Yearly Traffic Safety Analysis

176 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Appanoose County recorded 176 total crashes, a 5.4% decrease from the 186 crashes reported in 2022. Despite the reduction in overall collisions, the number of fatalities remained unchanged at one death in each period. The total number of injuries saw a marginal increase from 46 in 2022 to 47 in 2023.

176

▼ -5.4%was 186

Total Crash Events

1

Persons Killed

47

▲ 2.2%was 46

Persons Injured

1

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Appanoose County shows a slight decline year-over-year. Total crashes decreased by 5.4%, from 186 in 2022 to 176 in 2023. However, the outcomes of these crashes remained largely consistent, with total fatalities holding steady at one and total injuries increasing by a single person, from 46 to 47.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

46

Motorists Injured

Prior: 42↑9.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes showed notable shifts between the two periods, although the peak day for collisions remained Friday with 31 incidents in both 2022 and 2023. The peak hour for crashes moved from the afternoon at 3 p.m. in 2022 (15 crashes) to later in the evening in 2023, with 8 p.m. and 9 p.m. each recording a high of 14 crashes. The month with the most crashes also changed, shifting from November (24 crashes) in the prior year to September (22 crashes) in the current year.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes remained relatively stable year-over-year, with one fatal crash recorded in both 2023 and 2022, and the fatal crash rate increasing slightly from 0.54 to 0.57 per 100 crashes. While the number of serious injury crashes decreased from 7 to 6 and minor injury crashes fell from 19 to 15, possible injury crashes increased from 17 to 19. Crashes resulting in no injuries constituted the vast majority in both periods, accounting for 76.7% in 2023 and 76.3% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
→0.0%prior 1
Serious Injury6serious injury crashes3.4%
↓-14.3%prior 7
Minor Injury15minor injury crashes8.5%
↓-21.1%prior 19
Possible Injury19possible injury crashes10.8%
↑11.8%prior 17
No Injury135no injury crashes76.7%
↓-4.9%prior 142

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both years, though the count decreased from 70 in 2022 to 65 in 2023. Significant shifts occurred among other top factors; incidents where a driver failed to yield the right-of-way from a stop sign increased from 2 to 8, and 'Lost Control' crashes rose from 7 to 12. Conversely, crashes attributed to 'Ran off road - left' decreased from 14 in the prior year to 8 in the current year.

Officer-Reported Primary Contributing Cause

Animal65 (36.9%)↓-7.1%prior 70
Lost Control12 (6.8%)↑71.4%prior 7
FTYROW: From stop sign8 (4.5%)
Ran off road - left8 (4.5%)↓-42.9%prior 14
Driving too fast for conditions7 (4%)
Driver Distraction: Other interior distraction7 (4%)→0.0%prior 7
Ran off road - straight6 (3.4%)↓-33.3%prior 9
Other (explain in narrative): Other6 (3.4%)↓-60.0%prior 15
Followed too close5 (2.8%)↓-16.7%prior 6
Exceeded authorized speed4 (2.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather and on dry roads were less frequent in 2023 compared to 2022, with clear-weather incidents falling from 100 to 83 and dry-road incidents decreasing from 95 to 88. Conversely, crashes during snowy conditions increased from 5 to 9. Regarding lighting, collisions in daylight remained nearly identical (73 vs. 74), but crashes on unlit dark roadways decreased from 33 in 2022 to 23 in 2023.

Weather

Clear83 (71.6%)
↓-17.0%prior 100
Cloudy16 (13.8%)
↑60.0%prior 10
Snow9 (7.8%)
↑80.0%prior 5
Rain8 (6.9%)
↓-20.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight74 (63.8%)
↑1.4%prior 73
Dark - roadway not lighted23 (19.8%)
↓-30.3%prior 33
Dark - roadway lighted16 (13.8%)
↑23.1%prior 13
Dusk3 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry88 (75.2%)
↓-7.4%prior 95
Wet12 (10.3%)
↓-29.4%prior 17
Gravel6 (5.1%)
Snow6 (5.1%)
↑20.0%prior 5
Mud, dirt2 (1.7%)
Slush2 (1.7%)
Ice/frost1 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The ranking of vehicle makes involved in crashes shifted year-over-year. While Chevrolet-branded vehicles were most common in 2022 (66 incidents), their involvement decreased to 50 in 2023, allowing Ford to become the most frequent make with 56 incidents, up from 43. The age demographics of persons involved in crashes remained largely consistent, with the 16-20 and 26-34 age groups being highly represented in both years. However, the number of individuals aged 45-54 involved in crashes increased from 33 to 49, while involvement for the 35-44 age group decreased from 53 to 46.

Top Vehicle Makes (249 vehicles)

1
FORD56 (22.5%)
↑30.2%prior 43
2
CHEV43 (17.3%)
↓-14.0%prior 50
3
JEEP19 (7.6%)
↑72.7%prior 11
4
DODG12 (4.8%)
↓-20.0%prior 15
5
GMC10 (4%)
↓-9.1%prior 11
6
TOYT9 (3.6%)
→0.0%prior 9
7
CHRY9 (3.6%)
↑80.0%prior 5
8
BUIC8 (3.2%)
↓-27.3%prior 11
9
CHEVROLET7 (2.8%)
↓-56.3%prior 16
10
DODGE7 (2.8%)
↓-30.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (230 persons with recorded sex)

Male137 (59.6%)
↓-2.8%prior 141
Female93 (40.4%)
↑2.2%prior 91

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 176
  • Total persons involved: 376
  • Total vehicles involved: 249

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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