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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  called in sick to work 9 times last month and was written up at work. This was a person. He ate a lot of hot dogs. He slept around. This was a person. She  was a mason. This was a person. She  was a virgin. This was a person. She didn't get along with animals. This was a person. He was very good at cleaning. This was a person. She  was sort of selfish in bed. This was a person. She loved oreos. This was a person. She  volunteered at a middle school, because  she  had a crush on one of the other tutors. She  was sort of selfish in bed. This was a person. She  was a historian. She couldn't grow a mustache. This was a person. He sang. This was a person. He was left-handed. This was a person. He was working  his  way through all of the shows on Netflix. He was afraid of the water. This was a person. He  was a drunk. This was a person. She was a hoarder. This was a person. She has four overdue books.  This was a person. She spent a lot of time with old people. This was a person. She could fall asleep anywhere. She never drank coffee. This was a person. He spends a lot of time watching tennis. This was a person. She was a skilled woodcarver. She was thrifty. This was a person. She never finished the book club book. This was a person. He could play banjo. This was a person. She could play harmonica. This was a person. He made pie. This was a person. He constantly wore sunglasses. He wrote for the newspaper. This was a person. He  went to church. This was a person. She tutored kids. This was a person. She got thrown off of a golf course. She had a sexy phone voice. This was a person. She  scalped tickets This was a person. She  was a translator. She  did open mike. This was a person. She always wore a hat. This was a person. She was the unofficial relationship guru among   friends. This was a person. She wrote for the newspaper. She wanted to learn magic. This was a person. He grew up on a farm.  This was a person. She  kept buying vegetables, even though they always just went bad in  her fridge. This was a person. He wanted to learn magic. This was a person. She ate a lot of fish. She loved wine. This was a person. She made  her  own beer and was kind of stingy with it. This was a person. She never drank coffee. This was a person. He led the choir. He made scrapbooks. This was a person. She could play cricket. This was a person. He  was sort of selfish in bed. This was a person. She was afraid of heights. This was a person. He sang at parties. This was a person. He  kept buying vegetables, even though they always just went bad in  his fridge. He was working  his  way through all of the shows on Netflix. This was a person. He didn't have a family. This was a person. He chewed nicotine gum. This was a person. He was always in a hurry. This was a person. He loved fine dining. This was a person. She took careful notes after every meal. This was a person. He had a bunch of tattoos. This was a person. She was polite to salesmen. This was a person. She always brought lunch. She snored. This was a person. She  was learning to speak French. This was a person. She was 4 days sober. This was a person. He  was awaiting judgement for a DUI last month. He  was a virgin. This was a person. He had a lot of shoes. He was an expert barbecuer. This was a person. He  was a tailor. This was a person. She  dropped her work laptop last week, destroyed it and couldn't sleep for days. This was a person. He ate a lot of chinese food. This was a person. She was a dog person. This was a person. He looked like a cartoon. This was a person. She had a bunch of tattoos. She had braces on  her  teeth. This was a person. He loved chocolate. This was a person. He always brought lunch. This was a person. He  kept buying vegetables, even though they always just went bad in  his fridge. This was a person. He was thrifty. This was a person. He was allergic to peanuts. This was a person. He was rough and tumble. This was a person. He ate a lot of raisins. This was a person. He loved fine dining. He spent a lot of time with old people. This was a person. He loved pot. He had an unfortunate nickname. This was a person. She  was playing nine games of Words with Friends on  her  phone. She took careful notes after every meal. This was a person. He  had a personal injury lawsuit working its way through the courts. This was a person. He  had VD. This was a person. He  dropped his work laptop last week, destroyed it and couldn't sleep for days. This was a person. He was thrifty. This was a person. He  had a personal injury lawsuit working its way through the courts. He was a crossword whiz. This was a person. He was homophobic. This was a person. She  called in sick to work 9 times last month and was written up at work. This was a person. He talked during movies. This was a person. She  dropped her work laptop last week, destroyed it and couldn't sleep for days. She  was a mason. This was a person. She could fall asleep anywhere. This was a person. He plays fantasy football. This was a person. He  was afraid of flying. This was a person. He helped strangers. This was a person. He threw a lot of parties.

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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