Yearly Traffic Safety Analysis

104 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Keokuk County, total traffic crashes decreased by 15.4%, from 123 incidents in 2017 to 104 in 2018. During this period, the number of fatalities remained stable at one, while total injuries saw a significant 44.2% reduction, falling from 52 to 29. The most notable year-over-year shift was a 66.7% decrease in crashes attributed to a driver losing control, which dropped from 30 incidents to 10.

104

▼ -15.4%was 123

Total Crash Events

1

Persons Killed

29

▼ -44.2%was 52

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Keokuk County shows a decline in traffic incidents year-over-year. Total crashes fell by 15.4% from 123 in 2017 to 104 in 2018. This downward trend was also reflected in the number of people injured, which decreased by 44.2% from 52 to 29, while fatalities held steady at one for both years.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Cyclists Injured

Prior: 0→%

28

Motorists Injured

Prior: 51↓-45.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns shifted between the two periods. In 2018, the peak day for crashes was Friday with 19 incidents, a change from 2017 when Wednesday saw the most crashes at 24. The peak hours for crashes in 2018 were more spread out, with 7 a.m., 3 p.m., and 5 p.m. each recording 8 incidents. This contrasts with 2017, where the afternoon hours of 3 p.m. and 5 p.m. were the distinct peaks with 13 crashes each.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes lessened overall from 2017 to 2018. The proportion of collisions resulting in any type of injury decreased from 33.3% of all crashes in 2017 to 24.0% in 2018. While the number of fatal crashes was unchanged at one, the fatal crash rate per incident increased from 0.81% to 0.96% due to the lower total crash volume. Notably, crashes resulting in minor injuries fell from 19 to 8, and those with possible injuries dropped from 17 to 10.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
→0.0%prior 1
Serious Injury7serious injury crashes6.7%
↑40.0%prior 5
Minor Injury8minor injury crashes7.7%
↓-57.9%prior 19
Possible Injury10possible injury crashes9.6%
↓-41.2%prior 17
No Injury78no injury crashes75%
↓-3.7%prior 81

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the primary contributing factor in both years, though the count of such incidents decreased from 42 in 2017 to 33 in 2018. The most significant change was observed in crashes attributed to a driver losing control; this factor's count dropped by 66.7%, from 30 incidents in 2017 to 10 in 2018. As a result, 'Lost Control' fell from being the second-leading cause, accounting for a 24.4% share of crashes in 2017, to a 9.6% share in 2018.

Officer-Reported Primary Contributing Cause

Animal33 (31.7%)↓-21.4%prior 42
Lost Control10 (9.6%)↓-66.7%prior 30
Ran off road - straight8 (7.7%)↑33.3%prior 6
Other (explain in narrative): Other6 (5.8%)
Followed too close4 (3.8%)
FTYROW: Making left turn4 (3.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (3.8%)
Driving too fast for conditions3 (2.9%)
Swerving/Evasive Action3 (2.9%)
Driver Distraction: Exterior distraction2 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both periods occurred predominantly under favorable conditions. The proportion of crashes happening in clear weather increased from a 37.4% share in 2017 to a 47.1% share in 2018, while the share of crashes in daylight also rose from 46.3% to 51.0%. Conversely, the proportion of crashes on dry road surfaces saw a slight decrease from a 56.1% share to a 51.0% share.

Weather

Clear49 (68.1%)
↑6.5%prior 46
Cloudy16 (22.2%)
↓-48.4%prior 31
Snow4 (5.6%)
Freezing rain/drizzle1 (1.4%)
Rain1 (1.4%)
Severe Winds1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight53 (73.6%)
↓-7.0%prior 57
Dark - roadway not lighted11 (15.3%)
↓-15.4%prior 13
Dawn4 (5.6%)
Dark - roadway lighted2 (2.8%)
↓-60.0%prior 5
Dusk2 (2.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry53 (73.6%)
↓-23.2%prior 69
Wet10 (13.9%)
↑42.9%prior 7
Snow5 (6.9%)
Ice/frost3 (4.2%)
Gravel1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet (35 vehicles), Ford (21), and Dodge (18) leading in 2018, compared to Chevrolet (36), Ford (27), and Dodge (20) in 2017. The age distribution of persons involved showed some shifts; the 16-20 age group's involvement increased from 18 to 28 individuals, while the 55-64 age group saw a significant decrease from 31 to 17 individuals. The 26-34 age group was the largest demographic in both years, with 35 individuals involved in each period.

Top Vehicle Makes (146 vehicles)

1
CHEV26 (17.8%)
↑44.4%prior 18
2
FORD21 (14.4%)
↓-22.2%prior 27
3
DODG11 (7.5%)
↓-15.4%prior 13
4
CHEVROLET9 (6.2%)
↓-50.0%prior 18
5
TOYT8 (5.5%)
6
GMC7 (4.8%)
↑16.7%prior 6
7
KIA6 (4.1%)
8
DODGE5 (3.4%)
→0.0%prior 5
9
JEEP5 (3.4%)
↓-50.0%prior 10
10
PONT5 (3.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

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

Sex Distribution (113 persons with recorded sex)

Male69 (61.1%)
↑4.5%prior 66
Female44 (38.9%)
↑15.8%prior 38

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 104
  • Total persons involved: 193
  • Total vehicles involved: 146

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: 2018." Published September 9, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2018-annual-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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