Yearly Traffic Safety Analysis

27 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Adams County recorded 27 total crashes, a 34.1% decrease from the 41 crashes reported in 2017. There were no fatalities in either period. The most notable year-over-year shift was the significant reduction in injuries, which fell by 73.7% from 19 in 2017 to 5 in 2018.

27

▼ -34.1%was 41

Total Crash Events

0

Persons Killed

5

▼ -73.7%was 19

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 metrics in Adams County showed a positive trend, with crashes declining significantly from 2017 to 2018. The total number of crashes fell by 34.1%, from 41 to 27. This downward trend was even more pronounced for injuries, which decreased by 73.7% from 19 to 5.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

5

Motorists Injured

Prior: 19↓-73.7%

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 shifted between the two periods. The peak day for crashes moved from Friday (11 crashes) in 2017 to Sunday (8 crashes) in 2018. A similar change occurred with the peak time for collisions, which shifted from 9 PM in 2017 (5 crashes) to the morning hour of 7 AM in 2018 (4 crashes).

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 severity improved significantly from 2017 to 2018. While both years were free of fatal crashes, the 6 serious injury crashes recorded in 2017 were completely eliminated in 2018. Correspondingly, the proportion of crashes resulting in no injuries increased from 63.4% of all incidents in 2017 to 81.5% in 2018.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes14.8%
↓-33.3%prior 6
Possible Injury1possible injury crashes3.7%
↓-66.7%prior 3
No Injury22no injury crashes81.5%
↓-15.4%prior 26

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 involving an animal remained the leading contributing factor in both years, but the count of such incidents dropped by 56.3%, from 16 crashes in 2017 to 7 in 2018. 'Lost Control' was the second-ranked factor in both periods, with its count decreasing from 5 to 4. As a share of all crashes, animal-related incidents fell from 39.0% in the prior year to 25.9% in the current year.

Officer-Reported Primary Contributing Cause

Animal7 (25.9%)↓-56.3%prior 16
Lost Control4 (14.8%)↓-20.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner2 (7.4%)
Other (explain in narrative): Other2 (7.4%)
FTYROW: From driveway2 (7.4%)
Operator inexperience1 (3.7%)
Ran off road - right1 (3.7%)
Illegally Parked/Unattended1 (3.7%)
Downhill runaway1 (3.7%)
Driver Distraction: Other interior distraction1 (3.7%)

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

Road & Environmental Conditions

While the proportion of crashes occurring in adverse weather and on non-dry road surfaces remained relatively stable year-over-year, there was a notable shift in lighting conditions. The share of crashes occurring in daylight increased from 31.7% of all crashes in 2017 to 55.6% in 2018. Conversely, crashes on dark, unlighted roadways saw a substantial decrease, falling from 12 incidents in 2017 to 4 in 2018.

Weather

Clear14 (66.7%)
↓-39.1%prior 23
Cloudy4 (19.0%)
↓-20.0%prior 5
Snow2 (9.5%)
Blowing Snow1 (4.8%)

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

Lighting

Daylight15 (75.0%)
↑15.4%prior 13
Dark - roadway not lighted4 (20.0%)
↓-66.7%prior 12
Dark - roadway lighted1 (5.0%)

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

Road Surface

Dry17 (81.0%)
↓-29.2%prior 24
Snow3 (14.3%)
Ice/frost1 (4.8%)

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

Vehicles & Demographics

Top Vehicle Makes (39 vehicles)

1
FORD7 (17.9%)
↓-50.0%prior 14
2
CHEV7 (17.9%)
↓-22.2%prior 9
3
CHEVROLET6 (15.4%)
↓-14.3%prior 7
4
DODGE3 (7.7%)
5
PONTIAC2 (5.1%)
6
CHRYSLER2 (5.1%)
7
GMC2 (5.1%)
8
FREIGHTLINER1 (2.6%)
9
BUIC1 (2.6%)
10
JEEP1 (2.6%)

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

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

Sex Distribution (32 persons with recorded sex)

Male19 (59.4%)
↑18.8%prior 16
Female13 (40.6%)
↓-23.5%prior 17

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: 27
  • Total persons involved: 49
  • Total vehicles involved: 39

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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