Yearly Traffic Safety Analysis

121 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In 2019, Decatur County recorded 121 total crashes, an increase of 17.5% from the 103 crashes reported in 2018. Despite the rise in overall collisions, the number of fatalities decreased significantly from four in 2018 to one in 2019.

121

▲ 17.5%was 103

Total Crash Events

1

▼ -75.0%was 4

Persons Killed

29

▲ 3.6%was 28

Persons Injured

1

▼ -75.0%was 4

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 · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash volume in Decatur County increased year-over-year, rising from 103 incidents in 2018 to 121 in 2019, a 17.5% increase. While total injuries remained stable with 29 in 2019 compared to 28 in the prior year, fatalities saw a significant decline from four to one.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 4↓-75.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

27

Motorists Injured

Prior: 28↓-3.6%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between 2018 and 2019. While Friday remained the most frequent day for crashes in both years (23 in 2019 vs. 20 in 2018), the peak hour for collisions shifted three hours earlier, from 10 p.m. in 2018 (8 crashes) to 7 p.m. in 2019 (10 crashes). Crashes on Mondays also saw a notable increase from 14 to 21 year-over-year.

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes generally decreased in 2019 compared to the previous year. The number of fatal crashes dropped from four in 2018 to one in 2019, with the corresponding share of fatal incidents falling from 3.9% to 0.8% of all crashes. While crashes resulting in serious and minor injuries also decreased, the count of crashes with possible injuries more than doubled, increasing from 7 in 2018 to 17 in 2019.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
↓-75.0%prior 4
Serious Injury1serious injury crashes0.8%
↓-50.0%prior 2
Minor Injury9minor injury crashes7.4%
↓-25.0%prior 12
Possible Injury17possible injury crashes14%
↑142.9%prior 7
No Injury93no injury crashes76.9%
↑19.2%prior 78

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors to crashes in Decatur County remained consistent year-over-year. Collisions involving an animal were the leading factor in both 2019 (44 crashes) and 2018 (42 crashes), followed by a driver losing control (20 crashes in 2019 vs. 19 in 2018). The top three factors did not change in ranking between the two periods. Notably, crashes where a driver ran a stop sign increased from one instance in 2018 to three in 2019.

Officer-Reported Primary Contributing Cause

Animal44 (36.4%)↑4.8%prior 42
Lost Control20 (16.5%)↑5.3%prior 19
Ran off road - straight7 (5.8%)→0.0%prior 7
Ran off road - left5 (4.1%)
Other (explain in narrative): Other5 (4.1%)
Followed too close4 (3.3%)
Driving too fast for conditions4 (3.3%)
Ran off road - right3 (2.5%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (2.5%)
Ran Stop Sign3 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and on dry roads increased in 2019 compared to 2018. Crashes in daylight conditions rose from 37 in 2018 to 59 in 2019, accounting for 48.8% of all incidents versus 35.9% in the prior year. Collisions during snowy weather decreased from 7 to 3, while crashes on dark, unlighted roadways remained relatively stable with 27 incidents in 2019 compared to 26 in 2018.

Weather

Clear58 (63.7%)
↑48.7%prior 39
Cloudy17 (18.7%)
↑6.3%prior 16
Rain7 (7.7%)
↑40.0%prior 5
Snow3 (3.3%)
↓-57.1%prior 7
Freezing rain/drizzle3 (3.3%)
Blowing Snow1 (1.1%)
Fog, smoke, smog1 (1.1%)
Blowing sand, soil, dirt1 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash

Lighting

Daylight59 (64.8%)
↑59.5%prior 37
Dark - roadway not lighted27 (29.7%)
↑3.8%prior 26
Dawn3 (3.3%)
Dark - unknown roadway lighting1 (1.1%)
Dusk1 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field

Road Surface

Dry66 (71.7%)
↑37.5%prior 48
Wet12 (13.0%)
↑20.0%prior 10
Snow8 (8.7%)
↑14.3%prior 7
Gravel3 (3.3%)
Ice/frost2 (2.2%)
Water (standing or moving)1 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field

Vehicles & Demographics

An analysis of vehicles involved in crashes shows a shift in the top makes between the two years. While Ford was the most common make in 2018 crashes (24 vehicles), Chevrolet-branded vehicles were most frequent in 2019 (40 vehicles). The total number of vehicles involved in crashes increased from 130 in 2018 to 158 in 2019. Among persons involved in crashes, the 26-34 age group's representation grew, accounting for 20.2% of individuals with a known age in 2019, up from 15.8% in 2018.

Top Vehicle Makes (158 vehicles)

1
CHEVROLET22 (13.9%)
↑266.7%prior 6
2
FORD18 (11.4%)
↓-25.0%prior 24
3
CHEV18 (11.4%)
↑28.6%prior 14
4
DODG10 (6.3%)
↑25.0%prior 8
5
GMC7 (4.4%)
6
DODGE7 (4.4%)
→0.0%prior 7
7
HONDA5 (3.2%)
→0.0%prior 5
8
BUIC5 (3.2%)
9
KENWORTH5 (3.2%)
10
VOLVO4 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records

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

Sex Distribution (143 persons with recorded sex)

Male105 (73.4%)
↑61.5%prior 65
Female38 (26.6%)
↑52.0%prior 25

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 121
  • Total persons involved: 230
  • Total vehicles involved: 158

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: 2019." Published September 9, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2019-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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