Monthly Traffic Safety Analysis

3,940 CRASHES IN
IOWA, IA
JULY 2020

All metrics benchmarked againstJuly 2019

In July 2020, there were 3,940 crashes, a 9.6% decrease from the 4,357 crashes recorded in July 2019. Despite the overall reduction in collisions, the number of fatalities increased significantly, rising from 32 to 44 year-over-year. This indicates that while crashes were less frequent, they were more severe.

3,940

▼ -9.6%was 4,357

Total Crash Events

44

▲ 37.5%was 32

Persons Killed

1,504

▼ -5.6%was 1,593

Persons Injured

39

▲ 39.3%was 28

Fatal Crash Events

Note: "Persons Killed" (44) counts individual fatalities across all crash events. "Fatal" in the severity table below (39) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic collisions showed a downward trend in July 2020 compared to the previous year, with total crashes decreasing by 9.6% from 4,357 to 3,940. The number of injuries also saw a slight decline of 5.6%, from 1,593 to 1,504. However, this was contrasted by a sharp 37.5% increase in fatalities, which rose from 32 to 44.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 1↑200.0%

2

Cyclists Killed

Prior: 1↑100.0%

39

Motorists Killed

Prior: 30↑30.0%

0

Other Killed

Prior: 0→0.0%

21

Pedestrians Injured

Prior: 26↓-19.2%

27

Cyclists Injured

Prior: 47↓-42.6%

1,454

Motorists Injured

Prior: 1,518↓-4.2%

2

Other Injured

Prior: 2→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In July 2020, the peak day for crashes was Friday with 712 incidents, a change from July 2019 when Monday was the peak day with 770 crashes. The peak hour for collisions also shifted slightly, moving from the 4 p.m. hour (374 crashes) in the prior year to the 5 p.m. hour (305 crashes) in the current period.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened in July 2020 compared to the same month in 2019. The number of fatal crashes increased from 28 to 39, and their share of all crashes rose from 0.6% to 1.0%. While the share of serious injury crashes decreased slightly from 2.8% to 2.6%, the proportion of crashes resulting in any form of injury (possible, minor, serious, or fatal) increased from 31.2% to 33.0% of all incidents.

Severity is per crash event (most severe injury). 39 fatal crash events resulted in 44 persons killed.

Outcome by Severity (Crash Events)

Fatal39fatal crashes1%
↑39.3%prior 28
Serious Injury101serious injury crashes2.6%
↓-18.5%prior 124
Minor Injury465minor injury crashes11.8%
↓-2.3%prior 476
Possible Injury693possible injury crashes17.6%
↓-5.7%prior 735
No Injury2,642no injury crashes67.1%
↓-11.8%prior 2,994

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent, though their counts changed year-over-year. Collisions involving an 'Animal' were the top factor in both periods but decreased in count by 15.6% from 527 to 445 incidents. 'Followed too close' remained the second-most cited factor, with its count falling by 16.7% from 496 to 413. Conversely, crashes attributed to 'Ran Stop Sign' increased in count by 16.5%, rising from 121 to 141.

Officer-Reported Primary Contributing Cause

Animal445 (11.3%)↓-15.6%prior 527
Followed too close413 (10.5%)↓-16.7%prior 496
Lost Control227 (5.8%)↓-5.8%prior 241
Other (explain in narrative): Other219 (5.6%)↓-26.8%prior 299
Ran off road - left217 (5.5%)↓-3.6%prior 225
FTYROW: From stop sign190 (4.8%)↓-14.4%prior 222
FTYROW: Making left turn164 (4.2%)↓-16.3%prior 196
Ran Stop Sign141 (3.6%)↑16.5%prior 121
Ran off road - straight140 (3.6%)↑12.0%prior 125
Operating vehicle in an reckless, erratic, careless, negligent manner136 (3.5%)↑21.4%prior 112

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely stable year-over-year, with ideal conditions prevailing in both periods. The vast majority of collisions in both July 2020 and July 2019 occurred in 'Clear' weather (74.9% and 73.5% of crashes, respectively) and during 'Daylight' hours (71.8% and 72.7%). Similarly, 'Dry' road surfaces were reported in over 82% of crashes in both periods, indicating no significant shift in the prevalence of adverse environmental conditions.

Weather

Clear2,951 (82.0%)
↓-7.9%prior 3,204
Cloudy476 (13.2%)
↓-12.0%prior 541
Rain149 (4.1%)
↓-10.2%prior 166
Fog, smoke, smog12 (0.3%)
Other (explain in narrative)4 (0.1%)
Blowing sand, soil, dirt2 (0.1%)
Freezing rain/drizzle2 (0.1%)
Severe Winds1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Weather condition at time of crash

Lighting

Daylight2,830 (78.4%)
↓-10.6%prior 3,166
Dark - roadway lighted339 (9.4%)
↓-2.3%prior 347
Dark - roadway not lighted289 (8.0%)
↑5.9%prior 273
Dusk83 (2.3%)
↓-4.6%prior 87
Dawn57 (1.6%)
↑9.6%prior 52
Dark - unknown roadway lighting12 (0.3%)
↑9.1%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Lighting condition field

Road Surface

Dry3,260 (90.5%)
↓-8.9%prior 3,579
Wet233 (6.5%)
↓-8.3%prior 254
Gravel97 (2.7%)
↑21.3%prior 80
Mud, dirt7 (0.2%)
Water (standing or moving)2 (0.1%)
Sand1 (0.0%)
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet vehicles being the most frequent in both periods. The number of Ford vehicles in crashes decreased from 1,142 to 1,071, and Chevrolet-branded vehicles also saw a reduction in involvement from 1,454 to 1,361. An analysis of person demographics shows a slight proportional increase in the 16-20 age group's involvement, from 11.7% of all persons in the prior year to 13.0% in the current period.

Top Vehicle Makes (6,751 vehicles)

1
FORD1,071 (15.9%)
↓-6.2%prior 1,142
2
CHEV820 (12.1%)
↓-14.8%prior 963
3
CHEVROLET541 (8%)
↑10.2%prior 491
4
TOYT250 (3.7%)
↓-23.5%prior 327
5
DODG237 (3.5%)
↓-25.7%prior 319
6
NR232 (3.4%)
↑17.2%prior 198
7
JEEP224 (3.3%)
↓-5.1%prior 236
8
GMC219 (3.2%)
↓-13.8%prior 254
9
HOND213 (3.2%)
↓-9.4%prior 235
10
DODGE200 (3%)
↑1.0%prior 198

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · Vehicle unit records

1,324 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,013 persons with recorded sex)

Male3,588 (59.7%)
↓-9.2%prior 3,950
Female2,425 (40.3%)
↓-15.5%prior 2,870

Source: Iowa Crash Data · ArcGIS Open Data · 2020-07-01 to 2020-07-31 · 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: 2020-07-01 through 2020-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-07-01 through 2020-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,940
  • Total persons involved: 9,290
  • Total vehicles involved: 6,751

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: July 2020." Published September 9, 2026. Reporting period: 2020-07-01 to 2020-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-2020-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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