Yearly Traffic Safety Analysis

343 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In 2019, Buchanan County recorded 343 total crashes, an 8.5% increase from the 316 crashes documented in 2018. While the total number of injuries remained stable with 97 in 2019 compared to 94 in the prior year, the number of fatalities tripled from one to three. The most significant year-over-year shift was this increase in crash severity, alongside a notable rise in crashes within the city of Independence.

343

▲ 8.5%was 316

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

97

▲ 3.2%was 94

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) 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 · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash volume in Buchanan County trended upward from 2018 to 2019, with total incidents increasing by 8.5% from 316 to 343. This increase was accompanied by a more severe outcome profile, as fatalities rose from one to three, even as the total number of injuries saw only a minor increase from 94 to 97.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 0→%

1

Cyclists Injured

Prior: 2↓-50.0%

96

Motorists Injured

Prior: 91↑5.5%

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 shifted between the two periods. In 2019, the peak day for crashes was Tuesday with 60 incidents, a change from Wednesday (54 incidents) in 2018. The busiest time of day also shifted an hour later, with the peak moving from the 4 p.m. hour in 2018 (26 crashes) to the 5 p.m. hour in 2019 (38 crashes).

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 worsened year-over-year. The number of fatal crashes increased from one in 2018 to three in 2019, raising the share of fatal crashes from 0.3% to 0.9% of all incidents. While the count of serious injury crashes increased slightly from 6 to 7, minor injury crashes decreased from 32 to 26, representing a drop from 10.1% to 7.6% of all crashes.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
↑200.0%prior 1
Serious Injury7serious injury crashes2%
↑16.7%prior 6
Minor Injury26minor injury crashes7.6%
↓-18.8%prior 32
Possible Injury45possible injury crashes13.1%
↑25.0%prior 36
No Injury262no injury crashes76.4%
↑8.7%prior 241

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

Collisions involving animals remained the leading contributing factor in both years, with a nearly identical count of 108 crashes in 2019 versus 107 in 2018. The ranking of other top factors changed, with 'Driving too fast for conditions' increasing from 25 to 29 incidents to become the second-most common factor in 2019. Conversely, crashes attributed to 'Lost Control' decreased from 31 to 23, moving from the second to the third-ranked cause.

Officer-Reported Primary Contributing Cause

Animal108 (31.5%)↑0.9%prior 107
Driving too fast for conditions29 (8.5%)↑16.0%prior 25
Lost Control23 (6.7%)↓-25.8%prior 31
Other (explain in narrative): Other23 (6.7%)↑35.3%prior 17
Followed too close19 (5.5%)↑26.7%prior 15
Ran off road - straight16 (4.7%)→0.0%prior 16
FTYROW: From stop sign15 (4.4%)↑50.0%prior 10
Ran Stop Sign12 (3.5%)↑33.3%prior 9
Ran off road - left12 (3.5%)↓-20.0%prior 15
Failed to keep in proper lane6 (1.7%)

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 majority of crashes in both years occurred in clear weather and on dry roads. However, the proportion of crashes happening in daylight increased from 46.5% of all crashes in 2018 to 54.0% in 2019. There was a notable increase in crashes on adverse road surfaces; incidents on both icy/frosty roads and snowy roads rose from 21 each in 2018 to 31 each in 2019.

Weather

Clear153 (60.7%)
↑20.5%prior 127
Cloudy47 (18.7%)
↓-4.1%prior 49
Snow12 (4.8%)
↓-25.0%prior 16
Freezing rain/drizzle12 (4.8%)
↑33.3%prior 9
Rain12 (4.8%)
↑33.3%prior 9
Blowing Snow8 (3.2%)
↑60.0%prior 5
Fog, smoke, smog4 (1.6%)
Sleet, hail2 (0.8%)
Other (explain in narrative)1 (0.4%)
Severe Winds1 (0.4%)

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

Lighting

Daylight185 (73.7%)
↑25.9%prior 147
Dark - roadway not lighted46 (18.3%)
↓-2.1%prior 47
Dark - roadway lighted11 (4.4%)
↑10.0%prior 10
Dusk7 (2.8%)
↓-36.4%prior 11
Dawn2 (0.8%)

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

Road Surface

Dry152 (60.3%)
↑3.4%prior 147
Ice/frost31 (12.3%)
↑47.6%prior 21
Snow31 (12.3%)
↑47.6%prior 21
Wet28 (11.1%)
↑21.7%prior 23
Slush9 (3.6%)
Gravel1 (0.4%)
↓-83.3%prior 6

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

Vehicles & Demographics

Ford vehicles were involved in more crashes in 2019 (88) compared to 2018 (70), making it the top individual make. A significant demographic shift occurred among persons involved in crashes, with notable increases in the 26-34 age group (from 72 to 115 persons) and the 35-44 age group (from 70 to 118 persons). The 21-25 age group also saw a material increase from 54 to 74 persons involved.

Top Vehicle Makes (502 vehicles)

1
FORD88 (17.5%)
↑25.7%prior 70
2
CHEV77 (15.3%)
↓-18.9%prior 95
3
CHEVROLET43 (8.6%)
↑115.0%prior 20
4
DODG22 (4.4%)
↓-35.3%prior 34
5
JEEP17 (3.4%)
↑183.3%prior 6
6
TOYT17 (3.4%)
↑13.3%prior 15
7
BUIC16 (3.2%)
↑45.5%prior 11
8
HOND15 (3%)
↑25.0%prior 12
9
CHRY15 (3%)
↓-11.8%prior 17
10
GMC14 (2.8%)
↑75.0%prior 8

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

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

Sex Distribution (467 persons with recorded sex)

Male252 (54.0%)
↑18.3%prior 213
Female215 (46.0%)
↑90.3%prior 113

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 10, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 343
  • Total persons involved: 723
  • Total vehicles involved: 502

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 10, 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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