OLH Tag: STEM

Social Media Reading List: Data, Mis/disinformation, and Policy & Regulation

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Social media is a huge topic. There are infinite articles, videos, and other discussion on the subject – and it can be difficult to know where to start. We’ve rounded up some great introductory reading to help you get acquainted with such a broad and fast moving conversation.

In the Spotlight: Kate Kenny (Jacobs)

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Introducing our ‘In the Spotlight’ series, where we’ll shine a light on professionals in our Network. First up, Kate! Kate is Vice President and Head of Sector for Cities & Places in Europe at Jacobs, one of the world’s largest multi-disciplinary engineering firms.

Use Excel to Model COVID-19

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Ebrahim shows us how to create your own spreadsheet model of the COVID-19 virus spread.

Dhiresh & Makers4TheNHS

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An interview with Dhiresh, who, at the age of 18, has spent his lockdown making face shields for NHS hospitals, GP surgeries, care homes, and other places in need of PPE.

COVID-19: Preventing Outbreaks

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How do social, economic, historical and political factors intertwine with ecology to make ‘spillover’ (transfer of new viruses from animals to humans) increasingly likely, and can anything be done to prevent it?

The Value of Probabilistic Thinking

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Probabilistic thinking is essentially trying to estimate, using some elements of maths and logic, the likelihood of a specific outcome actually happening.

Ecosystems

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Ecosystems are bubbles of life. They arise when weather, landscape, plants, animals, and other organisms all work together to form an interactive system. Ecosystems contain biotic (living) parts, like plants and animals, and abiotic (non-living) parts, like rocks and precipitation.

What are models?

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If you turn on the news right now, chances are you’ll probably hear someone talking about models. And they are important. They’re a crucial tool in helping us visualise the path of COVID-19, meaning we can start to make predictions about which interventions might work and which might not. So what actually are they?