Monthly Traffic Safety Analysis

4,064 CRASHES IN
IOWA, IA
JULY 2018

All metrics benchmarked againstJuly 2017

In July 2018, there were 4,064 total crashes across Iowa, a 4.4% decrease from the 4,250 crashes recorded in July 2017. Alongside this overall decline, total injuries fell by 8.6% from 1,661 to 1,518. One of the most notable year-over-year shifts was a 13.3% increase in the count of crashes attributed to animals, which rose from 413 to 468 incidents.

4,064

▼ -4.4%was 4,250

Total Crash Events

32

▼ -3.0%was 33

Persons Killed

1,518

▼ -8.6%was 1,661

Persons Injured

32

Fatal Crash Events

Note: "Persons Killed" (32) 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 · 2018-07-01 to 2018-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year, traffic incidents showed a downward trend in July 2018 compared to July 2017. Total crashes decreased by 4.4% from 4,250 to 4,064, and total injuries saw a more significant drop of 8.6%, from 1,661 to 1,518. Fatalities remained relatively stable, with 32 deaths recorded in the current period compared to 33 in the prior year.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 0→%

3

Cyclists Killed

Prior: 1↑200.0%

25

Motorists Killed

Prior: 32↓-21.9%

0

Other Killed

Prior: 0→0.0%

23

Pedestrians Injured

Prior: 28↓-17.9%

50

Cyclists Injured

Prior: 45↑11.1%

1,440

Motorists Injured

Prior: 1,585↓-9.1%

5

Other Injured

Prior: 3↑66.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The time of day when crashes were most frequent remained consistent, with the 4 PM hour being the peak for both July 2018 (336 crashes) and July 2017 (390 crashes). However, the peak day for crashes shifted from Monday (708 crashes) in the prior year to Tuesday (739 crashes) in the current period. While the peak hour remained the same, the number of crashes during that hour decreased by 13.8% year-over-year.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity remained largely stable, with the number of fatal crash events holding steady at 32 for both July 2018 and July 2017. The fatal crash rate saw a slight increase from 0.75 to 0.79 per 100 crashes. Crashes resulting in serious injuries decreased from 126 to 110, a proportional drop from 3.0% to 2.7% of all incidents. Correspondingly, the share of no-injury crashes increased slightly from 67.3% to 68.3% of the total.

Outcome by Severity (Crash Events)

Fatal32fatal crashes0.8%
→0.0%prior 32
Serious Injury110serious injury crashes2.7%
↓-12.7%prior 126
Minor Injury441minor injury crashes10.9%
↓-10.7%prior 494
Possible Injury704possible injury crashes17.3%
↓-4.5%prior 737
No Injury2,777no injury crashes68.3%
↓-2.9%prior 2,861

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Most severe injury per crash record

Top Contributing Factors

Following too closely was the top contributing factor in both periods, though its count was nearly unchanged, moving from 497 in July 2017 to 494 in July 2018. The most significant change was in crashes attributed to animals, where the count increased by 13.3% from 413 incidents to 468, solidifying its rank as the second leading cause. Conversely, incidents involving a driver running a stop sign decreased from 149 to 102, and those involving running a traffic signal fell from 150 to 132.

Officer-Reported Primary Contributing Cause

Followed too close494 (12.2%)↓-0.6%prior 497
Animal468 (11.5%)↑13.3%prior 413
Lost Control264 (6.5%)↑4.8%prior 252
Other (explain in narrative): Other261 (6.4%)↓-11.8%prior 296
Ran off road - left219 (5.4%)↓-12.0%prior 249
FTYROW: Making left turn204 (5%)↑9.7%prior 186
FTYROW: From stop sign203 (5%)↓-13.2%prior 234
Ran off road - straight140 (3.4%)↓-13.6%prior 162
Ran Traffic Signal132 (3.2%)↓-12.0%prior 150
Driver Distraction: Other interior distraction108 (2.7%)↓-1.8%prior 110

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both periods overwhelmingly occurred in clear weather and daylight on dry roads. In July 2018, the proportion of crashes happening in clear weather increased to 76.8% from 73.5% in the prior year. Incidents during adverse conditions saw a decline; crashes in the rain fell from 138 to 87, and collisions on wet road surfaces decreased from 231 to 141. The distribution of crashes by lighting conditions remained consistent, with approximately 73% of incidents in both years occurring during daylight hours.

Weather

Clear3,122 (84.9%)
↓-0.1%prior 3,125
Cloudy458 (12.4%)
↓-25.0%prior 611
Rain87 (2.4%)
↓-37.0%prior 138
Fog, smoke, smog7 (0.2%)
↓-36.4%prior 11
Other (explain in narrative)2 (0.1%)
Severe Winds1 (0.0%)
Blowing sand, soil, dirt1 (0.0%)
Sleet, hail1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Weather condition at time of crash

Lighting

Daylight2,949 (80.0%)
↓-6.1%prior 3,141
Dark - roadway lighted331 (9.0%)
↓-4.6%prior 347
Dark - roadway not lighted271 (7.4%)
↓-2.2%prior 277
Dusk69 (1.9%)
↓-13.8%prior 80
Dawn51 (1.4%)
↑6.3%prior 48
Dark - unknown roadway lighting13 (0.4%)
↓-31.6%prior 19

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Lighting condition field

Road Surface

Dry3,433 (93.3%)
↓-3.0%prior 3,541
Wet141 (3.8%)
↓-39.0%prior 231
Gravel95 (2.6%)
↓-18.1%prior 116
Other (explain in narrative)6 (0.2%)
→0.0%prior 6
Mud, dirt3 (0.1%)
Water (standing or moving)3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent year-over-year, with Ford and Chevrolet models being the most frequently represented in both periods. Ford vehicles were involved in 1,141 crashes in July 2018, down from 1,173, while Chevrolet models were involved in a combined 1,408 crashes, down from 1,450. An analysis of persons involved shows the 26-34 age group had the highest representation in July 2018 with 1,309 individuals, an increase from 1,159 in the prior year.

Top Vehicle Makes (7,066 vehicles)

1
FORD1,141 (16.1%)
↓-2.7%prior 1,173
2
CHEV938 (13.3%)
↑0.8%prior 931
3
CHEVROLET470 (6.7%)
↓-9.4%prior 519
4
DODG298 (4.2%)
↓-7.7%prior 323
5
TOYT288 (4.1%)
↓-18.2%prior 352
6
HOND254 (3.6%)
↓-5.9%prior 270
7
JEEP212 (3%)
↓-11.7%prior 240
8
NR212 (3%)
↑15.8%prior 183
9
GMC200 (2.8%)
↓-9.1%prior 220
10
DODGE179 (2.5%)
↓-12.3%prior 204

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · Vehicle unit records

1,160 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,267 persons with recorded sex)

Male2,975 (56.5%)
↑6.9%prior 2,782
Female2,292 (43.5%)
↑8.0%prior 2,122

Source: Iowa Crash Data · ArcGIS Open Data · 2018-07-01 to 2018-07-31 · 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: 2018-07-01 through 2018-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-07-01 through 2018-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,064
  • Total persons involved: 8,388
  • Total vehicles involved: 7,066

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: July 2018." Published September 9, 2026. Reporting period: 2018-07-01 to 2018-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-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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