Yearly Traffic Safety Analysis

522 CRASHES IN
IOWA, IA
2015

In 2015, Marion County recorded 522 traffic crashes, resulting in 3 fatalities and 160 injuries. These incidents involved 943 people and 777 vehicles. The single most prominent contributing factor identified in crash reports was collisions with animals, which accounted for 171 incidents, representing 32.8% of all crashes in the county for the year.

522

Total Crash Events

3

Persons Killed

160

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Motorists accounted for all 3 fatalities and the vast majority of injuries, with 152 motorists injured in 2015. While no fatalities were recorded for vulnerable road users, 6 cyclists and 1 pedestrian sustained injuries in crashes. An additional injury was recorded for a person classified as 'other'.

0

Pedestrians Killed

0

Cyclists Killed

3

Motorists Killed

0

Other Killed

1

Pedestrians Injured

6

Cyclists Injured

152

Motorists Injured

1

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency in Marion County peaked on Fridays, which saw 97 incidents, and during the 5 p.m. hour, with 45 crashes. Analysis of lighting conditions shows that 254 crashes occurred in daylight. In contrast, a total of 124 crashes were recorded during periods of darkness, dusk, or dawn, with 54 of those happening on unlit roadways.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 522 total crashes, 387 incidents (74.1%) resulted in no injuries, involving only property damage. The remaining crashes involved injuries of varying severity: 17 were classified as serious injury crashes, 45 as minor injury, and 70 as possible injury. There were 3 fatal crashes recorded, which resulted in a total of 3 fatalities.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
Serious Injury17serious injury crashes3.3%
Minor Injury45minor injury crashes8.6%
Possible Injury70possible injury crashes13.4%
No Injury387no injury crashes74.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor cited in crashes was an animal in the roadway, accounting for 171 incidents or 32.8% of the total. Following this, failure to yield the right-of-way from a stop sign was noted in 39 crashes (7.5%). Other significant factors included drivers losing control of their vehicle (32 crashes) and reckless or erratic driving (23 crashes).

Officer-Reported Primary Contributing Cause

Animal171 (32.8%)
FTYROW: From stop sign39 (7.5%)
Other (explain in narrative): Other36 (6.9%)
Lost Control32 (6.1%)
Operating vehicle in an reckless, erratic, careless, negligent manner23 (4.4%)
Driving too fast for conditions20 (3.8%)
Followed too close19 (3.6%)
Ran off road - left18 (3.4%)
Ran off road - straight15 (2.9%)
FTYROW: From driveway12 (2.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A substantial portion of crashes happened under favorable conditions, with 288 incidents occurring on dry roads and 268 in clear weather. Daylight conditions were present for 254 crashes. Adverse conditions were less frequent, with 35 crashes on wet roads, 22 on snow-covered roads, and 20 during rainfall.

Weather

Clear268 (70.9%)
Cloudy65 (17.2%)
Rain20 (5.3%)
Snow12 (3.2%)
Fog, smoke, smog9 (2.4%)
Blowing Snow2 (0.5%)
Freezing rain/drizzle1 (0.3%)
Blowing sand, soil, dirt1 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight254 (67.2%)
Dark - roadway not lighted54 (14.3%)
Dark - roadway lighted39 (10.3%)
Dusk17 (4.5%)
Dawn11 (2.9%)
Dark - unknown roadway lighting3 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry288 (76.2%)
Wet35 (9.3%)
Snow22 (5.8%)
Ice/frost15 (4.0%)
Gravel14 (3.7%)
Slush2 (0.5%)
Mud, dirt2 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Among the 943 people involved in crashes, the 26-34 age group was the most represented with 142 individuals, followed closely by the 16-20 age group with 138 individuals. An analysis of the 777 vehicles involved shows that Chevrolet (174 vehicles), Ford (141 vehicles), and Dodge (65 vehicles) were the most frequently recorded makes in crash incidents.

Top Vehicle Makes (777 vehicles)

1
FORD141 (18.1%)
2
CHEV97 (12.5%)
3
CHEVROLET77 (9.9%)
4
DODG42 (5.4%)
5
GMC29 (3.7%)
6
PONT27 (3.5%)
7
TOYT25 (3.2%)
8
DODGE23 (3%)
9
TOYOTA22 (2.8%)
10
HOND19 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

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

Sex Distribution (719 persons with recorded sex)

Male391 (54.4%)
Female328 (45.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most frequently cited major cause of crashes was an animal in the roadway, listed in 171 reports. Failure to yield the right-of-way from a stop sign was the second-leading cause, contributing to 39 crashes. Other primary causes included drivers losing control (32 crashes), reckless or erratic operation (23 crashes), and driving too fast for conditions (20 crashes).

