Monthly Traffic Safety Analysis

4,332 CRASHES IN
IOWA, IA
AUGUST 2018

All metrics benchmarked againstAugust 2017

In August 2018, Iowa recorded 4,332 vehicle crashes, a 2.5% decrease from the 4,445 crashes documented in August 2017. This overall decline was accompanied by a reduction in both fatalities, which fell from 36 to 31, and total injuries, which decreased from 1,792 to 1,630. The most notable shift was an increase in the proportion of crashes occurring in adverse weather, with incidents during rain rising from 4.4% to 7.5% of all crashes year-over-year.

4,332

-2.5%was 4,445

Total Crash Events

31

-13.9%was 36

Persons Killed

1,630

-9.0%was 1,792

Persons Injured

30

-14.3%was 35

Fatal Crash Events

Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Iowa showed a modest improvement in August 2018 compared to the same month in the prior year. Total crashes decreased by 2.5%, from 4,445 to 4,332. This downward trend was also reflected in crash outcomes, with fatalities declining by 13.9% (from 36 to 31) and injuries falling by 9.0% (from 1,792 to 1,630).

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

1

Cyclists Killed

Prior: 2-50.0%

29

Motorists Killed

Prior: 33-12.1%

0

Other Killed

Prior: 00.0%

32

Pedestrians Injured

Prior: 306.7%

45

Cyclists Injured

Prior: 49-8.2%

1,549

Motorists Injured

Prior: 1,713-9.6%

4

Other Injured

Prior: 0%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted slightly between the two periods. In August 2018, Friday was the peak day for crashes with 850 incidents, a change from August 2017 when Thursday was the peak day with 762 crashes. The peak hour also shifted earlier, moving from the 5 p.m. hour (383 crashes) in the prior year to the 4 p.m. hour (396 crashes) in the current period.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a slight decrease year-over-year. The fatal crash rate fell from 0.79 per 100 crashes in August 2017 to 0.69 in August 2018, corresponding to a drop in fatal crashes from 35 to 30. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) also decreased, accounting for 30.6% of all crashes in the current period compared to 32.7% in the prior year.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 31 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.7%
-14.3%prior 35
Serious Injury116serious injury crashes2.7%
-4.9%prior 122
Minor Injury455minor injury crashes10.5%
-7.5%prior 492
Possible Injury752possible injury crashes17.4%
-10.4%prior 839
No Injury2,979no injury crashes68.8%
0.7%prior 2,957

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors remained consistent year-over-year, with 'Followed too close' as the leading cause in both periods. However, its count increased by 5.3%, from 551 incidents in August 2017 to 580 in August 2018. Crashes involving an 'Animal' were the second-most common factor in the current period with 326 incidents, a 6.9% decrease in count from 350 in the prior year. Notably, crashes attributed to 'Ran Traffic Signal' decreased by 17.1% from 175 to 145 incidents.

Officer-Reported Primary Contributing Cause

Followed too close580 (13.4%)5.3%prior 551
Animal326 (7.5%)-6.9%prior 350
Other (explain in narrative): Other286 (6.6%)1.1%prior 283
FTYROW: From stop sign264 (6.1%)3.1%prior 256
Ran off road - left256 (5.9%)-0.4%prior 257
Lost Control241 (5.6%)-10.1%prior 268
FTYROW: Making left turn210 (4.8%)-4.5%prior 220
Driving too fast for conditions154 (3.6%)26.2%prior 122
Ran Traffic Signal145 (3.3%)-17.1%prior 175
Operating vehicle in an reckless, erratic, careless, negligent manner141 (3.3%)38.2%prior 102

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While most crashes in both periods occurred in clear weather and on dry roads, there was a notable increase in crashes under adverse conditions in August 2018. The proportion of crashes happening in rain increased from 4.4% (195 incidents) in the prior year to 7.5% (325 incidents) in the current period. Correspondingly, crashes on wet road surfaces rose from 7.5% to 12.5% of all incidents. Lighting conditions remained relatively stable, with about 75% of crashes in both years occurring during daylight.

Weather

Clear2,799 (69.3%)
-8.9%prior 3,074
Cloudy873 (21.6%)
-0.8%prior 880
Rain325 (8.0%)
66.7%prior 195
Fog, smoke, smog32 (0.8%)
128.6%prior 14
Other (explain in narrative)4 (0.1%)
Severe Winds3 (0.1%)
Freezing rain/drizzle2 (0.0%)
Sleet, hail2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Weather condition at time of crash

Lighting

Daylight3,276 (80.6%)
-1.1%prior 3,311
Dark - roadway lighted378 (9.3%)
3.0%prior 367
Dark - roadway not lighted265 (6.5%)
-18.7%prior 326
Dawn68 (1.7%)
9.7%prior 62
Dusk66 (1.6%)
-29.0%prior 93
Dark - unknown roadway lighting12 (0.3%)
-29.4%prior 17

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Lighting condition field

Road Surface

Dry3,401 (84.0%)
-7.8%prior 3,689
Wet540 (13.3%)
62.7%prior 332
Gravel97 (2.4%)
-24.2%prior 128
Mud, dirt6 (0.1%)
Other (explain in narrative)4 (0.1%)
-42.9%prior 7
Oil1 (0.0%)
Slush1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Road surface condition field

Vehicles & Demographics

The distribution of vehicle makes involved in crashes remained largely unchanged year-over-year. Ford and Chevrolet (including 'CHEV' and 'CHEVROLET' records) were the top two makes in both August 2017 and August 2018, with their total counts remaining relatively stable. Similarly, the age distribution of persons involved in crashes showed no significant shifts, with the 26-34 age group representing the largest cohort in both periods at approximately 15% of all individuals.

Top Vehicle Makes (7,814 vehicles)

1
FORD1,237 (15.8%)
-1.0%prior 1,249
2
CHEV994 (12.7%)
-2.9%prior 1,024
3
CHEVROLET465 (6%)
-11.8%prior 527
4
TOYT405 (5.2%)
0.7%prior 402
5
DODG338 (4.3%)
-2.0%prior 345
6
HOND277 (3.5%)
-1.8%prior 282
7
JEEP249 (3.2%)
-4.6%prior 261
8
NISS228 (2.9%)
16.9%prior 195
9
TOYOTA213 (2.7%)
6.5%prior 200
10
GMC208 (2.7%)
-4.1%prior 217

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · Vehicle unit records

1,099 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,933 persons with recorded sex)

Male3,304 (55.7%)
8.2%prior 3,053
Female2,629 (44.3%)
8.4%prior 2,425

Source: Iowa Crash Data · ArcGIS Open Data · 2018-08-01 to 2018-08-31 · 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: 2018-08-01 through 2018-08-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-08-01 through 2018-08-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,332
  • Total persons involved: 9,055
  • Total vehicles involved: 7,814

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: August 2018." Published September 9, 2026. Reporting period: 2018-08-01 to 2018-08-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/august-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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