The Happy Land Fire Tragedy Casualties Visualization Tool - Cockeyed.com

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Disaster Casualties Visualization Tool: The Happy Land Fire: 1990

87 Dead Men and Women

The Happy Land fire was an arson fire that killed 87 people trapped in an unlicensed social club, 1990.

This was a person. He knew a lot of cops.

This was a person. She was the unofficial relationship guru among friends. She played a lot of social card games.

This was a person. She could play harmonica. She was very careful about conserving gasoline.

This was a person. She wanted to learn magic. She could play cricket.

This was a person. He watched a lot of sports on TV, but never played them himself. He taught guitar.

This was a person. He was a glassblower.

This was a person. He has a suit at the cleaners. He was a skilled woodcarver.

This was a person. She got a terrible haircut a few days ago and shaved her head to escape from it. She scalped tickets

This was a person. She had a lot of Beatles records. She helped people.

This was a person. She wanted to learn magic. She could play banjo.

This was a person. She did not own a fridge.

This was a person. He had bonsai trees.

This was a person. She smoked pot at music festivals.

This was a person. He had a sexy phone voice.

This was a person. He was always in a hurry.

This was a person. She was always in a hurry.

This was a person. She was a wedding photographer.

This was a person. He was cockeyed.

This was a person. He has a suit at the cleaners. He could fall asleep anywhere.

This was a person. She was a teacher.

This was a person. She was working her way through all of the shows on Netflix.

This was a person. She could fix anything.

This was a person. He was a skilled woodcarver. He was thrifty.

This was a person. She was a historian.

This was a person. She had a gun. She was a skilled woodcarver.

This was a person. She was a cat person.

This was a person. She was a Mac evangelist.

This was a person. He helped people. He kept to himself mostly

This was a person. He could play banjo.

This was a person. He never carried cash.

This was a person. He played piano.

This was a person. She called in sick to work 9 times last month and was written up at work.

This was a person. She lived on breakfast bars.

This was a person. He got a terrible haircut a few days ago and shaved his head to escape from it.

This was a person. She constantly wore sunglasses.

This was a person. She was a Mac evangelist.

This was a person. He was a DJ. He wore earphones all the time.

This was a person. He couldn't grow a mustache.

This was a person. He played World of Warcraft He helped strangers.

This was a person. He wrote for the newspaper.

This was a person. She never ate breakfast.

This was a person. He was a dog person.

This was a person. She looked like a cartoon.

This was a person. She loved pot.

This was a person. She was the richest of her friends.

This was a person. He was a vegetarian. He could play cricket.

This was a person. She wore a lot of hats.

This was a person. He was living with his sister. He was learning to speak French.

This was a person. She did not sleep with a pillow. She always brought lunch.

This was a person. She spent a lot of time with old people.

This was a person. She always brought lunch. She brought great food to social gatherings.

This was a person. He had a personal injury lawsuit working its way through the courts.

This was a person. She ate a lot of fiber.

This was a person. She brought great food to social gatherings.

This was a person. She loved Elvis. She brought great food to social gatherings.

This was a person. She ate the food at convenience stores. She chewed nicotine gum.

This was a person. She talked during movies.

This was a person. She could play harmonica.

This was a person. He called in sick to work 9 times last month and was written up at work. He was a virgin.

This was a person. She was a hoarder.

This was a person. She was an expert barbecuer.

This was a person. He played World of Warcraft He had lice.

This was a person. He wore earphones all the time.

This was a person. She was a skilled woodcarver. She was homophobic.

This was a person. He was good to people.

This was a person. She brought great food to social gatherings.

This was a person. He had a sexy phone voice.

This was a person. He had been having trouble tying his shoes because he pulled a muscle in his abs. He was a plumber.

This was a person. He loved wine.

This was a person. She was polite to telemarketers.

This was a person. She never raised hervoice.

This was a person. He was a cat person. He snored.

This was a person. He had a sexy phone voice.

This was a person. She was afraid of the water.

This was a person. She never carried cash.

This was a person. He never drank coffee.

This was a person. He loved fine dining. He played chess.

This was a person. He ate a lot of raisins.

This was a person. He could fall asleep anywhere. He loved oreos.

This was a person. She slept around. She was left-handed.

This was a person. He played a lot of social card games.

This was a person. She spent a lot of time with old people. She loved rollerblading.

This was a person. He excelled at woodworking.

This was a person. He spent a lot of time with old people. He fixed bikes.

This was a person. He took a lot of photos. He had a bunch of cameras.

This was a person. She was learning to use CAD software.

This was a person. She was afraid of heights.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

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