Monthly Traffic Safety Analysis

4,445 CRASHES IN
IOWA, IA
AUGUST 2017

All metrics benchmarked againstAugust 2016

In August 2017, Iowa recorded 4,445 vehicle crashes, a 7.1% increase from the 4,149 crashes documented in August 2016. This rise was accompanied by an 11.4% increase in total injuries, from 1,609 to 1,792, while total fatalities saw a slight decrease from 38 to 36. The most notable year-over-year shift was a 29.2% increase in the count of crashes attributed to animals, which rose from 271 to 350.

4,445

7.1%was 4,149

Total Crash Events

36

-5.3%was 38

Persons Killed

1,792

11.4%was 1,609

Persons Injured

35

Fatal Crash Events

Note: "Persons Killed" (36) counts individual fatalities across all crash events. "Fatal" in the severity table below (35) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic collisions in Iowa increased in August 2017 compared to the same month in the prior year. The total number of crashes rose by 296, from 4,149 to 4,445, representing a 7.1% year-over-year increase. Similarly, the number of people injured in these incidents grew by 11.4%, while fatalities decreased slightly from 38 to 36.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

2

Cyclists Killed

Prior: 0%

33

Motorists Killed

Prior: 37-10.8%

30

Pedestrians Injured

Prior: 37-18.9%

49

Cyclists Injured

Prior: 4022.5%

1,713

Motorists Injured

Prior: 1,52712.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year, with collisions peaking during the afternoon commute. The peak day for crashes shifted slightly from Wednesday (735 crashes) in the prior period to Thursday (762 crashes) in the current period. The peak hour also moved later, from the 4 p.m. hour in 2016 to the 5 p.m. hour in 2017, which recorded 383 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity remained stable between the two periods, with the number of fatal crashes holding steady at 35. The fatal crash rate saw a negligible decrease from 0.84% to 0.79% of all crashes. Crashes resulting in any level of injury (serious, minor, or possible) collectively accounted for 32.7% of incidents in the current period, a slight increase from 31.7% in the prior period, while no-injury crashes decreased proportionally from 67.5% to 66.5%.

Severity is per crash event (most severe injury). 35 fatal crash events resulted in 36 persons killed.

Outcome by Severity (Crash Events)

Fatal35fatal crashes0.8%
0.0%prior 35
Serious Injury122serious injury crashes2.7%
13.0%prior 108
Minor Injury492minor injury crashes11.1%
12.8%prior 436
Possible Injury839possible injury crashes18.9%
9.0%prior 770
No Injury2,957no injury crashes66.5%
5.6%prior 2,800

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both periods was "Followed too close," with counts remaining nearly unchanged at 551 in August 2017 versus 554 in August 2016. A significant change was observed in crashes involving animals, which saw their count increase by 29.2% from 271 to 350, moving it from the second-ranked factor in both periods but with a much larger volume. The count of crashes where a driver "Lost Control" also grew from 233 to 268.

Officer-Reported Primary Contributing Cause

Followed too close551 (12.4%)-0.5%prior 554
Animal350 (7.9%)29.2%prior 271
Other (explain in narrative): Other283 (6.4%)6.4%prior 266
Lost Control268 (6%)15.0%prior 233
Ran off road - left257 (5.8%)8.9%prior 236
FTYROW: From stop sign256 (5.8%)14.3%prior 224
FTYROW: Making left turn220 (4.9%)-3.1%prior 227
Ran Traffic Signal175 (3.9%)5.4%prior 166
Ran off road - straight164 (3.7%)22.4%prior 134
Ran Stop Sign145 (3.3%)33.0%prior 109

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both August 2017 and August 2016 occurred under ideal conditions. In the current period, 69.2% of crashes happened in clear weather, 74.5% in daylight, and 83.0% on dry road surfaces. These proportions are slightly higher than in the prior period, where crashes in clear weather, daylight, and on dry roads accounted for 63.6%, 73.2%, and 81.2% of the total, respectively, indicating no shift toward adverse conditions causing more crashes.

Weather

Clear3,074 (73.7%)
16.4%prior 2,640
Cloudy880 (21.1%)
-8.0%prior 957
Rain195 (4.7%)
-27.8%prior 270
Fog, smoke, smog14 (0.3%)
-44.0%prior 25
Freezing rain/drizzle4 (0.1%)
Other (explain in narrative)2 (0.0%)
Severe Winds1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Weather condition at time of crash

Lighting

Daylight3,311 (79.3%)
9.0%prior 3,037
Dark - roadway lighted367 (8.8%)
-14.3%prior 428
Dark - roadway not lighted326 (7.8%)
2.8%prior 317
Dusk93 (2.2%)
32.9%prior 70
Dawn62 (1.5%)
5.1%prior 59
Dark - unknown roadway lighting17 (0.4%)
54.5%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Lighting condition field

Road Surface

Dry3,689 (88.5%)
9.5%prior 3,368
Wet332 (8.0%)
-20.0%prior 415
Gravel128 (3.1%)
20.8%prior 106
Other (explain in narrative)7 (0.2%)
Sand5 (0.1%)
Mud, dirt3 (0.1%)
Water (standing or moving)3 (0.1%)
-57.1%prior 7
Oil2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes showed a consistent pattern, with Ford and Chevrolet models being the most common in both August 2017 and August 2016. The age distribution of persons involved in crashes also remained stable year-over-year. The 26-34 age group was the largest cohort in both periods, accounting for 1,279 individuals in the current period and 1,303 in the prior, with no significant shifts in demographic representation.

Top Vehicle Makes (7,975 vehicles)

1
FORD1,249 (15.7%)
4.2%prior 1,199
2
CHEV1,024 (12.8%)
50.6%prior 680
3
CHEVROLET527 (6.6%)
-32.8%prior 784
4
TOYT402 (5%)
29.7%prior 310
5
DODG345 (4.3%)
48.1%prior 233
6
HOND282 (3.5%)
57.5%prior 179
7
JEEP261 (3.3%)
13.0%prior 231
8
GMC217 (2.7%)
-0.5%prior 218
9
NR203 (2.5%)
8.0%prior 188
10
TOYOTA200 (2.5%)
-21.6%prior 255

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · Vehicle unit records

972 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,478 persons with recorded sex)

Male3,053 (55.7%)
-0.7%prior 3,074
Female2,425 (44.3%)
4.7%prior 2,316

Source: Iowa Crash Data · ArcGIS Open Data · 2017-08-01 to 2017-08-31 · 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: 2017-08-01 through 2017-08-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2017-08-01 through 2017-08-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,445
  • Total persons involved: 8,430
  • Total vehicles involved: 7,975

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 2017." Published September 9, 2026. Reporting period: 2017-08-01 to 2017-08-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/august-2017-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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