-14.0%prior 2,904
Dark - roadway lighted984 (21.6%)
↑4.2%prior 944
Dark - roadway not lighted756 (16.6%)
↑3.0%prior 734
Dusk173 (3.8%)
↑16.1%prior 149
Dawn129 (2.8%)
↑3.2%prior 125
Dark - unknown roadway lighting23 (0.5%)
↓-25.8%prior 31

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

Road Surface

Dry2,085 (45.8%)
↑14.2%prior 1,825
Ice/frost874 (19.2%)
↑9.0%prior 802
Wet726 (15.9%)
↑20.4%prior 603
Snow697 (15.3%)
↓-50.0%prior 1,395
Slush130 (2.9%)
↓-24.0%prior 171
Gravel25 (0.5%)
↓-45.7%prior 46
Other (explain in narrative)8 (0.2%)
↓-50.0%prior 16
Sand7 (0.2%)
↑40.0%prior 5
Mud, dirt3 (0.1%)
↓-70.0%prior 10
Water (standing or moving)1 (0.0%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet, Ford, and Dodge leading in both periods, although the total counts for each make decreased. An analysis of persons involved in crashes shows a general decrease across most adult age groups, with the 21-25 age bracket seeing a drop from 1,387 to 1,193 individuals. Conversely, the number of persons aged 0-15 involved in crashes increased from 141 to 166.

Top Vehicle Makes (8,482 vehicles)

1
FORD1,371 (16.2%)
↓-11.1%prior 1,543
2
CHEV1,091 (12.9%)
↓-11.2%prior 1,229
3
CHEVROLET631 (7.4%)
↑6.8%prior 591
4
DODG402 (4.7%)
↓-12.2%prior 458
5
TOYT354 (4.2%)
↓-17.7%prior 430
6
JEEP273 (3.2%)
↑8.3%prior 252
7
DODGE262 (3.1%)
↑22.4%prior 214
8
GMC261 (3.1%)
↓-2.6%prior 268
9
HOND237 (2.8%)
↓-24.8%prior 315
10
TOYOTA234 (2.8%)
↑26.5%prior 185

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

1,183 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,790 persons with recorded sex)

Male3,810 (56.1%)
↓-15.0%prior 4,481
Female2,980 (43.9%)
↓-12.2%prior 3,393

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-01-31 · 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 2016-01-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2016-01-01 through 2016-01-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,014
  • Total persons involved: 9,950
  • Total vehicles involved: 8,482

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: January 2016." Published September 9, 2026. Reporting period: 2016-01-01 to 2016-01-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/january-2016-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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