Yearly Traffic Safety Analysis

117 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Howard County, total crashes decreased slightly from 120 in 2022 to 117 in 2023, a 2.5% reduction. The most significant year-over-year change was the elimination of traffic fatalities, which fell from two in the prior period to zero in the current period. Concurrently, the total number of people injured in crashes increased from 38 to 45.

117

▼ -2.5%was 120

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

45

▲ 18.4%was 38

Persons Injured

0

▼ -100.0%was 2

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

Trend Summary

The overall trend in Howard County shows a slight decrease in total crashes, with 117 incidents in 2023 compared to 120 in 2022. While the number of fatal crashes dropped to zero from two the previous year, the number of persons injured increased by 18.4%, rising from 38 to 45.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 2↓-100.0%

45

Motorists Injured

Prior: 38↑18.4%

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 temporal patterns of crashes in Howard County showed some shifts between 2022 and 2023. While Friday remained the peak day for crashes in both periods (27 in 2022, 24 in 2023), the peak hour moved from 5 p.m. in 2022 (12 crashes) to 9 p.m. in 2023 (13 crashes). Crash counts on Saturdays saw a notable decrease from 22 to 12, while incidents on Tuesdays and Wednesdays increased.

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 in Howard County improved with the elimination of fatal incidents, which dropped from 2 in 2022 to 0 in 2023. However, the proportion of crashes involving injuries increased. The share of minor injury crashes rose from 8.3% to 15.4% of all incidents, and serious injury crashes increased slightly from 4.2% to 5.1%. The share of no-injury crashes decreased from 71.7% in 2022 to 68.4% in 2023.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes5.1%
↑20.0%prior 5
Minor Injury18minor injury crashes15.4%
↑80.0%prior 10
Possible Injury13possible injury crashes11.1%
↓-23.5%prior 17
No Injury80no injury crashes68.4%
↓-7.0%prior 86

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

In both 2022 and 2023, collisions involving an animal were the leading contributing factor, though the count decreased from 44 to 41. The second-ranked factor shifted year-over-year; 'Lost Control' incidents dropped in count from 12 to 4, while crashes attributed to 'Failure to Yield Right of Way from a stop sign' increased from 8 to 13 incidents, becoming the second-most common factor in 2023. The count for crashes attributed to 'Ran off road - straight' also doubled from 4 to 8.

Officer-Reported Primary Contributing Cause

Animal41 (35%)↓-6.8%prior 44
FTYROW: From stop sign13 (11.1%)↑62.5%prior 8
Ran off road - straight8 (6.8%)
Other (explain in narrative): Other8 (6.8%)→0.0%prior 8
Lost Control4 (3.4%)↓-66.7%prior 12
Ran Stop Sign4 (3.4%)
Improper Backing3 (2.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (2.6%)
Followed too close3 (2.6%)
Driving too fast for conditions3 (2.6%)↓-40.0%prior 5

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

Road & Environmental Conditions

The conditions under which crashes occurred remained broadly similar year-over-year, with most incidents happening in daylight and on dry roads. In 2023, 52.1% of crashes occurred on dry surfaces, up from a 44.2% share in 2022. Correspondingly, crashes on adverse road surfaces like snow and ice saw a change, with the count of crashes on snowy roads falling from 12 to 3. The proportion of crashes in clear weather was slightly lower in 2023 (44.4%) compared to 2022 (48.3%).

Weather

Clear52 (59.1%)
↓-10.3%prior 58
Cloudy18 (20.5%)
↑12.5%prior 16
Rain6 (6.8%)
Blowing Snow3 (3.4%)
Fog, smoke, smog3 (3.4%)
Snow3 (3.4%)
↓-57.1%prior 7
Other (explain in narrative)1 (1.1%)
Severe Winds1 (1.1%)
Sleet, hail1 (1.1%)

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

Lighting

Daylight55 (61.8%)
↑7.8%prior 51
Dark - roadway not lighted27 (30.3%)
↑17.4%prior 23
Dawn3 (3.4%)
Dark - roadway lighted2 (2.2%)
↓-60.0%prior 5
Dusk2 (2.2%)
↓-60.0%prior 5

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

Road Surface

Dry61 (69.3%)
↑15.1%prior 53
Wet10 (11.4%)
↑25.0%prior 8
Ice/frost7 (8.0%)
↑16.7%prior 6
Gravel4 (4.5%)
↓-60.0%prior 10
Snow3 (3.4%)
↓-75.0%prior 12
Slush2 (2.3%)
Mud, dirt1 (1.1%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both periods, though their numbers declined. The count of Chevrolet vehicles in crashes fell from 44 in 2022 to 33 in 2023, while Ford vehicles decreased from 34 to 32. An analysis of persons involved shows a notable increase in the 26-34 age group, which grew from 38 individuals in 2022 to 53 in 2023. The involvement of other age groups remained comparatively stable year-over-year.

Top Vehicle Makes (163 vehicles)

1
FORD32 (19.6%)
↓-5.9%prior 34
2
CHEV21 (12.9%)
↓-41.7%prior 36
3
CHEVROLET12 (7.4%)
↑50.0%prior 8
4
DODG11 (6.7%)
↑83.3%prior 6
5
JEEP8 (4.9%)
↑14.3%prior 7
6
GMC8 (4.9%)
7
BUIC6 (3.7%)
↓-33.3%prior 9
8
RAM5 (3.1%)
9
TOYT5 (3.1%)
10
DODGE4 (2.5%)

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

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

Sex Distribution (157 persons with recorded sex)

Male99 (63.1%)
↑3.1%prior 96
Female58 (36.9%)
↓-6.5%prior 62

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 10, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 117
  • Total persons involved: 242
  • Total vehicles involved: 163

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 10, 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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