Major Cause

1
Animal171 (33.7%)
2
FTYROW: From stop sign39 (7.7%)
3
Other (explain in narrative): Other36 (7.1%)
4
Lost Control32 (6.3%)
5
Operating vehicle in an reckless, erratic, careless, negligent manner23 (4.5%)
6
Driving too fast for conditions20 (3.9%)
7
Followed too close19 (3.7%)
8
Ran off road - left18 (3.6%)
9
Ran off road - straight15 (3%)

Showing top 9 of 44 reported. 35 additional (134 total) not shown: FTYROW: From driveway, Improper Backing, FTYROW: From parked position, FTYROW: Making left turn, Driver Distraction: Other interior distraction, Ran off road - right, Other (explain in narrative): No improper action, Ran Traffic Signal, Ran Stop Sign, FTYROW: From yield sign, Other (explain in narrative): Vision obstructed, Driver Distraction: Exterior distraction, Swerving/Evasive Action, Improper or erratic lane changing, Passing: Other passing (explain in narrative), Failed to keep in proper lane, Driver Distraction: Manual operation of an electronic communication device, FTYROW: Other (explain in narrative), Crossed centerline (undivided), Driver Distraction: Reaching for object(s)/fallen object(s), Operator inexperience, Aggressive driving/road rage, Exceeded authorized speed, Driver Distraction: Inattentive/lost in thought, Made improper turn, Cargo/equipment loss or shift, Driver Distraction: Unrestrained animal, FTYROW: At uncontrolled intersection, Driver Distraction: Passenger, FTYROW: To pedestrian, Illegally Parked/Unattended, Other (explain in narrative): Getting off/out of vehicle, Passing: On wrong side, Traveling wrong way or on wrong side of road, Driving less than the posted speed limit.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, which occurred in 206 crashes. The second-most-common event was a collision with an animal, recorded in 170 incidents. Other notable events included overturns or rollovers in 26 crashes and collisions with a ditch in 23 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic206 (39.5%)
2
Collision with: Animal170 (32.6%)
3
Non-collision events: Overturn/rollover26 (5%)
4
Collision with fixed object: Ditch23 (4.4%)
5
Collision with: Parked motor vehicle19 (3.6%)
6
Collision with: Re-entering roadway11 (2.1%)
7
Collision with fixed object: Utility pole/light support9 (1.7%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)7 (1.3%)
9
Other (explain in narrative)6 (1.2%)

Showing top 9 of 31 reported. 22 additional (44 total) not shown: Collision with fixed object: Traffic sign support, Non-collision events: Other non-collision (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Tree, Collision with fixed object: Mailbox, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Embankment, Collision with fixed object: Curb/island/raised median, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Vehicle went airborne, Collision with fixed object: Fire hydrant, Collision with fixed object: Snow bank, Collision with fixed object: Building, Miscellaneous events: Hit and run, Non-collision events: Jackknife, Collision with fixed object: Fence, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Traffic signal support, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Culvert/pipe opening.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

Analysis of crash locations shows that more incidents occurred at non-junction segments of the roadway than at intersections. Out of crashes with available data, 201 took place at a non-junction location, and an additional 28 were related to driveway access. In contrast, 79 crashes occurred at four-way intersections and 39 at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature201 (53.2%)
2
Intersection: Four-way intersection79 (20.9%)
3
Intersection: T-intersection39 (10.3%)
4
Non-intersection: Driveway access (related, not in)20 (5.3%)
5
Non-intersection: Driveway access (within)8 (2.1%)
6
Non-intersection: Other non-intersection (explain in narrative)8 (2.1%)
7
Intersection: Y-intersection4 (1.1%)
8
Intersection: Intersection with ramp3 (0.8%)
9
Interchange-related: Off-ramp2 (0.5%)

Showing top 9 of 18 reported. 9 additional (14 total) not shown: Interchange-related: Off-ramp, diverge area, Interchange-related: On-ramp, Intersection: Other intersection (explain in narrative), Non-intersection: Alley, Non-intersection: Crossover-related, Intersection: Roundabout, Interchange-related: Other interchange (explain in narrative), Non-intersection: Railroad grade crossing, Interchange-related: On-ramp merge area.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 383 of the 777 vehicles. Light trucks and pickups were the next most frequent with 147 vehicles, followed by sport utility vehicles (SUVs) with 137. Commercial tractor-trailers were involved in 14 crashes, and motorcycles were involved in 10.

Vehicle Type

"Other" combines 8 smaller categories (22 records): Cargo/panel van (7), Single-unit truck (>= 3 axles) (6), Passenger van (seats 9-15) (2), Other bus (seats > 15) (2), Farm tractor (2), Motor home/recreational vehicle (1), Golf cart (1), All-terrain vehicle (ATV) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

The majority of crashes occurred where no traffic controls were present, with this situation noted in 453 instances. Where traffic controls were in place, stop signs were the most common, present at the scene of 92 crashes. Traffic signals were a factor in 51 crashes.

Traffic Control Device

"Other" combines 1 smaller categories (2 records): Warning sign (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most frequent area of impact, recorded as the most damaged area for 172 vehicles. This suggests a high number of frontal collisions. The rear of the vehicle was the primary damage area in 75 instances, indicative of rear-end collisions, while side impacts were also common, with 38 vehicles damaged on the driver's side middle and 34 on the passenger's side middle.

