111 posts
How experts use disease modeling to help inform policymakers

Harry Stevens and John Muyskens for The Washington Post put you in the spot of an epidemiologist receiving inquiries from policymakers about what might happen: Imagine you are an epidemiologist, and one day the governor sends you an email about an emerging new disease that has just arrived in your state. To avoid the complexities of a real disease like covid-19, the illness caused by the novel coronavirus, we have...

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Comparing Covid-19 models

FiveThirtyEight compared six Covid-19 models for a sense of where we might be headed. With different assumptions and varying math, the trajectories vary, but they at least provide clues so that policymakers can make educated decisions. If you’re interested in the data behind these models, check out the COVID-19 Forecast Hub maintained by the Reich Lab at the University of Massachusetts Amherst. They helped with the FiveThirtyEight comparisons and are...

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Challenges of making a reliable Covid-19 model

Fatalities from Covid-19 range from the hundreds of thousands to the millions. Nobody knows for sure. These predictions are based on statistical models, which are based on data, which aren’t consistent and reliable yet. FiveThirtyEight, whose bread and butter is models and forecasts, breaks down the challenges of making a model and why they haven’t provided any. Tags: coronavirus, FiveThirtyEight, modeling

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Myth of the impartial machine

In its inaugural issue, Parametric Press describes how bias can easily come about when working with data: Even big data are susceptible to non-sampling errors. A study by researchers at Google found that the United States (which accounts for 4% of the world population) contributed over 45% of the data for ImageNet, a database of more than 14 million labelled images. Meanwhile, China and India combined contribute just 3% of...

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Game of Thrones death predictor

Monica Ramirez tried her hand with modeling deaths on Game of Thrones and trying to predict the next ones: Since the series is so famous for killing principal characters (It’s true! Yu can’t have a favourite character because he/she wouls die, and slowly, other characters take the lead… and would probably die too), I decided to make a Classification Model in Python, to try to find any rule or pattern...

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