Yearly Traffic Safety Analysis

548 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Muscatine County recorded 548 total traffic crashes, a 6.5% decrease from the 586 crashes documented in 2017. While total fatalities remained unchanged at four, the number of injuries fell by 21.9% from 251 to 196. The most significant year-over-year change was a 63.4% reduction in crashes involving driving under the influence (DUI), which dropped from 41 incidents in 2017 to 15 in 2018.

548

▼ -6.5%was 586

Total Crash Events

4

Persons Killed

196

▼ -21.9%was 251

Persons Injured

3

▼ -25.0%was 4

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Overall traffic safety trends in Muscatine County improved from 2017 to 2018. The total number of crashes declined by 6.5%, from 586 to 548. This was accompanied by a 21.9% decrease in injuries, from 251 to 196, and a 25% drop in fatal crashes, from 4 to 3, even as the total number of fatalities held steady at 4.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 1↓-100.0%

3

Motorists Killed

Prior: 3→0.0%

0

Other Killed

Prior: 0→0.0%

6

Pedestrians Injured

Prior: 7↓-14.3%

1

Cyclists Injured

Prior: 2↓-50.0%

187

Motorists Injured

Prior: 241↓-22.4%

2

Other Injured

Prior: 1↑100.0%

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

The temporal patterns of crashes in Muscatine County remained consistent year-over-year. Tuesday was the peak day for crashes in both 2018 (96 crashes) and 2017 (92 crashes). Similarly, the 5 p.m. hour was the single busiest hour for collisions in both periods, with 50 crashes in 2018 and 53 in 2017, indicating stable daily and weekly traffic risk patterns.

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

Crash outcomes became less severe in 2018 compared to the prior year. The fatal crash rate decreased from 0.68% to 0.55% of all crashes. Most notably, the count of serious injury crashes fell sharply from 29 to 9, and their share of all crashes dropped from 4.9% to 1.6%. Consequently, the proportion of crashes resulting in no injuries increased from 65.5% in 2017 to 71.7% in 2018.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
↓-25.0%prior 4
Serious Injury9serious injury crashes1.6%
↓-69.0%prior 29
Minor Injury65minor injury crashes11.9%
↓-19.8%prior 81
Possible Injury78possible injury crashes14.2%
↓-11.4%prior 88
No Injury393no injury crashes71.7%
↑2.3%prior 384

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 were the leading contributing factor in both years, with the count of such incidents increasing by 36.7% from 128 in 2017 to 175 in 2018. This factor's share of all crashes grew from 21.8% to 31.9%. Conversely, several other top factors saw a decline in count, including "Followed too close" (from 48 to 38 incidents), "FTYROW: Making left turn" (from 34 to 23), and "Ran Stop Sign" (from 25 to 15).

Officer-Reported Primary Contributing Cause

Animal175 (31.9%)↑36.7%prior 128
Followed too close38 (6.9%)↓-20.8%prior 48
Other (explain in narrative): Other37 (6.8%)↑2.8%prior 36
FTYROW: From stop sign29 (5.3%)↓-14.7%prior 34
Lost Control26 (4.7%)↓-3.7%prior 27
FTYROW: Making left turn23 (4.2%)↓-32.4%prior 34
Ran off road - left20 (3.6%)↓-23.1%prior 26
Driving too fast for conditions20 (3.6%)↓-13.0%prior 23
Ran Stop Sign15 (2.7%)↓-40.0%prior 25
Ran off road - straight14 (2.6%)↓-33.3%prior 21

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

Road & Environmental Conditions

The conditions under which crashes occurred shifted between the two periods. The share of crashes happening on dry road surfaces decreased from 65.7% in 2017 to 54.2% in 2018. Correspondingly, crashes on icy or frosty roads increased from 6 incidents to 20. The proportion of crashes in clear weather also decreased, from 60.9% of all crashes in 2017 to 51.0% in 2018, while lighting conditions remained relatively stable.

Weather

Clear279 (68.4%)
↓-21.8%prior 357
Cloudy68 (16.7%)
↓-6.8%prior 73
Rain24 (5.9%)
↓-14.3%prior 28
Snow14 (3.4%)
→0.0%prior 14
Freezing rain/drizzle13 (3.2%)
Fog, smoke, smog3 (0.7%)
↓-57.1%prior 7
Blowing Snow3 (0.7%)
Other (explain in narrative)2 (0.5%)
Blowing sand, soil, dirt1 (0.2%)
Severe Winds1 (0.2%)

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

Lighting

Daylight257 (63.3%)
↓-14.6%prior 301
Dark - roadway not lighted67 (16.5%)
↓-18.3%prior 82
Dark - roadway lighted61 (15.0%)
↓-21.8%prior 78
Dusk12 (3.0%)
↑100.0%prior 6
Dawn7 (1.7%)
↓-46.2%prior 13
Dark - unknown roadway lighting2 (0.5%)

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

Road Surface

Dry297 (72.8%)
↓-22.9%prior 385
Wet60 (14.7%)
↑1.7%prior 59
Ice/frost20 (4.9%)
↑233.3%prior 6
Snow19 (4.7%)
↑11.8%prior 17
Gravel7 (1.7%)
↓-36.4%prior 11
Slush3 (0.7%)
Other (explain in narrative)2 (0.5%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes showed some shifts between 2017 and 2018. While Ford and Chevrolet remained the top two makes, their ranks swapped, with Chevrolet becoming the most frequent make in 2018 (192 vehicles) compared to Ford in 2017 (151 vehicles). Among persons involved in crashes, there was a decrease in the 16-20 age group (from 148 to 124 persons) and an increase in the 26-34 age group (from 164 to 183 persons).

Top Vehicle Makes (859 vehicles)

1
CHEV139 (16.2%)
↑31.1%prior 106
2
FORD135 (15.7%)
↓-10.6%prior 151
3
TOYT58 (6.8%)
→0.0%prior 58
4
CHEVROLET53 (6.2%)
↓-39.8%prior 88
5
DODG41 (4.8%)
↓-18.0%prior 50
6
HOND30 (3.5%)
↑36.4%prior 22
7
GMC29 (3.4%)
↓-9.4%prior 32
8
JEEP25 (2.9%)
↓-21.9%prior 32
9
KIA25 (2.9%)
→0.0%prior 25
10
TOYOTA21 (2.4%)
↓-36.4%prior 33

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

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

Sex Distribution (637 persons with recorded sex)

Male382 (60.0%)
↑0.8%prior 379
Female255 (40.0%)
↓-8.9%prior 280

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: 548
  • Total persons involved: 1,097
  • Total vehicles involved: 859

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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