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Из курса от партнера The Pennsylvania State University

Epidemics - the Dynamics of Infectious Diseases

587 оценки

The Pennsylvania State University

Epidemics - the Dynamics of Infectious Diseases

587 оценки

Not so long ago, it was almost guaranteed that you would die of an infectious disease. In fact, had you been born just 150 years ago, your chances of dying of an infectious disease before you've reached the tender age of 5 would have been extremely high. Since then, science has come a long way in understanding infectious diseases - what they are, how they spread, and how they can be prevented. But diseases like HIV/AIDS, Malaria, Tuberculosis, or the flu are still major killers worldwide, and novel emerging diseases are a constant threat to public health. In addition, the bugs are evolving. Antibiotics, our most potent weapon against bacterial infections, are losing their power because the bacteria are becoming resistant. In this course, we'll explore the major themes of infectious diseases dynamics. After we’ve covered the basics, we'll be looking at the dynamics of the flu, and why we're worried about flu pandemics. We'll be looking at the dynamics of childhood diseases such as measles and whooping cough, which were once considered almost eradicated, but are now making a comeback. We'll explore Malaria, and use it as a case study of the evolution of drug resistance. We'll even be looking at social networks - how diseases can spread from you to your friends to your friends' friends, and so on. And of course we’ll be talking about vaccination too. We’ll also be talking about how mobile phones, social media and crowdsourcing are revolutionizing disease surveillance, giving rise to a new field of digital epidemiology. And yes, we will be talking about Zombies - not human zombies, but zombie ants whose brains are hijacked by an infectious fungus. We're looking forward to having you join us for an exciting course!

Из урока

Epidemiology

Where humans live and how they are connected to each other, have strong effects on how infectious diseases can spread. In this module, you will learn about some of the related key concepts of epidemiology. After looking at some fascinating history, we’ll learn about social networks as the ultimate “road map” on which diseases can travel and we’ll talk about how the structure of the network can influence disease dynamics. After that, we’ll cover three topics that all affect infectious disease epidemiology in dramatic ways: human transport systems, population density and so-called superspreaders - individuals who can spread a disease to dozens or even hundreds of other individuals. We’ll close by identifying what information is required for disease surveillance.

Roots of Epidemiology6:25

Social Networks5:45

Structure of Networks5:49

Superspreaders6:09

Познакомьтесь с преподавателями

Dr. Ottar N. Bjornstad
Professor of Entomology and Biology
Department of Biology
Dr. Rachel A. Smith
Associate Professor
Department of Communication Arts & Sciences and Human Development & Family Studies
Dr. Mary L. Poss
Professor of Biology
Department of Biology
Dr. David P. Hughes
Assistant Professor of Entomology and Biology
Department of Biology
Dr. Peter Hudson
Willaman Professor of Biology
Department of Biology
Dr. Matthew Ferrari
Assistant Professor of Biology
Department of Biology
Dr. Andrew Read
Alumni Professor in the Biological Sciences, and Professor of Entomology
Center for Infectious Disease Dynamics
Dr. Marcel Salathé
Assistant Professor of Biology
Department of Biology

Social networks are of huge importance to infectious disease spread.

But when I say social network I mean something different from what

you may think.

When I say social network, you may think of friends and family.

Or you may think of online social networks such as Facebook and Twitter, and

indeed these kinds of networks do matter too.

But really when I say social network I mean a network of people

that are connected by potential disease transmission events.

Let me clarify.

Infectious diseases can cause nasty symptoms and sometimes be a deadly threat.

But what makes infectious diseases so

dangerous is that they are, well, infectious.

The organisms that cause the disease can jump from one person to the next, and

thereby setting off a massive cascade of disease transmission.

We can conceptualize this by a network, or what's often called a graph.

In this kind of network, we think of people simply as nodes in the network, and

we put an edge between two nodes only if there is a potential for

disease transmission.

We can start with any person and connect them to

any other person to whom they could potentially transmit the disease.

For all of these people, we will do the same.

We'll connect them to any other person to whom they could then pass on the disease,

and so on and on until we have mapped the entire social network for

this particular disease.

This social network is like the road system on which a disease can travel.

And just like you would want to have a map of all roads

when you try to study traffic patterns, we would like

to know about the social network when we try to study disease dynamics.

It's important to note that each disease has its own social network.

That's because the edges in the network represent potential disease

transmission events.

And that varies from disease to disease.

Some networks are probably quite similar to each other.

For example, all diseases that are sexually transmitted,

probably have a similar social network that's relevant for them.

But at the same time if the transmission roots of two diseases are very different

then the relevant social networks will be very different.

This is why you would not expect any similarity between the networks relevant

for something like the flu to something like malaria.

Social networks are incredibly important when we think of infectious diseases.

A good example is a strategy called contact tracing.

Lets say you were studying an outbreak of a disease and

you would like to stop the outbreak right away.

Hopefully, you've been on the case very early during the outbreak,

in which case there would be only a few cases.

Contact tracing means to identify all the contacts that

a case has had in the recent past.

You could follow up with all the contacts and try to protect them and

the rest of the population with whatever measures you would find necessary,

such as vaccination or quarantining.

Indeed, contact tracing was hugely important in recent disease outbreaks

such as the Ebola outbreak in West Africa that started in 2014 and

the MERS outbreak in South Korea that started in 2015.

Contact tracing is essentially a social network strategy

starting from a given node, you find all the contacted nodes

by following along the edges adjacent to the first node.

Then, by vaccinating or quarantining the nodes you found,

you are essentially cutting them off from the social network,

thereby protecting the rest of the network.

We probably won't have very good data on entire social networks for

any disease for a long time, if ever.

The main reason is that social networks are very hard to measure.

Contact tracing is a very resource intensive process,

even if you just follow-up on a few cases.

Imagine having to do this for thousands or millions of people.

That's almost guaranteed to be impractical for various reasons.

However, what you can do is map the social networks of some groups like schools,

households, workplaces, hospitals, and others.

The kinds of groups you'd pick will depend on the disease, and

then see if you can find some generalities.

Perhaps there are aspects about certain social networks

that are very constant across various groups, in which case,

it would not be necessary to map the network of an entire population.

To summarize, social networks are the road maps for

the spread of infectious diseases.

Because of that, these social networks are very important to study

disease dynamics and to study ways of controlling the spread of disease.

At the same time, mapping these networks in great detail is impractical.

And so, we need to come up with more efficient ways

to understand the structure of these networks.

Thankfully, in the past two decades, the emerging science

of complex networks has revealed a lot about spreading processes,

such as infectious disease spread on a variety of network structures.

In another video, we'll look at some of these more common social network

structures and how they affect the way in which disease can spread and

how it can be best controlled.

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