A New Mathematical Research Can Track Epidemics - Seeker's Thoughts

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A New Mathematical Research Can Track Epidemics


As Coronavirus spreads worldwide, leaders are relying on mathematical models to make public health and economic decisions.

A new model developed by Princeton and Carnegie Mellon researchers improves the tracking of epidemics by accounting for mutations in diseases. Now, the researchers are working to apply their model to allow leaders to evaluate the effects of countermeasures to epidemics before they deploy them.

Researchers want to consider interventions like quarantines, isolating people. etc., and then see how they affect and the epidemic’s spread when the pathogen is mutating as it spreads.

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Epidemics and Economics

Infectious diseases and associated mortality have abated, but they remain a significant threat throughout the world. We continue to fight both old pathogens, such as the plague, that have troubled humanity for millennia and new pathogens, such as human immunodeficiency virus (HIV), that have mutated or spilled from animal reservoirs.

Several infectious diseases, such as TB and malaria, are endemic to many areas, imposing substantial but steady burdens. 

Others, such as influenza, fluctuate in pervasiveness and intensity, wreaking havoc in developing and developed economies alike when an outbreak a sharp increase in prevalence in a relatively limited area or population, an endemic a sharp increase covering a larger area or population, or pandemic an epidemic covering multiple countries or continents occurs.


The health risks of outbreaks and epidemics and the fear and panic that accompany them map to various economic risks.

Costs to the health system

There are the costs to the health system, both public and private, of medical treatment of the infected and of outbreak control. A sizable outbreak can overwhelm the health system, limiting the capacity to deal with routine health issues and compounding the problem.
Beyond shocks to the health sector, epidemics force both the ill and their caretakers to miss work or be less effective at their jobs, driving down disrupting productivity.
                 
Fear of infection can result in social distancing or closed schools, enterprises, commercial establishments, transportation, and public services all of which disrupt economic and other socially valuable activity.

Consequences of outbreaks and epidemics

The consequences of outbreaks and epidemics are not distributed equally throughout the economy. Some sectors may even benefit financially, while others will suffer disproportionately.

Pharmaceutical companies that produce vaccines, antibiotics, or other products needed for outbreak response are potential beneficiaries. Health and life insurance companies are likely to bear heavy costs, at least in the short term, as are livestock producers in the event of an outbreak linked to animals.

Vulnerable populations, particularly the poor, are likely to suffer disproportionately, as they may have less access to health care and lower savings to protect against financial catastrophe.


Several factors complicate the management of epidemic risk

Diseases can be transmitted rapidly, both within and across countries, which means that timely response to initial outbreaks is essential.

In addition to being exacerbated by globalization, the epidemic potential is elevated by the twin phenomena of climate change and urbanization.
Climate change is expanding that habitat of various diseases, like the novel coronavirus and other deadly viruses.

Urbanization means more humans live in close quarters, amplifying the transmissibility of contagious disease. In rapidly urbanizing areas, the growth of slums forces more people to live in conditions with substandard sanitation and poor access to clean water compounding the problem.


How new mathematical can be effectively tract epidemics?

The models currently used to track epidemics use data from doctors and health workers to make predictions about disease progression.

The model most widely used today is not designed to account for changes in the disease being tracked. This inability to account for changes in the diseases can make it more difficult for leaders to counter a disease’s spread knowing how a mutation could affect transmission or virulence could help leaders decide when to institute isolation orders or dispatch additional resources to an area.

“In reality, these are a physical thing, but in this model, they abstracted into parameters that can help us more easily understand the effects of policies and of mutation”
If the researchers can correctly account for measures to counter the spread of disease, they could give leaders critical insights into the best steps they could take in the face of pandemics.
The researchers are now working to adapt the model to account for public health measures taken to stem an epidemic as well.




Information through social networks

The researchers’ work stems from their examination of the movement of information through social networks, which has remarkable similarities to the spread of biological infections.
Notably, the spread of information is affected by slight changes in the information itself. If something becomes slightly more exciting to recipients.

For example – they are more likely to pass it along or to pass it along to a wider group of people. By modeling such variations, one can see how changes in the message change its target audience.

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According to the researcher, the spread of a rumor or of information through a network is very similar to the spread of a virus through the population.
This model allows researchers to consider changes to the information as it spread through the network and how those changes affect the spread.

The model is agnostic with regards to the physical network of connectivity among individuals. An expert in the field of information theory whose work has helped establish a modern cellphone network.
The information is being abstracted into graphs of connected nodes; the nodes might be information sources or they might be potential sources of infection.

Conclusively - the COVID-19 virus is spreading so much more rapidly than predicted, and thereby helps them deploy more effective and timely countermeasures.


Researchers – H Vincent poor co-authors included researchers Rashad Eletreby, Yong Zhuang, Kathleen Carley and Osman Yağan of Carnegie Mellon. The work was supported in part by the Army Research Office, the National Science Foundation and the Office of Naval Research.

Source – Princeton University, Engineering school


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