Yearly Traffic Safety Analysis

221 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Madison County recorded 221 total crashes, an 8.3% increase from the 204 crashes documented in 2020. Despite the rise in total incidents, the number of fatalities saw a substantial decrease, falling from 7 in the prior year to 1 in the current period.

221

▲ 8.3%was 204

Total Crash Events

1

▼ -85.7%was 7

Persons Killed

56

Persons Injured

1

▼ -85.7%was 7

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Madison County increased by 8.3% from 2020 to 2021, rising from 204 to 221 incidents. However, this increase in crash volume did not correspond to a rise in harm, as total injuries remained unchanged at 56, and total fatalities decreased significantly from 7 to 1.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 6↓-83.3%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 1→0.0%

54

Motorists Injured

Prior: 55↓-1.8%

1

Other Injured

Prior: 0→%

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 timing of crashes shifted between the two periods. In 2021, the peak days for crashes were Friday and Saturday, each with 38 incidents, a change from 2020 when Wednesday was the peak day with 35 crashes. Similarly, the most frequent crash time moved from the 8 a.m. hour in 2020 (18 crashes) to the 5 p.m. hour in 2021 (21 crashes).

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 decreased notably from 2020 to 2021. The number of fatal crashes fell from 7 to 1, and serious injury crashes dropped from 7 to 2. Consequently, the share of fatal crashes decreased from 3.4% to 0.5% of all incidents. While minor injury crashes also saw a proportional decrease, crashes resulting in possible injuries more than doubled in count from 11 to 29, representing 13.1% of all crashes in 2021 compared to 5.4% in 2020.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-85.7%prior 7
Serious Injury2serious injury crashes0.9%
↓-71.4%prior 7
Minor Injury24minor injury crashes10.9%
↓-20.0%prior 30
Possible Injury29possible injury crashes13.1%
↑163.6%prior 11
No Injury165no injury crashes74.7%
↑10.7%prior 149

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 involving an animal remained the leading contributing factor in both periods, with the count increasing by 50% from 54 crashes in 2020 to 81 in 2021. Consequently, its share of all crashes grew from 26.5% to 36.7%. Conversely, crashes attributed to 'Failure to Yield Right of Way from a stop sign' decreased significantly, falling from 15 incidents in 2020 to 6 in 2021. The count for 'Lost Control' also saw a slight decrease from 17 to 14 crashes.

Officer-Reported Primary Contributing Cause

Animal81 (36.7%)↑50.0%prior 54
Lost Control14 (6.3%)↓-17.6%prior 17
Followed too close13 (5.9%)→0.0%prior 13
Ran off road - left11 (5%)↑10.0%prior 10
Other (explain in narrative): Other9 (4.1%)
FTYROW: From yield sign8 (3.6%)
Ran off road - straight7 (3.2%)↓-30.0%prior 10
Driving too fast for conditions7 (3.2%)↑16.7%prior 6
Driver Distraction: Other interior distraction6 (2.7%)→0.0%prior 6
FTYROW: From stop sign6 (2.7%)↓-60.0%prior 15

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

Road & Environmental Conditions

Crashes on dry roads increased from 115 to 131, representing a slightly larger share of total incidents in 2021 (59.3%) compared to 2020 (56.4%). Notably, crashes occurring on icy or frosty surfaces decreased from 18 in the prior year to 7 in the current year. The distribution of crashes by lighting conditions remained relatively stable, with daylight crashes accounting for 49.3% of incidents in 2021 versus 52.5% in 2020.

Weather

Clear136 (76.0%)
↑17.2%prior 116
Cloudy24 (13.4%)
↓-22.6%prior 31
Rain6 (3.4%)
Snow5 (2.8%)
↓-16.7%prior 6
Blowing Snow3 (1.7%)
Fog, smoke, smog3 (1.7%)
↓-40.0%prior 5
Severe Winds1 (0.6%)
Freezing rain/drizzle1 (0.6%)

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

Lighting

Daylight109 (60.6%)
↑1.9%prior 107
Dark - roadway not lighted51 (28.3%)
↑18.6%prior 43
Dawn7 (3.9%)
↓-22.2%prior 9
Dusk6 (3.3%)
Dark - roadway lighted5 (2.8%)
→0.0%prior 5
Dark - unknown roadway lighting2 (1.1%)

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

Road Surface

Dry131 (73.2%)
↑13.9%prior 115
Wet15 (8.4%)
↑36.4%prior 11
Gravel12 (6.7%)
↑50.0%prior 8
Snow12 (6.7%)
↑9.1%prior 11
Ice/frost7 (3.9%)
↓-61.1%prior 18
Other (explain in narrative)1 (0.6%)
Mud, dirt1 (0.6%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford and Chevrolet models being the most common in both 2021 and 2020. In terms of demographics, the 26-34 age group was the most represented group among persons involved in crashes in 2021, with 68 individuals, up from 60 in the prior year. The total number of persons involved in crashes decreased from 414 to 390, despite an increase in the total number of crashes.

Top Vehicle Makes (316 vehicles)

1
FORD52 (16.5%)
↓-3.7%prior 54
2
CHEV52 (16.5%)
↓-3.7%prior 54
3
CHEVROLET35 (11.1%)
↑29.6%prior 27
4
JEEP12 (3.8%)
↓-29.4%prior 17
5
DODG12 (3.8%)
↓-14.3%prior 14
6
DODGE11 (3.5%)
↑37.5%prior 8
7
TOYT9 (2.8%)
↑12.5%prior 8
8
GMC9 (2.8%)
↑12.5%prior 8
9
BUIC7 (2.2%)
10
HONDA7 (2.2%)

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 (255 persons with recorded sex)

Male154 (60.4%)
↓-11.5%prior 174
Female101 (39.6%)
↓-3.8%prior 105

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: 221
  • Total persons involved: 390
  • Total vehicles involved: 316

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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