Most Damaged Area

"Other" combines 9 smaller categories (177 records): Rear - driver side corner (30), Passenger side - front (29), Passenger side - rear (29), Driver side - rear (25), Top (25), Rear - passenger side corner (23), Other (explain in narrative) (11), Non-collision/no damage (3), Undercarriage (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

A total of 11 crashes, or 2.1% of all incidents, were recorded as involving an impaired driver. Of these, alcohol was a factor in 9 crashes, drugs were a factor in 1 crash, and a combination of alcohol and drugs was noted in 1 crash. These figures represent a minimum, as impairment is often under-reported.

Crashes by City

Within Marion County, the city of Pella experienced the highest number of crashes, with 143 incidents reported in 2015. The city of Knoxville had the second-highest total with 87 crashes. Following these, Pleasantville recorded 24 crashes.

Crashes by City

1
PELLA143 (55%)
2
KNOXVILLE87 (33.5%)
3
PLEASANTVILLE24 (9.2%)
4
HAMILTON2 (0.8%)
5
SWAN1 (0.4%)
6
MARYSVILLE1 (0.4%)
7
MELCHER-DALLAS1 (0.4%)
8
BUSSEY1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

Crashes predominantly occurred on paved roadways, which accounted for 485 incidents. A smaller but notable number of crashes, 33 in total, took place on unpaved surfaces such as gravel or dirt roads. This represents 6.4% of the crashes where road surface type was specified.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

Among the small number of crashes where a roadway factor was cited as a contributor, adverse surface conditions such as wet or icy roads were the most common, noted in 30 incidents. Other factors like roadway debris or a slippery or worn surface were each cited in 3 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)30 (75%)
2
Slippery, loose or worn surface3 (7.5%)
3
Debris3 (7.5%)
4
Traffic backup, prior crash1 (2.5%)
5
Shoulders (none, low, soft, high)1 (2.5%)
6
Non-highway work1 (2.5%)
7
Ruts/holes/bumps1 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Driver Condition

In cases where a driver's condition was noted as something other than 'apparently normal,' the most frequent citation was being under the influence of alcohol, recorded for 12 drivers. The next most common condition was being asleep or fatigued, which was noted for 6 drivers. These conditions are recorded for a minority of drivers involved in crashes.

Driver Condition

1
Under the influence of alcohol12 (44.4%)
2
Asleep/fatigued6 (22.2%)
3
Emotional (e.g. depressed, angry)4 (14.8%)
4
Medical condition (seizure, reaction)2 (7.4%)
5
Paraplegic/wheelchair restricted1 (3.7%)
6
Illness/fainted1 (3.7%)
7
Under the influence of drugs/meds1 (3.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most common estimated property damage cost was in the $1,500 to $7,500 range, which applied to 396 crashes. A total of 9 crashes, representing 1.7% of the total, were estimated to have damage costs exceeding $25,000. Another 99 crashes fell into the $7,500 to $25,000 damage category.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events were the most frequent manner of collision, accounting for 225 crashes or 43.1% of the total. Among multi-vehicle crashes, broadside (front-to-side) collisions were most common, occurring in 80 incidents (15.3%), closely followed by rear-end collisions, which accounted for 79 incidents (15.1%).

Manner of Collision

"Other" combines 3 smaller categories (15 records): Sideswipe, opposite direction (6), Head-on (front to front) (6), Rear to rear (3).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was moving straight ahead, which was the case for 395 vehicles. Turning left was the next most frequent action, recorded for 55 vehicles, followed by backing, which was the pre-crash action for 52 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight395 (58.4%)
2
Turning left55 (8.1%)
3
Backing52 (7.7%)
4
Slowing/stopping (deceleration)33 (4.9%)
5
Legally Parked29 (4.3%)
6
Turning right27 (4%)
7
Stopped in traffic24 (3.6%)
8
Other (explain in narrative)20 (3%)
9
Negotiating a curve8 (1.2%)

Showing top 9 of 19 reported. 10 additional (33 total) not shown: Overtaking/passing, Changing lanes, Illegally Parked/Unattended, Leaving a parked position, Accelerating in road, Starting in road, Leaving traffic lane, Entering traffic lane (merging), Making U-turn, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 943 people involved in crashes, the vast majority, 910 individuals, were drivers. Passengers accounted for 25 of the people involved. The remaining individuals included 6 bicyclists, 1 pedestrian, and 1 person classified as an 'other non-motorist'.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 943 individuals involved in crashes, 3 suffered fatal injuries. A total of 160 people sustained non-fatal injuries, including 18 with serious injuries, 56 with minor injuries, and 86 with possible injuries. The data also recorded 3 individuals involved in crashes who sustained no injuries.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Based on available data for safety equipment usage, 114 vehicle occupants were reported as using a shoulder and lap belt. In contrast, 15 occupants were recorded as using no safety equipment at all. A small number of occupants used other restraints like a shoulder belt only or a child safety seat.

Occupant Safety Equipment

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Single-vehicle crashes were the most common type of incident, accounting for 279 of the 522 total crashes (53.4%). Two-vehicle crashes were also frequent, with 231 incidents (44.3%). Crashes involving three or more vehicles were rare, with only 12 such events recorded during the year.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

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: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 522
  • Total persons involved: 943
  • Total vehicles involved: 777

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: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-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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