Monthly Traffic Safety Analysis

4,040 CRASHES IN
IOWA, IA
JULY 2016

All metrics benchmarked againstJuly 2015

In July 2016, Iowa recorded 4,040 traffic crashes, a 6.1% decrease from the 4,303 crashes reported in July 2015. Despite the overall reduction in collisions, the number of fatalities increased from 34 to 38 year-over-year. This represents an 11.8% rise in traffic deaths, even as total injuries fell by 13.6% from 1,820 to 1,573.

4,040

▼ -6.1%was 4,303

Total Crash Events

38

▲ 11.8%was 34

Persons Killed

1,573

▼ -13.6%was 1,820

Persons Injured

30

Fatal Crash Events

Note: "Persons Killed" (38) 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 · 2016-07-01 to 2016-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Iowa saw a year-over-year decrease of 6.1% between July 2015 and July 2016, falling from 4,303 to 4,040. This downward trend was also reflected in total injuries, which dropped by 13.6%. However, fatalities moved in the opposite direction, increasing by 11.8% from 34 to 38.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2↓-50.0%

2

Cyclists Killed

Prior: 1↑100.0%

34

Motorists Killed

Prior: 31↑9.7%

1

Other Killed

Prior: 0→%

23

Pedestrians Injured

Prior: 36↓-36.1%

38

Cyclists Injured

Prior: 59↓-35.6%

1,502

Motorists Injured

Prior: 1,717↓-12.5%

10

Other Injured

Prior: 8↑25.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both July 2016 (759 crashes) and July 2015 (806 crashes). Similarly, the 4 p.m. hour was the peak hour in both periods, with 327 crashes in 2016 and 365 in 2015. While most days saw a decrease in crashes, Sunday collisions increased from 422 to 486.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of fatal crashes remained unchanged at 30 for both July 2016 and July 2015, the number of people killed in those crashes rose from 34 to 38. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) decreased slightly, from a combined 32.0% of all crashes in 2015 to 31.6% in 2016. Specifically, serious injury crashes fell from 137 to 121, and minor injury crashes dropped from 515 to 440.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 38 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.7%
→0.0%prior 30
Serious Injury121serious injury crashes3%
↓-11.7%prior 137
Minor Injury440minor injury crashes10.9%
↓-14.6%prior 515
Possible Injury716possible injury crashes17.7%
↓-0.8%prior 722
No Injury2,733no injury crashes67.6%
↓-5.7%prior 2,899

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors for crashes were similar in both periods, with 'Followed too close' ranking first in July 2016 (526 crashes) and July 2015 (538 crashes). Crashes involving animals, the second-ranked factor, saw a significant 21% decrease in count from 485 to 383 year-over-year. Conversely, crashes where 'Exceeded authorized speed' was a factor increased in count by 65%, from 40 incidents in 2015 to 66 in 2016. 'Ran off road - left' also saw an increase in count from 197 to 222.

Officer-Reported Primary Contributing Cause

Followed too close526 (13%)↓-2.2%prior 538
Animal383 (9.5%)↓-21.0%prior 485
Lost Control250 (6.2%)↓-5.7%prior 265
FTYROW: From stop sign244 (6%)↓-3.6%prior 253
Other (explain in narrative): Other222 (5.5%)↓-18.4%prior 272
Ran off road - left222 (5.5%)↑12.7%prior 197
FTYROW: Making left turn186 (4.6%)↓-13.9%prior 216
Ran off road - straight161 (4%)↑7.3%prior 150
Ran Traffic Signal143 (3.5%)↓-10.6%prior 160
Operating vehicle in an reckless, erratic, careless, negligent manner121 (3%)↑10.0%prior 110

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The vast majority of crashes in both periods occurred in clear weather and on dry roads. In July 2016, the proportion of crashes on dry roads increased to 82.0% from 79.2% the previous year. Correspondingly, crashes during rainy conditions saw a notable decrease, falling from 309 incidents in July 2015 to 164 in July 2016. Lighting conditions remained stable, with daylight crashes accounting for approximately 73.5% of all incidents in both years.

Weather

Clear2,711 (73.0%)
↓-3.8%prior 2,817
Cloudy823 (22.2%)
↑6.2%prior 775
Rain164 (4.4%)
↓-46.9%prior 309
Fog, smoke, smog11 (0.3%)
↓-45.0%prior 20
Severe Winds2 (0.1%)
Freezing rain/drizzle2 (0.1%)
Other (explain in narrative)1 (0.0%)
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Weather condition at time of crash

Lighting

Daylight2,966 (79.6%)
↓-6.3%prior 3,167
Dark - roadway lighted328 (8.8%)
↑7.5%prior 305
Dark - roadway not lighted292 (7.8%)
↓-9.9%prior 324
Dusk71 (1.9%)
↓-6.6%prior 76
Dawn57 (1.5%)
↓-8.1%prior 62
Dark - unknown roadway lighting11 (0.3%)
→0.0%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Lighting condition field

Road Surface

Dry3,313 (88.7%)
↓-2.8%prior 3,408
Wet281 (7.5%)
↓-28.5%prior 393
Gravel123 (3.3%)
↑8.8%prior 113
Mud, dirt5 (0.1%)
Other (explain in narrative)4 (0.1%)
Water (standing or moving)4 (0.1%)
Oil2 (0.1%)
Snow1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford being the top two in both July 2016 and July 2015. The total number of vehicles involved in crashes decreased from 7,538 to 7,051, in line with the overall trend. An analysis of persons involved shows a decrease in count across all age groups. Notably, the proportion of persons aged 65 and older involved in crashes decreased from 11.3% of the total in 2015 to 9.9% in 2016.

Top Vehicle Makes (7,051 vehicles)

1
FORD1,128 (16%)
↓-9.9%prior 1,252
2
CHEVROLET722 (10.2%)
↑14.8%prior 629
3
CHEV686 (9.7%)
↓-19.6%prior 853
4
DODGE255 (3.6%)
↑5.4%prior 242
5
TOYOTA246 (3.5%)
↑16.0%prior 212
6
TOYT242 (3.4%)
↓-28.0%prior 336
7
DODG223 (3.2%)
↓-20.6%prior 281
8
NR198 (2.8%)
↑25.3%prior 158
9
JEEP195 (2.8%)
↓-4.9%prior 205
10
GMC184 (2.6%)
↓-16.0%prior 219

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · Vehicle unit records

1,027 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,257 persons with recorded sex)

Male2,924 (55.6%)
↓-21.2%prior 3,710
Female2,333 (44.4%)
↓-21.4%prior 2,968

Source: Iowa Crash Data · ArcGIS Open Data · 2016-07-01 to 2016-07-31 · 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: 2016-07-01 through 2016-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2016-07-01 through 2016-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,040
  • Total persons involved: 8,373
  • Total vehicles involved: 7,051

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 2016." Published September 9, 2026. Reporting period: 2016-07-01 to 2016-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-2016-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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