Monthly Traffic Safety Analysis

6,022 CRASHES IN
IOWA, IA
NOVEMBER 2018

All metrics benchmarked againstNovember 2017

In November 2018, Iowa recorded 6,022 total vehicle crashes, an increase of 7.7% from the 5,594 crashes in November 2017. This rise in total incidents was accompanied by a significant year-over-year shift in crash outcomes. The most notable change was a 93.3% increase in total fatalities, which rose from 15 in the prior period to 29 in the current period.

6,022

7.7%was 5,594

Total Crash Events

29

93.3%was 15

Persons Killed

1,590

6.3%was 1,496

Persons Injured

25

66.7%was 15

Fatal Crash Events

Note: "Persons Killed" (29) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for November 2018 shows a year-over-year increase in traffic incidents compared to November 2017. Total crashes rose by 7.7% from 5,594 to 6,022. Similarly, total injuries increased by 6.3% from 1,496 to 1,590, and total fatalities nearly doubled, rising from 15 to 29.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 1300.0%

0

Cyclists Killed

Prior: 00.0%

25

Motorists Killed

Prior: 1478.6%

0

Other Killed

Prior: 00.0%

30

Pedestrians Injured

Prior: 38-21.1%

11

Cyclists Injured

Prior: 837.5%

1,545

Motorists Injured

Prior: 1,4476.8%

4

Other Injured

Prior: 333.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes showed some changes between the two periods. While the peak hour for crashes remained the 5 p.m. hour in both November 2017 (707 crashes) and November 2018 (723 crashes), the peak day of the week shifted. In 2017, Wednesday was the busiest day with 942 crashes, whereas in 2018, Friday saw the most incidents with 1,280 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in November 2018 compared to the previous year. The number of fatal crashes increased from 15 to 25, and the fatal crash rate rose from 0.27% to 0.42% of all crashes. The counts for serious injury crashes (78 to 88) and minor injury crashes (380 to 401) also saw increases, contributing to a higher number of total injuries year-over-year.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 29 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.4%
66.7%prior 15
Serious Injury88serious injury crashes1.5%
12.8%prior 78
Minor Injury401minor injury crashes6.7%
5.5%prior 380
Possible Injury834possible injury crashes13.8%
1.5%prior 822
No Injury4,674no injury crashes77.6%
8.7%prior 4,299

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Most severe injury per crash record

Top Contributing Factors

While collisions with animals remained the top contributing factor in both periods, the count decreased from 1,740 in November 2017 to 1,602 in November 2018. Conversely, crashes attributed to 'Driving too fast for conditions' saw a substantial increase in count, rising from 118 to 413 incidents. 'Ran off road - left' also increased in count from 230 to 335. The count for 'Followed too close' remained nearly stable, with 554 incidents in 2017 and 556 in 2018.

Officer-Reported Primary Contributing Cause

Animal1,602 (26.6%)-7.9%prior 1,740
Followed too close556 (9.2%)0.4%prior 554
Driving too fast for conditions413 (6.9%)250.0%prior 118
Ran off road - left335 (5.6%)45.7%prior 230
Lost Control304 (5%)13.9%prior 267
FTYROW: From stop sign286 (4.7%)12.6%prior 254
Other (explain in narrative): Other267 (4.4%)-9.2%prior 294
FTYROW: Making left turn228 (3.8%)24.6%prior 183
Ran off road - straight184 (3.1%)47.2%prior 125
Ran Stop Sign150 (2.5%)5.6%prior 142

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a significant shift in crash conditions year-over-year. Although total crashes increased, incidents on dry roads decreased from 3,648 to 3,118. In contrast, crashes occurring on adverse road surfaces rose sharply: incidents on icy or frosty roads increased from 22 to 421, and crashes on snowy surfaces increased from zero reported in November 2017 to 378 in November 2018. This corresponds with a large increase in crashes reported during snow and freezing rain conditions.

Weather

Clear2,484 (52.7%)
-11.8%prior 2,815
Cloudy1,261 (26.7%)
16.4%prior 1,083
Snow378 (8.0%)
Rain377 (8.0%)
92.3%prior 196
Freezing rain/drizzle118 (2.5%)
218.9%prior 37
Fog, smoke, smog45 (1.0%)
-55.4%prior 101
Blowing Snow40 (0.8%)
Other (explain in narrative)5 (0.1%)
Sleet, hail5 (0.1%)
Severe Winds2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Weather condition at time of crash

Lighting

Daylight2,581 (54.6%)
15.6%prior 2,233
Dark - roadway lighted968 (20.5%)
4.8%prior 924
Dark - roadway not lighted851 (18.0%)
13.5%prior 750
Dusk193 (4.1%)
2.1%prior 189
Dawn106 (2.2%)
-16.5%prior 127
Dark - unknown roadway lighting28 (0.6%)
-6.7%prior 30

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Lighting condition field

Road Surface

Dry3,118 (66.0%)
-14.5%prior 3,648
Wet699 (14.8%)
48.7%prior 470
Ice/frost421 (8.9%)
1813.6%prior 22
Snow378 (8.0%)
Gravel65 (1.4%)
-38.7%prior 106
Slush32 (0.7%)
Mud, dirt5 (0.1%)
-28.6%prior 7
Other (explain in narrative)3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Road surface condition field

Vehicles & Demographics

The vehicle makes most frequently involved in crashes remained consistent, with Ford and Chevrolet models topping the list in both November 2017 and November 2018. The number of crashes involving these top makes increased, in line with the overall trend. The age distribution of persons involved in crashes also showed a consistent pattern, with proportional representation across age groups remaining similar year-over-year despite an increase in the total number of people involved.

Top Vehicle Makes (9,744 vehicles)

1
FORD1,615 (16.6%)
5.8%prior 1,526
2
CHEV1,406 (14.4%)
11.2%prior 1,264
3
CHEVROLET557 (5.7%)
-3.0%prior 574
4
TOYT495 (5.1%)
14.6%prior 432
5
DODG442 (4.5%)
11.1%prior 398
6
JEEP368 (3.8%)
26.5%prior 291
7
GMC332 (3.4%)
35.0%prior 246
8
HOND330 (3.4%)
14.6%prior 288
9
NISS280 (2.9%)
28.4%prior 218
10
NR242 (2.5%)
26.0%prior 192

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · Vehicle unit records

1,013 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,312 persons with recorded sex)

Male3,536 (56.0%)
5.5%prior 3,353
Female2,776 (44.0%)
3.6%prior 2,680

Source: Iowa Crash Data · ArcGIS Open Data · 2018-11-01 to 2018-11-30 · 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: 2018-11-01 through 2018-11-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-11-01 through 2018-11-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 6,022
  • Total persons involved: 10,225
  • Total vehicles involved: 9,744

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 2018." Published September 9, 2026. Reporting period: 2018-11-01 to 2018-11-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/november-2018-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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