Yearly Traffic Safety Analysis

208 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Appanoose County, total traffic crashes increased by 18.2%, rising from 176 incidents in 2023 to 208 in 2024. Despite the overall increase in crashes and a 27.7% rise in injuries from 47 to 60, the most notable year-over-year shift was a positive one: the number of traffic fatalities fell from one in the prior period to zero in the current period.

208

▲ 18.2%was 176

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

60

▲ 27.7%was 47

Persons Injured

0

▼ -100.0%was 1

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Appanoose County show an increase in crash frequency year-over-year. Total crashes rose from 176 to 208, an 18.2% increase, while the number of people injured grew from 47 to 60. In contrast to this trend, the county recorded zero traffic fatalities in 2024, down from one in 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

60

Motorists Injured

Prior: 46↑30.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. The peak day for crashes moved from Friday (31 crashes) in 2023 to Monday (36 crashes) in 2024. Similarly, the peak hour for incidents shifted slightly earlier, from the 8 p.m. and 9 p.m. hours in the prior year to 7 p.m. in the current year, which saw 16 crashes. November was a month with a high volume of crashes in both years, with 31 incidents in 2024 and 20 in 2023.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes improved, as fatal crashes dropped from one in 2023 to zero in 2024. The count of serious injury crashes remained unchanged at six incidents in both periods, though their share of total crashes decreased slightly from 3.4% to 2.9%. Conversely, crashes resulting in minor injuries increased in both count, from 15 to 22, and proportion, from 8.5% to 10.6% of all crashes.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes2.9%
→0.0%prior 6
Minor Injury22minor injury crashes10.6%
↑46.7%prior 15
Possible Injury19possible injury crashes9.1%
→0.0%prior 19
No Injury161no injury crashes77.4%
↑19.3%prior 135

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, with the count of such incidents increasing by 15.4% from 65 to 75. The share of crashes attributed to this factor remained stable at approximately 36%. Crashes cited for "Driving too fast for conditions" doubled in count from 7 to 14, while incidents involving "Lost Control" decreased by 33.3%, from 12 crashes in 2023 to 8 in 2024.

Officer-Reported Primary Contributing Cause

Animal75 (36.1%)↑15.4%prior 65
Driving too fast for conditions14 (6.7%)↑100.0%prior 7
FTYROW: From stop sign10 (4.8%)↑25.0%prior 8
Other (explain in narrative): Other10 (4.8%)↑66.7%prior 6
Lost Control8 (3.8%)↓-33.3%prior 12
Followed too close7 (3.4%)↑40.0%prior 5
Ran off road - left7 (3.4%)↓-12.5%prior 8
Driver Distraction: Other interior distraction7 (3.4%)→0.0%prior 7
FTYROW: Making left turn7 (3.4%)
Made improper turn5 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and daylight conditions increased year-over-year, accounting for 51.0% and 47.6% of crashes in 2024, respectively. While the share of crashes on dry road surfaces was stable at around 50% in both periods, incidents on adverse surfaces like wet, snow, or ice saw a proportional increase. These crashes represented 18.3% of the total in the current period, up from 15.3% in the prior year.

Weather

Clear106 (75.2%)
↑27.7%prior 83
Cloudy18 (12.8%)
↑12.5%prior 16
Rain11 (7.8%)
↑37.5%prior 8
Freezing rain/drizzle2 (1.4%)
Fog, smoke, smog2 (1.4%)
Snow2 (1.4%)
↓-77.8%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight99 (68.3%)
↑33.8%prior 74
Dark - roadway not lighted28 (19.3%)
↑21.7%prior 23
Dark - roadway lighted10 (6.9%)
↓-37.5%prior 16
Dark - unknown roadway lighting3 (2.1%)
Dusk3 (2.1%)
Dawn2 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry103 (73.0%)
↑17.0%prior 88
Wet18 (12.8%)
↑50.0%prior 12
Gravel8 (5.7%)
↑33.3%prior 6
Snow7 (5.0%)
↑16.7%prior 6
Ice/frost4 (2.8%)
Slush1 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

A notable shift occurred in the makes of vehicles involved in crashes, as Chevrolet (87 vehicles, combining 'CHEV' and 'CHEVROLET' entries) surpassed Ford (52 vehicles) as the most common make, a reversal from 2023. Analysis of persons involved shows the 65+ age group's representation grew significantly, from 10.6% of all persons in the prior period to 16.5% in the current period. The share of persons in the 16-20 age group also increased from 16.2% to 18.1%.

Top Vehicle Makes (299 vehicles)

1
CHEV68 (22.7%)
↑58.1%prior 43
2
FORD52 (17.4%)
↓-7.1%prior 56
3
CHEVROLET19 (6.4%)
↑171.4%prior 7
4
GMC18 (6%)
↑80.0%prior 10
5
DODG17 (5.7%)
↑41.7%prior 12
6
TOYT12 (4%)
↑33.3%prior 9
7
BUIC11 (3.7%)
↑37.5%prior 8
8
NISS10 (3.3%)
9
JEEP9 (3%)
↓-52.6%prior 19
10
KIA7 (2.3%)
↑40.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (150 persons with recorded sex)

Male96 (64.0%)
↓-29.9%prior 137
Female54 (36.0%)
↓-41.9%prior 93

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 208
  • Total persons involved: 310
  • Total vehicles involved: 299

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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