Monthly Traffic Safety Analysis

5,663 CRASHES IN
IOWA, IA
NOVEMBER 2016

All metrics benchmarked againstNovember 2015

In November 2016, Iowa recorded 5,663 total traffic crashes, a 3.3% decrease from the 5,857 crashes in November 2015. Despite the overall decline in collisions, the number of fatalities rose significantly, increasing from 23 to 35 year-over-year. The most notable contributing factor shift was a 66.5% decrease in crashes attributed to driving too fast for conditions, dropping from 397 to 133 incidents.

5,663

▼ -3.3%was 5,857

Total Crash Events

35

▲ 52.2%was 23

Persons Killed

1,600

▼ -6.7%was 1,714

Persons Injured

32

▲ 68.4%was 19

Fatal Crash Events

Note: "Persons Killed" (35) counts individual fatalities across all crash events. "Fatal" in the severity table below (32) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes and related injuries showed a downward trend year-over-year. Total crashes decreased by 3.3% from 5,857 to 5,663, and total injuries fell by 6.7% from 1,714 to 1,600. However, this trend did not extend to crash severity, as total fatalities increased by 52.2%, from 23 in November 2015 to 35 in November 2016.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 2→0.0%

0

Cyclists Killed

Prior: 0→0.0%

33

Motorists Killed

Prior: 21↑57.1%

0

Other Killed

Prior: 0→0.0%

52

Pedestrians Injured

Prior: 44↑18.2%

26

Cyclists Injured

Prior: 23↑13.0%

1,519

Motorists Injured

Prior: 1,643↓-7.5%

3

Other Injured

Prior: 4↓-25.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The day with the most crashes changed from Friday (1,129 crashes) in November 2015 to Tuesday (1,029 crashes) in November 2016. The peak hour for collisions, however, remained consistent at 5 p.m. in both years, accounting for 708 crashes in the prior period and 669 in the current period.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened year-over-year despite a drop in total incidents. The number of fatal crashes increased from 19 to 32, and the fatal crash rate rose from 0.32 to 0.57 per 100 crashes. The proportion of crashes resulting in no injury remained stable at approximately 76% for both periods, while the share of possible injury crashes decreased slightly from 15.0% to 14.6%.

Severity is per crash event (most severe injury). 32 fatal crash events resulted in 35 persons killed.

Outcome by Severity (Crash Events)

Fatal32fatal crashes0.6%
↑68.4%prior 19
Serious Injury98serious injury crashes1.7%
↓-1.0%prior 99
Minor Injury402minor injury crashes7.1%
↓-0.2%prior 403
Possible Injury827possible injury crashes14.6%
↓-5.9%prior 879
No Injury4,304no injury crashes76%
↓-3.4%prior 4,457

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, with the count of such incidents increasing by 8.3% from 1,524 to 1,650. 'Followed too close' remained the second-ranked factor, with its count rising 15.9% from 521 to 604. A significant change occurred in crashes attributed to 'Driving too fast for conditions,' which fell from the third-ranked factor with 397 incidents in the prior period to the eleventh-ranked with 133 incidents in the current period, a 66.5% decrease in count.

Officer-Reported Primary Contributing Cause

Animal1,650 (29.1%)↑8.3%prior 1,524
Followed too close604 (10.7%)↑15.9%prior 521
FTYROW: From stop sign289 (5.1%)↑26.8%prior 228
Lost Control284 (5%)↓-8.1%prior 309
Other (explain in narrative): Other256 (4.5%)↓-10.8%prior 287
Ran off road - left253 (4.5%)↓-23.8%prior 332
FTYROW: Making left turn211 (3.7%)↓-12.1%prior 240
Ran off road - straight158 (2.8%)↓-20.6%prior 199
Ran Traffic Signal141 (2.5%)↓-11.3%prior 159
Ran Stop Sign135 (2.4%)↓-3.6%prior 140

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions appear to have been more favorable in November 2016 compared to the prior year. Crashes occurring in clear weather increased from 2,468 to 3,019, and those on dry road surfaces rose from 2,738 to 3,609. Correspondingly, crashes in adverse weather saw a substantial decrease; incidents in snow conditions fell from 521 to 44, and crashes on wet roads dropped from 1,015 to 560. The distribution of crashes by lighting condition remained relatively stable year-over-year.

