Monthly Traffic Safety Analysis

4,308 CRASHES IN
IOWA, IA
AUGUST 2019

All metrics benchmarked againstAugust 2018

In August 2019, Iowa recorded 4,308 traffic crashes, a marginal 0.6% decrease from the 4,332 crashes in August 2018. While total crashes and fatalities (31 in both periods) remained stable, the most notable year-over-year shift was a 7.0% increase in total injuries, from 1,630 to 1,743. This was driven in part by a 15.5% rise in the number of serious injury crashes.

4,308

▼ -0.6%was 4,332

Total Crash Events

31

Persons Killed

1,743

▲ 6.9%was 1,630

Persons Injured

30

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 · 2019-08-01 to 2019-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Iowa remained nearly stable, decreasing by just 24 incidents (0.6%) from August 2018 to August 2019. However, the severity of outcomes worsened, as total injuries increased by 7.0% from 1,630 to 1,743. The number of fatalities was unchanged at 31 in both periods.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 1↑300.0%

1

Cyclists Killed

Prior: 1→0.0%

26

Motorists Killed

Prior: 29↓-10.3%

0

Other Killed

Prior: 0→0.0%

28

Pedestrians Injured

Prior: 32↓-12.5%

60

Cyclists Injured

Prior: 45↑33.3%

1,652

Motorists Injured

Prior: 1,549↑6.6%

3

Other Injured

Prior: 4↓-25.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes were largely consistent year-over-year, with Friday remaining the peak day and the 4 PM hour being the most frequent time for incidents in both August 2019 and 2018. The number of crashes on the peak day was nearly identical, with 835 in 2019 compared to 850 in 2018. A notable shift occurred on Wednesdays, which saw a significant drop in crashes from 742 in 2018 to 541 in 2019.

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes was identical at 30 in both August 2019 and August 2018, the severity of non-fatal crashes increased. The count of serious injury crashes rose by 15.5%, from 116 to 134, increasing their share of all crashes from 2.7% to 3.1%. Minor injury crashes also saw a 6.6% increase in count (from 455 to 485), while property-damage-only crashes decreased by 2.6%.

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%
→0.0%prior 30
Serious Injury134serious injury crashes3.1%
↑15.5%prior 116
Minor Injury485minor injury crashes11.3%
↑6.6%prior 455
Possible Injury756possible injury crashes17.5%
↑0.5%prior 752
No Injury2,903no injury crashes67.4%
↓-2.6%prior 2,979

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes were consistent year-over-year, with "Followed too close" remaining the top-ranked cause, accounting for 575 crashes in August 2019 compared to 580 in the prior year. There were, however, significant changes in the counts of other factors. Crashes attributed to "Driving too fast for conditions" saw a 37.7% decrease in count, from 154 to 96. Conversely, crashes involving a "Failure to yield from a driveway" increased in count by 44.3%, from 61 to 88.

Officer-Reported Primary Contributing Cause

Followed too close575 (13.3%)↓-0.9%prior 580
Animal353 (8.2%)↑8.3%prior 326
Other (explain in narrative): Other302 (7%)↑5.6%prior 286
FTYROW: From stop sign258 (6%)↓-2.3%prior 264
Ran off road - left222 (5.2%)↓-13.3%prior 256
Lost Control213 (4.9%)↓-11.6%prior 241
FTYROW: Making left turn207 (4.8%)↓-1.4%prior 210
Ran Stop Sign150 (3.5%)↑21.0%prior 124
Ran Traffic Signal138 (3.2%)↓-4.8%prior 145
Ran off road - straight133 (3.1%)↓-4.3%prior 139

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A larger proportion of crashes in August 2019 occurred under ideal environmental conditions compared to the prior year. Crashes on dry road surfaces accounted for 84.6% of the total, up from 78.5% in August 2018, while crashes on wet roads fell from 12.5% to 6.7% of all incidents. A similar trend was seen with lighting, where crashes in daylight represented 73.4% of the total, though incidents on unlit dark roadways increased their share from 6.1% to 7.9%.

Weather

Clear3,141 (78.1%)
↑12.2%prior 2,799
Cloudy683 (17.0%)
↓-21.8%prior 873
Rain172 (4.3%)
↓-47.1%prior 325
Fog, smoke, smog14 (0.3%)
↓-56.3%prior 32
Severe Winds4 (0.1%)
Freezing rain/drizzle3 (0.1%)
Other (explain in narrative)2 (0.0%)
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Weather condition at time of crash

Lighting

Daylight3,160 (78.2%)
↓-3.5%prior 3,276
Dark - roadway lighted367 (9.1%)
↓-2.9%prior 378
Dark - roadway not lighted339 (8.4%)
↑27.9%prior 265
Dusk92 (2.3%)
↑39.4%prior 66
Dawn68 (1.7%)
→0.0%prior 68
Dark - unknown roadway lighting13 (0.3%)
↑8.3%prior 12

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Lighting condition field

Road Surface

Dry3,643 (90.5%)
↑7.1%prior 3,401
Wet290 (7.2%)
↓-46.3%prior 540
Gravel86 (2.1%)
↓-11.3%prior 97
Other (explain in narrative)4 (0.1%)
Mud, dirt3 (0.1%)
↓-50.0%prior 6
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Road surface condition field

Vehicles & Demographics

The top makes of vehicles involved in crashes, primarily Ford and Chevrolet, remained stable between the two periods. Ford vehicles were involved in 1,231 crashes in August 2019, nearly unchanged from 1,237 in the prior year. In contrast, there were significant shifts in the age demographics of people involved in crashes, with the 26-34 age group seeing a 19.5% increase in involvement (from 1,403 to 1,676 people) and the 65+ age group seeing a 22.1% increase (from 995 to 1,215 people).

Top Vehicle Makes (7,706 vehicles)

1
FORD1,231 (16%)
↓-0.5%prior 1,237
2
CHEV1,005 (13%)
↑1.1%prior 994
3
CHEVROLET547 (7.1%)
↑17.6%prior 465
4
TOYT328 (4.3%)
↓-19.0%prior 405
5
HOND283 (3.7%)
↑2.2%prior 277
6
DODG268 (3.5%)
↓-20.7%prior 338
7
JEEP236 (3.1%)
↓-5.2%prior 249
8
NR223 (2.9%)
↑26.0%prior 177
9
GMC223 (2.9%)
↑7.2%prior 208
10
TOYOTA210 (2.7%)
↓-1.4%prior 213

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · Vehicle unit records

1,273 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,946 persons with recorded sex)

Male3,893 (56.0%)
↑17.8%prior 3,304
Female3,053 (44.0%)
↑16.1%prior 2,629

Source: Iowa Crash Data · ArcGIS Open Data · 2019-08-01 to 2019-08-31 · 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: 2019-08-01 through 2019-08-31
  • Report generated: September 10, 2026

Data Coverage

  • Reporting period: 2019-08-01 through 2019-08-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,308
  • Total persons involved: 10,345
  • Total vehicles involved: 7,706

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 2019." Published September 10, 2026. Reporting period: 2019-08-01 to 2019-08-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/august-2019-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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