Yearly Traffic Safety Analysis

83 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Pocahontas County recorded 83 total crashes, representing a 22.1% increase from the 68 crashes documented in 2017. While the overall number of crashes rose, the most significant year-over-year change was in fatalities, which increased from 1 in 2017 to 6 in 2018. Conversely, the total number of people injured in crashes decreased from 46 to 26.

83

▲ 22.1%was 68

Total Crash Events

6

▲ 500.0%was 1

Persons Killed

26

▼ -43.5%was 46

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (6) 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

The overall crash trend in Pocahontas County from 2017 to 2018 shows an increase in both the frequency and severity of collisions. Total crashes rose by 22.1% from 68 to 83. This increase was marked by a sharp rise in fatalities from 1 to 6, even as the number of non-fatal injuries reported fell by 43.5%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 1↑500.0%

1

Pedestrians Injured

Prior: 0→%

25

Motorists Injured

Prior: 46↓-45.7%

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 remained relatively stable year-over-year. Friday was the peak day for crashes in both 2018 (15 crashes) and 2017 (16 crashes). The peak hour for collisions shifted slightly, moving from 10 a.m. in 2017 (8 crashes) to 11 a.m. in 2018 (11 crashes). A notable change occurred on Mondays, which saw an increase from 8 crashes in 2017 to 14 in 2018.

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 significantly worsened in 2018 compared to the prior year. The number of fatal crashes tripled from 1 to 3, and the corresponding fatality count increased from 1 to 6. Consequently, the fatal crash rate rose from 1.5% of all crashes in 2017 to 3.6% in 2018. While the proportion of minor injury crashes decreased from 20.6% to 10.8%, the share of crashes with no injuries increased from 60.3% to 69.9%.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes3.6%
↑200.0%prior 1
Serious Injury3serious injury crashes3.6%
↓-25.0%prior 4
Minor Injury9minor injury crashes10.8%
↓-35.7%prior 14
Possible Injury10possible injury crashes12%
↑25.0%prior 8
No Injury58no injury crashes69.9%
↑41.5%prior 41

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

The leading contributing factors to crashes showed some notable shifts between periods. "Lost Control" remained a primary cause, accounting for 12 incidents in both 2017 and 2018. Crashes involving animals increased by 66.7%, from 6 incidents in 2017 to 10 in 2018, making it the second-leading factor. In contrast, crashes attributed to "Ran off road - straight" fell from 11 to 4 incidents, while those due to "Driving too fast for conditions" tripled from 2 to 6.

Officer-Reported Primary Contributing Cause

Lost Control12 (14.5%)→0.0%prior 12
Animal10 (12%)↑66.7%prior 6
Driving too fast for conditions6 (7.2%)
Ran off road - left5 (6%)
Ran off road - straight4 (4.8%)↓-63.6%prior 11
Followed too close3 (3.6%)
FTYROW: From driveway3 (3.6%)
FTYROW: From stop sign3 (3.6%)
Improper Backing3 (3.6%)
Ran off road - right3 (3.6%)

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 during which crashes occurred were largely consistent across both years, with the majority happening in clear weather, during daylight, and on dry roads. The proportion of crashes in daylight increased from 60.3% in 2017 to 67.5% in 2018. A notable change was observed in road surface conditions, where the number of crashes on icy or frosty roads doubled from 5 incidents in 2017 to 10 in 2018.

Weather

Clear54 (71.1%)
↑31.7%prior 41
Cloudy13 (17.1%)
→0.0%prior 13
Rain4 (5.3%)
Blowing Snow3 (3.9%)
Fog, smoke, smog1 (1.3%)
Snow1 (1.3%)
↓-80.0%prior 5

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

Lighting

Daylight56 (72.7%)
↑36.6%prior 41
Dark - roadway not lighted15 (19.5%)
→0.0%prior 15
Dark - roadway lighted3 (3.9%)
Dawn3 (3.9%)

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

Road Surface

Dry52 (67.5%)
↑13.0%prior 46
Ice/frost10 (13.0%)
↑100.0%prior 5
Wet7 (9.1%)
↓-22.2%prior 9
Snow6 (7.8%)
→0.0%prior 6
Gravel2 (2.6%)

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

Vehicles & Demographics

Vehicle and person demographics saw some changes between 2017 and 2018. Ford and Chevrolet remained the top two vehicle makes involved in crashes in both periods, with similar counts year-over-year. The age distribution of people involved in crashes shifted, with a notable increase in older individuals; the 55-64 and 65+ age groups grew from 19 and 18 people respectively in 2017 to 25 each in 2018. The 16-20 age group also saw an increase from 16 to 22 people involved in crashes.

Top Vehicle Makes (129 vehicles)

1
FORD23 (17.8%)
↓-4.2%prior 24
2
CHEVROLET18 (14%)
↓-14.3%prior 21
3
CHEV11 (8.5%)
↑120.0%prior 5
4
FREIGHTLINER6 (4.7%)
5
BUICK6 (4.7%)
↓-25.0%prior 8
6
DODGE6 (4.7%)
↓-14.3%prior 7
7
GMC6 (4.7%)
8
DODG5 (3.9%)
9
INTERNATIONA4 (3.1%)
10
NR4 (3.1%)

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

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

Sex Distribution (94 persons with recorded sex)

Male57 (60.6%)
↑23.9%prior 46
Female37 (39.4%)
↑37.0%prior 27

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: 83
  • Total persons involved: 154
  • Total vehicles involved: 129

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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