Weather

Clear3,019 (69.3%)
↑22.3%prior 2,468
Cloudy881 (20.2%)
↑7.8%prior 817
Rain296 (6.8%)
↓-52.6%prior 624
Snow44 (1.0%)
↓-91.6%prior 521
Freezing rain/drizzle39 (0.9%)
↓-60.6%prior 99
Fog, smoke, smog33 (0.8%)
↑37.5%prior 24
Severe Winds18 (0.4%)
↓-18.2%prior 22
Blowing Snow15 (0.3%)
↓-64.3%prior 42
Other (explain in narrative)6 (0.1%)
Sleet, hail3 (0.1%)
↓-62.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Weather condition at time of crash

Lighting

Daylight2,456 (56.2%)
↓-1.4%prior 2,491
Dark - roadway lighted888 (20.3%)
↓-16.7%prior 1,066
Dark - roadway not lighted736 (16.8%)
↓-2.5%prior 755
Dusk164 (3.8%)
↓-18.4%prior 201
Dawn112 (2.6%)
↑16.7%prior 96
Dark - unknown roadway lighting12 (0.3%)
↓-62.5%prior 32

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Lighting condition field

Road Surface

Dry3,609 (82.7%)
↑31.8%prior 2,738
Wet560 (12.8%)
↓-44.8%prior 1,015
Gravel102 (2.3%)
↑52.2%prior 67
Ice/frost46 (1.1%)
↓-81.7%prior 251
Snow17 (0.4%)
↓-96.5%prior 484
Slush15 (0.3%)
↓-78.3%prior 69
Mud, dirt7 (0.2%)
↓-22.2%prior 9
Other (explain in narrative)5 (0.1%)
→0.0%prior 5
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent year-over-year, with Ford and Chevrolet continuing to be the top two most frequently involved makes in both November 2016 and November 2015. Regarding driver demographics, there was a notable decrease in the number of persons aged 16-20 involved in crashes, which fell from 1,460 to 1,160. The 26-34 age group also saw a decline in involvement, from 1,925 persons to 1,533.

Top Vehicle Makes (9,124 vehicles)

1
FORD1,505 (16.5%)
↓-4.1%prior 1,570
2
CHEVROLET1,058 (11.6%)
↑24.6%prior 849
3
CHEV788 (8.6%)
↓-25.9%prior 1,063
4
TOYOTA412 (4.5%)
↑50.4%prior 274
5
DODGE362 (4%)
↑15.3%prior 314
6
TOYT297 (3.3%)
↓-19.1%prior 367
7
DODG280 (3.1%)
↓-30.0%prior 400
8
JEEP268 (2.9%)
↓-5.6%prior 284
9
GMC266 (2.9%)
↓-0.4%prior 267
10
HONDA230 (2.5%)
↑21.7%prior 189

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · Vehicle unit records

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

Sex Distribution (6,899 persons with recorded sex)

Male3,924 (56.9%)
↓-15.6%prior 4,648
Female2,975 (43.1%)
↓-19.3%prior 3,685

Source: Iowa Crash Data · ArcGIS Open Data · 2016-11-01 to 2016-11-30 · 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: 2016-11-01 through 2016-11-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2016-11-01 through 2016-11-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,663
  • Total persons involved: 9,526
  • Total vehicles involved: 9,124

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: November 2016." Published September 9, 2026. Reporting period: 2016-11-01 to 2016-11-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/november-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

ThatCarHitMe.com · An Injuria.ai Company