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Social media data offers clues about the best pandemic response

Tracking social media can provide clues about how the general population are responding to a pandemic, new research reveals.

One of the worst Covid-19 outbreaks is devastating Brazil — Photo © AFP
One of the worst Covid-19 outbreaks is devastating Brazil — Photo © AFP

Assessing the spread of viruses can be aided by an analysis of social media accounts, according to a new study. To do so requires the application of sophisticated algorithms and the amassing of large quantities of data.

Research has been undertaken in relation to the spread of COVID-19 worldwide, modelled by scientists based in Australia, Afghanistan, Iran and Italy. The researchers amassed 35,000 tweets to assess the attitudes and perceptions of people. The aim of the research was not only to find insights in relation to the coronavirus situation, but also in relation to the societal effects during any pandemic.

A pandemic is an epidemic occurring worldwide, or over a very wide area, crossing international boundaries and usually affecting a large number of people. Pandemics occur annually in each of the temperate southern and northern hemispheres, given that seasonal epidemics cross international boundaries and affect a large number of people. Pandemics can also be of a very large range and impact, as the coronavirus situation of 2019-2021 illustrates.

Most of the data collected from social media related to Australia. Crunching the digital crowdsourced social media data enables policy makers to test out guidelines for interventions and to test out the decisions of authorities during the time of a pandemic.

Tackling a large city is important because there is a greater diversity of zoonotic diseases (diseases transmitted between animals and humans), and hence the next pandemic threat, in higher income countries. This is more so in nations with larger land areas, more dense human populations, and greater forest coverage. Further drivers for an escalating pandemic risk include population growth and density, especially as this places additional putting pressure on ecosystems.

Various response scenarios were tested, including alterations to social distancing policies, requirements for self-isolation, imposed quarantines, new forms of movement control, updated travel restrictions, and periodic lockdowns.

Such data can be used in conjunction with SIR dynamics (where the SIR represents susceptible, infected, and recovered). This is a common tool used in epidemiological studies of disease movement, especially for tracking disease spread according to various person-to-person interactions.

As well as enabling public policy to be shaped around the views of people to health officials and politicians, the analysed data provides details of the best ways to encourage people to follow certain measures and restrictions, and also to track how well these are being adhered to.

Going forwards such inquiries are of value since vaccine alone are not sufficient for controlling a pandemic, due to the factors associated with asymptomatic and pre-symptomatic transmission.

The sociology of health perspective appears in the journal Health Information Science and Systems. The research is titled “How can social media analytics assist authorities in pandemic-related policy decisions? Insights from Australian states and territories.”

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