Yearly Traffic Safety Analysis

211 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Franklin County recorded 211 total crashes, a 27.9% increase from the 165 crashes documented in 2022. The most significant year-over-year change was the occurrence of 3 traffic-related fatalities in 2023, compared to none in the prior year. The total number of people injured also rose by 25%, from 44 in 2022 to 55 in 2023.

211

27.9%was 165

Total Crash Events

3

Persons Killed

55

25.0%was 44

Persons Injured

3

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

Trend Summary

Crash trends in Franklin County showed a notable increase from 2022 to 2023. Total crashes rose by 27.9%, from 165 to 211 incidents. This upward trend was also reflected in crash outcomes, with total injuries increasing by 25% from 44 to 55, and fatalities rising from zero to three.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

3

Motorists Killed

Prior: 0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

52

Motorists Injured

Prior: 4418.2%

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 shifted between the two periods. In 2023, Monday was the most frequent day for crashes with 38 incidents, a change from Thursday being the peak day in 2022 with 32 crashes. The peak hour for collisions also moved later in the afternoon, from 1 p.m. in 2022 (14 crashes) to 3 p.m. in 2023 (18 crashes).

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

Crash severity worsened in 2023, with the county recording 3 fatal crashes, whereas there were none in 2022. Consequently, the fatal crash rate rose from 0 to 1.42 per 100 crashes. While the number of serious injury crashes increased from 5 to 6, their share of total crashes decreased slightly from 3.0% to 2.8%. The count of minor injury crashes fell from 18 to 17, but possible injury crashes increased from 13 to 19.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.4%
Serious Injury6serious injury crashes2.8%
20.0%prior 5
Minor Injury17minor injury crashes8.1%
-5.6%prior 18
Possible Injury19possible injury crashes9%
46.2%prior 13
No Injury166no injury crashes78.7%
28.7%prior 129

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 top contributing factor in both periods, with the count increasing by 46.5% from 43 crashes in 2022 to 63 in 2023. Several other factors saw significant changes in volume; crashes attributed to 'Failure to Yield Right of Way from a stop sign' increased from 2 to 11 incidents, and 'Driver Distraction: Other interior distraction' rose from 5 to 12 incidents. Conversely, crashes related to 'Driving too fast for conditions' decreased notably from 11 incidents in 2022 to just 3 in 2023.

Officer-Reported Primary Contributing Cause

Animal63 (29.9%)46.5%prior 43
Other (explain in narrative): Other17 (8.1%)13.3%prior 15
Lost Control14 (6.6%)40.0%prior 10
Driver Distraction: Other interior distraction12 (5.7%)140.0%prior 5
FTYROW: From stop sign11 (5.2%)
FTYROW: At uncontrolled intersection11 (5.2%)10.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner9 (4.3%)
Ran off road - left9 (4.3%)12.5%prior 8
Ran off road - straight7 (3.3%)-22.2%prior 9
Followed too close5 (2.4%)

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 increased in count, rising from 92 to 115 and 91 to 121, respectively, though their proportion of total crashes remained relatively stable. Despite an overall increase in total incidents, crashes occurring on snow or ice-covered roads decreased from 32 in 2022 to 24 in 2023. Similarly, collisions in dark, unlit conditions fell from 25 to 15 year-over-year.

Weather

Clear115 (71.0%)
25.0%prior 92
Cloudy32 (19.8%)
52.4%prior 21
Snow6 (3.7%)
Rain5 (3.1%)
Severe Winds2 (1.2%)
Other (explain in narrative)1 (0.6%)
Blowing Snow1 (0.6%)
-85.7%prior 7

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

Lighting

Daylight124 (76.1%)
33.3%prior 93
Dark - roadway not lighted15 (9.2%)
-40.0%prior 25
Dark - roadway lighted13 (8.0%)
30.0%prior 10
Dawn5 (3.1%)
Dusk4 (2.5%)
Dark - unknown roadway lighting2 (1.2%)

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

Road Surface

Dry121 (74.7%)
33.0%prior 91
Ice/frost14 (8.6%)
16.7%prior 12
Snow10 (6.2%)
-50.0%prior 20
Wet10 (6.2%)
66.7%prior 6
Gravel7 (4.3%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet leading in both years and showing an increase in counts proportional to the overall rise in crashes. A more significant shift occurred in the age distribution of persons involved in collisions. The number of individuals in the 35-44 age group more than doubled from 34 to 71, and those aged 65 and older also saw their involvement more than double from 33 to 67. Conversely, the 21-25 age group saw a decrease in involvement, from 47 individuals in 2022 to 32 in 2023.

Top Vehicle Makes (321 vehicles)

1
FORD68 (21.2%)
54.5%prior 44
2
CHEV51 (15.9%)
45.7%prior 35
3
CHEVROLET15 (4.7%)
0.0%prior 15
4
TOYT13 (4%)
5
GMC12 (3.7%)
33.3%prior 9
6
NISS11 (3.4%)
7
DODGE11 (3.4%)
-8.3%prior 12
8
CHRY10 (3.1%)
42.9%prior 7
9
DODG9 (2.8%)
50.0%prior 6
10
JEEP8 (2.5%)
-20.0%prior 10

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

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

Sex Distribution (292 persons with recorded sex)

Male174 (59.6%)
26.1%prior 138
Female118 (40.4%)
29.7%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: 211
  • Total persons involved: 447
  • Total vehicles involved: 321

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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