Yearly Traffic Safety Analysis

296 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Jones County, total traffic crashes increased slightly from 289 in 2020 to 296 in 2021, a rise of 2.4%. While the overall volume of crashes remained relatively stable, the number of fatalities saw a significant year-over-year increase, growing from 4 in 2020 to 7 in 2021. This increase in fatalities occurred alongside a 10.9% rise in total injuries, from 64 to 71.

296

▲ 2.4%was 289

Total Crash Events

7

▲ 75.0%was 4

Persons Killed

71

▲ 10.9%was 64

Persons Injured

7

▲ 75.0%was 4

Fatal Crash Events

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Jones County showed a slight increase in the total number of crashes from 2020 to 2021. Crashes rose by 2.4%, from 289 to 296. More significantly, the severity of crashes worsened, with total fatalities increasing by 75% (from 4 to 7) and total injuries increasing by 10.9% (from 64 to 71) over the same period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

7

Motorists Killed

Prior: 4↑75.0%

2

Cyclists Injured

Prior: 0→%

69

Motorists Injured

Prior: 64↑7.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2021 (60 crashes) and 2020 (54 crashes). The peak hour for crashes shifted slightly, from 9 p.m. in 2020 (24 crashes) to 8 p.m. in 2021 (20 crashes). Notably, crashes occurring on Saturday increased from 41 to 54, while Sunday crashes decreased from 47 to 30.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased from 2020 to 2021. The number of fatal crashes rose from 4 to 7, and the fatal crash rate increased from 1.4% to 2.4% of all crashes. While the count of serious injury crashes decreased from 9 to 6, this was offset by an increase in possible injury crashes, which grew from 19 to 29. Consequently, the proportion of crashes that resulted in no injuries declined from 82.0% in 2020 to 78.7% in 2021.

Outcome by Severity (Crash Events)

Fatal7fatal crashes2.4%
↑75.0%prior 4
Serious Injury6serious injury crashes2%
↓-33.3%prior 9
Minor Injury21minor injury crashes7.1%
↑5.0%prior 20
Possible Injury29possible injury crashes9.8%
↑52.6%prior 19
No Injury233no injury crashes78.7%
↓-1.7%prior 237

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the top contributing factor in both periods, though the count decreased by 10.9% from 137 crashes in 2020 to 122 in 2021. 'Lost Control' remained the second-most cited factor, with its count increasing by 11.5% from 26 to 29 incidents. The third-ranked factor, 'Ran off road - straight,' also saw an increase in count from 13 to 16 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Animal122 (41.2%)↓-10.9%prior 137
Lost Control29 (9.8%)↑11.5%prior 26
Ran off road - straight16 (5.4%)↑23.1%prior 13
FTYROW: From stop sign14 (4.7%)↑16.7%prior 12
Followed too close12 (4.1%)↑50.0%prior 8
Ran off road - left9 (3%)↑50.0%prior 6
Other (explain in narrative): Other9 (3%)↓-18.2%prior 11
Driver Distraction: Other interior distraction6 (2%)↓-25.0%prior 8
Other (explain in narrative): No improper action5 (1.7%)↓-16.7%prior 6
Swerving/Evasive Action5 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions were broadly similar between 2020 and 2021, with most incidents occurring in clear weather (108 vs. 121), during daylight hours (118 vs. 122), and on dry roads (125 vs. 135). There was no significant shift in the proportion of crashes under adverse conditions. However, the absolute number of crashes in dark, unlighted conditions increased from 34 to 39, and crashes on icy or frosty surfaces rose from 10 to 13.

Weather

Clear121 (64.4%)
↑12.0%prior 108
Cloudy37 (19.7%)
↑8.8%prior 34
Rain14 (7.4%)
↑75.0%prior 8
Snow10 (5.3%)
↓-16.7%prior 12
Freezing rain/drizzle3 (1.6%)
↓-40.0%prior 5
Fog, smoke, smog2 (1.1%)
Severe Winds1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight122 (64.6%)
↑3.4%prior 118
Dark - roadway not lighted39 (20.6%)
↑14.7%prior 34
Dark - roadway lighted14 (7.4%)
↑100.0%prior 7
Dusk10 (5.3%)
↓-9.1%prior 11
Dawn4 (2.1%)
↓-20.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry135 (71.8%)
↑8.0%prior 125
Wet24 (12.8%)
↑14.3%prior 21
Ice/frost13 (6.9%)
↑30.0%prior 10
Snow9 (4.8%)
↓-25.0%prior 12
Gravel5 (2.7%)
Other (explain in narrative)1 (0.5%)
Slush1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both years, though both saw a decrease in crash counts; Ford-involved crashes fell from 85 to 67, and Chevrolet from a combined 73 to 69. A notable shift occurred in the age distribution of persons involved in crashes. The 26-34 age group saw its count decrease from 97 to 70, while the 55-64 age group's involvement increased from 56 to 76 persons.

Top Vehicle Makes (403 vehicles)

1
FORD67 (16.6%)
↓-21.2%prior 85
2
CHEV45 (11.2%)
↓-18.2%prior 55
3
CHEVROLET24 (6%)
↑33.3%prior 18
4
GMC23 (5.7%)
↑43.8%prior 16
5
DODG23 (5.7%)
↑43.8%prior 16
6
TOYO23 (5.7%)
↑91.7%prior 12
7
JEEP18 (4.5%)
↑125.0%prior 8
8
DODGE15 (3.7%)
↑25.0%prior 12
9
KIA13 (3.2%)
10
HOND11 (2.7%)
↑37.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (306 persons with recorded sex)

Male173 (56.5%)
↓-22.4%prior 223
Female133 (43.5%)
↓-5.0%prior 140

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 296
  • Total persons involved: 525
  • Total vehicles involved: 403

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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