Monthly Traffic Safety Analysis

5,369 CRASHES IN
IOWA, IA
OCTOBER 2018

All metrics benchmarked againstOctober 2017

In October 2018, there were 5,369 traffic crashes, a negligible 0.04% decrease from the 5,371 crashes recorded in October 2017. While the total number of incidents remained stable, the most notable year-over-year shift was a significant 29.4% reduction in traffic fatalities, which fell from 34 to 24.

5,369

▼ -0.0%was 5,371

Total Crash Events

24

▼ -29.4%was 34

Persons Killed

1,674

▲ 0.9%was 1,659

Persons Injured

23

▼ -20.7%was 29

Fatal Crash Events

Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (23) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash totals were remarkably stable year-over-year, decreasing by only 2 incidents from 5,371 in October 2017 to 5,369 in October 2018. However, this stability in total numbers masks a positive trend in outcomes, with both total fatalities (down 29.4%) and total injuries (up 0.9%) showing changes. The number of fatal crashes decreased by 20.7%, from 29 to 23.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 4↓-75.0%

0

Cyclists Killed

Prior: 1↓-100.0%

23

Motorists Killed

Prior: 29↓-20.7%

0

Other Killed

Prior: 0→0.0%

54

Pedestrians Injured

Prior: 41↑31.7%

39

Cyclists Injured

Prior: 33↑18.2%

1,580

Motorists Injured

Prior: 1,581↓-0.1%

1

Other Injured

Prior: 4↓-75.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In October 2018, the peak day for crashes was Wednesday with 933 incidents, a change from Tuesday (872 incidents) in the prior year. The peak hour also shifted from the afternoon to the morning, moving from 3 p.m. in 2017 (428 crashes) to 7 a.m. in 2018 (441 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a notable improvement year-over-year. The fatal crash rate decreased from 0.54% of all crashes in October 2017 to 0.43% in October 2018. The number of fatal crashes fell from 29 to 23, and serious injury crashes also declined from 103 to 86. Conversely, crashes resulting in minor injuries increased from 422 to 460.

Severity is per crash event (most severe injury). 23 fatal crash events resulted in 24 persons killed.

Outcome by Severity (Crash Events)

Fatal23fatal crashes0.4%
↓-20.7%prior 29
Serious Injury86serious injury crashes1.6%
↓-16.5%prior 103
Minor Injury460minor injury crashes8.6%
↑9.0%prior 422
Possible Injury825possible injury crashes15.4%
↓-3.5%prior 855
No Injury3,975no injury crashes74%
↑0.3%prior 3,962

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, increasing in count by 8.0% from 1,072 to 1,158 incidents. 'Followed too close' was the second most common factor in both years, with a slight increase from 586 to 606 crashes. A significant decrease was observed in crashes attributed to 'Lost Control,' which fell by 26.2% from 290 incidents in 2017 to 214 in 2018, dropping its rank from the 5th to the 7th most common factor.

Officer-Reported Primary Contributing Cause

Animal1,158 (21.6%)↑8.0%prior 1,072
Followed too close606 (11.3%)↑3.4%prior 586
FTYROW: From stop sign299 (5.6%)↑2.4%prior 292
Other (explain in narrative): Other295 (5.5%)↓-11.9%prior 335
Ran off road - left244 (4.5%)↓-0.8%prior 246
FTYROW: Making left turn237 (4.4%)↑1.7%prior 233
Lost Control214 (4%)↓-26.2%prior 290
Ran off road - straight161 (3%)↓-2.4%prior 165
Ran Traffic Signal159 (3%)↓-5.4%prior 168
Other (explain in narrative): No improper action142 (2.6%)↑132.8%prior 61

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely consistent year-over-year. Crashes in clear weather accounted for 2,738 incidents in October 2018, up from 2,599 in the prior year, while crashes during rain decreased slightly from 583 to 525. Similarly, road surface conditions showed little change, with incidents on dry roads numbering 3,382 in 2018 compared to 3,451 in 2017. There were no significant shifts in the proportion of crashes occurring in adverse conditions.

Weather

Clear2,738 (61.3%)
↑5.3%prior 2,599
Cloudy1,111 (24.9%)
↓-13.3%prior 1,281
Rain525 (11.8%)
↓-9.9%prior 583
Fog, smoke, smog31 (0.7%)
↑93.8%prior 16
Freezing rain/drizzle23 (0.5%)
↓-32.4%prior 34
Snow20 (0.4%)
↑100.0%prior 10
Other (explain in narrative)7 (0.2%)
Severe Winds6 (0.1%)
↓-60.0%prior 15
Sleet, hail2 (0.0%)
Blowing Snow1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Weather condition at time of crash

Lighting

Daylight3,000 (67.2%)
↓-0.1%prior 3,004
Dark - roadway lighted646 (14.5%)
↓-10.5%prior 722
Dark - roadway not lighted544 (12.2%)
↓-5.6%prior 576
Dawn144 (3.2%)
↑5.9%prior 136
Dusk114 (2.6%)
↑10.7%prior 103
Dark - unknown roadway lighting19 (0.4%)
↓-24.0%prior 25

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Lighting condition field

Road Surface

Dry3,382 (75.8%)
↓-2.0%prior 3,451
Wet961 (21.5%)
↓-2.6%prior 987
Gravel94 (2.1%)
↓-11.3%prior 106
Slush10 (0.2%)
Snow6 (0.1%)
Mud, dirt4 (0.1%)
Ice/frost4 (0.1%)
↓-20.0%prior 5
Sand1 (0.0%)
Other (explain in narrative)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet leading in both October 2017 and October 2018. An analysis of persons involved shows a shift in age demographics. The number of individuals in the 26-34 age group involved in crashes increased from 1,377 to 1,530, and the 35-44 age group increased from 1,291 to 1,338. Conversely, involvement decreased for younger drivers, with the 16-20 age group falling from 1,290 to 1,249 and the 21-25 group falling from 1,065 to 993.

Top Vehicle Makes (9,040 vehicles)

1
FORD1,421 (15.7%)
↓-2.7%prior 1,461
2
CHEV1,281 (14.2%)
↑13.9%prior 1,125
3
CHEVROLET511 (5.7%)
↓-15.1%prior 602
4
TOYT457 (5.1%)
↑1.6%prior 450
5
DODG404 (4.5%)
↑3.6%prior 390
6
HOND315 (3.5%)
↑4.7%prior 301
7
JEEP290 (3.2%)
↓-3.0%prior 299
8
GMC249 (2.8%)
↑6.0%prior 235
9
CHRY240 (2.7%)
↑16.5%prior 206
10
NR223 (2.5%)
↓-6.3%prior 238

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · Vehicle unit records

1,009 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,954 persons with recorded sex)

Male3,398 (57.1%)
↑4.2%prior 3,260
Female2,556 (42.9%)
↓-2.5%prior 2,622

Source: Iowa Crash Data · ArcGIS Open Data · 2018-10-01 to 2018-10-31 · 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: 2018-10-01 through 2018-10-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-10-01 through 2018-10-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,369
  • Total persons involved: 9,553
  • Total vehicles involved: 9,040

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: October 2018." Published September 9, 2026. Reporting period: 2018-10-01 to 2018-10-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/october-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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