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Legionnaires' disease outbreak in New Jersey's prisons kept quiet by state officials -- Health & Wellness -- Sott.net


© Illustration: Science Photo Library via AP
Illustration of Legionella pneumophila bacteria, the cause of Legionnaires disease: After one person died and another spent a month in a coma, state officials found Legionella bacteria in the water at two New Jersey prisons.After Jamil Robinson drank the water from the infirmary at East Jersey State Prison, he became so violently ill that prison officials quietly sent him to the hospital. On February 9, Robinson
was placed in a medically induced coma, which he stayed in for more than 30 days. When he woke up on March 12, nurses told him he had contracted Legionnaires disease, a rare form of pneumonia. ....

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New Jersey Legionnaires' Outbreak Kept Quiet in State Prisons


Staff never announced that anyone had contracted Legionnaires’ disease, according to Robinson and one other person incarcerated at EJSP, who requested to speak anonymously for fear of retaliation. And they didn’t tell people to stop drinking the water until two weeks ago, Robinson said. According to both Robinson and the other person, prison officials did not provide free bottled water to anyone except corrections staff.
On April 16, Rutgers Health, which regularly sends public health notices to New Jersey prisons, distributed a flyer about how Legionella grows and how the disease spreads to post in all housing units and on must-read boards. ....

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How Decision Intelligence Can Seriously Boost Your BI Game


(Image: Getty)
For most of us, making data-driven business decisions is a four-step process. First, you collect the data. Next, you mine it, which just means some combination of tools and data scientists look for patterns and correlations between different kinds of data. Third, those discoveries get pumped into the dashboards and visualizations that managers get to see. From there, it s up to the manager to interpret what the dashboard is telling them and make their decision.
The problem there is that the data you ve collected, and the patterns your tools and data scientists have discovered, now define the decisions you can make. A simplified example: Say PCMag collects loads of data on which articles have performed the best in terms of how many clicks a particular article or group of articles has received. Then our database engines rumble to life, groups the best articles together, and builds pretty visualizations so we can understand what was found. What we re looking ....

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