Yearly Traffic Safety Analysis

211 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Appanoose County, a total of 211 crashes were recorded in 2021, a slight increase of 1.4% from the 208 crashes in 2020. Despite the small rise in total incidents, there was a notable year-over-year improvement in crash outcomes. The number of people injured decreased by 24.3%, from 74 in 2020 to 56 in 2021, and fatalities fell from two to one.

211

▲ 1.4%was 208

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

56

▼ -24.3%was 74

Persons Injured

1

▼ -50.0%was 2

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 crash trends in Appanoose County were relatively stable, with total incidents increasing by just three, from 208 in 2020 to 211 in 2021. However, the severity of these crashes decreased, as evidenced by a 50% reduction in fatalities (from 2 to 1) and a 24.3% drop in total injuries (from 74 to 56) over the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

3

Pedestrians Injured

Prior: 3→0.0%

1

Cyclists Injured

Prior: 1→0.0%

52

Motorists Injured

Prior: 70↓-25.7%

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 showed some shifts between the two years. While Thursday remained the peak day for crashes in both 2021 and 2020 with 38 incidents each year, the peak time of day changed. In 2021, the most crashes occurred at 3 p.m. (17 incidents), whereas in 2020 the peak was during the evening commute, with 20 crashes each at 5 p.m. and 6 p.m.

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

The severity of crashes decreased from 2020 to 2021. The number of fatal crashes was halved from two to one, and total injuries fell from 74 to 56. While the count of serious injury crashes increased from 8 to 12, minor injury crashes saw a significant drop from 26 to 16. Consequently, crashes resulting in no injury increased from 154 in 2020 to 160 in 2021, making up 75.8% of all incidents compared to 74% in the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-50.0%prior 2
Serious Injury12serious injury crashes5.7%
↑50.0%prior 8
Minor Injury16minor injury crashes7.6%
↓-38.5%prior 26
Possible Injury22possible injury crashes10.4%
↑22.2%prior 18
No Injury160no injury crashes75.8%
↑3.9%prior 154

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 animals remained the top contributing factor in both periods, though the count decreased from 77 crashes in 2020 to 68 in 2021. The rankings of other major factors shifted; crashes attributed to a driver losing control fell from 19 to 11, while incidents of running off the road increased, with those going straight rising from 8 to 16 and those going left increasing from 3 to 15. Crashes involving failure to yield from a stop sign also increased, from 6 in 2020 to 11 in 2021.

Officer-Reported Primary Contributing Cause

Animal68 (32.2%)↓-11.7%prior 77
Ran off road - straight16 (7.6%)↑100.0%prior 8
Ran off road - left15 (7.1%)
Followed too close11 (5.2%)↑22.2%prior 9
FTYROW: From stop sign11 (5.2%)↑83.3%prior 6
Lost Control11 (5.2%)↓-42.1%prior 19
Driver Distraction: Other interior distraction8 (3.8%)↑33.3%prior 6
Other (explain in narrative): Other8 (3.8%)↓-33.3%prior 12
Ran Stop Sign7 (3.3%)→0.0%prior 7
FTYROW: From parked position4 (1.9%)

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

Road & Environmental Conditions

Year-over-year, there was a shift in the conditions under which crashes occurred. In 2021, more crashes happened in clear weather (124) and on dry roads (119) compared to 2020 (93 and 109, respectively). Conversely, incidents during adverse conditions decreased, with crashes on wet roads falling from 20 to 6 and crashes in cloudy weather dropping from 36 to 16. Crashes on snowy roads saw an increase from 3 in 2020 to 10 in 2021.

Weather

Clear124 (81.0%)
↑33.3%prior 93
Cloudy16 (10.5%)
↓-55.6%prior 36
Snow5 (3.3%)
Rain4 (2.6%)
↓-50.0%prior 8
Blowing Snow2 (1.3%)
Fog, smoke, smog2 (1.3%)

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

Lighting

Daylight99 (64.3%)
↑11.2%prior 89
Dark - roadway not lighted28 (18.2%)
↑3.7%prior 27
Dark - roadway lighted18 (11.7%)
→0.0%prior 18
Dawn5 (3.2%)
Dusk3 (1.9%)
↓-40.0%prior 5
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry119 (77.8%)
↑9.2%prior 109
Snow10 (6.5%)
Gravel9 (5.9%)
Ice/frost7 (4.6%)
→0.0%prior 7
Wet6 (3.9%)
↓-70.0%prior 20
Slush1 (0.7%)
Mud, dirt1 (0.7%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent year-over-year, with Chevrolet, Ford, and Dodge vehicles being the most frequent in both 2021 and 2020. There was a decrease in the total number of people involved in crashes from 456 to 388. Notably, the number of individuals in the 16-20 age group involved in crashes fell from 70 to 58, and the 45-54 age group saw a reduction from 78 to 53.

Top Vehicle Makes (304 vehicles)

1
FORD49 (16.1%)
↓-9.3%prior 54
2
CHEV45 (14.8%)
↑2.3%prior 44
3
CHEVROLET28 (9.2%)
↑16.7%prior 24
4
DODG19 (6.3%)
→0.0%prior 19
5
TOYT16 (5.3%)
↑60.0%prior 10
6
JEEP15 (4.9%)
↓-6.3%prior 16
7
GMC13 (4.3%)
↑44.4%prior 9
8
DODGE10 (3.3%)
↑66.7%prior 6
9
PONT6 (2%)
10
BUIC6 (2%)
↑20.0%prior 5

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 (239 persons with recorded sex)

Male133 (55.6%)
↓-23.1%prior 173
Female106 (44.4%)
↑11.6%prior 95

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: 211
  • Total persons involved: 388
  • Total vehicles involved: 304

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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