Summary
Aim: The REMEDY project will provide innovative interdisciplinary empirical research that explores the driver and health
consequences of resistant behaviour against epidemic measures, leveraging social science insights, economic and statistical methods
and data science techniques.
Background: In the advent of the COVID-19 pandemic, one pressing challenge for the public health response is the general resistance
to legitimate public health policies driven by news media, influencers, extremist politicians, and rampant misinformation circulated
on the internet – a potential information disorder due to an “infodemic”. There is, however, little understanding of the mechanism
through which these potentially malicious messages propagate and how they, in turn, influence the behaviour of the population in
opposing vaccine, mask-wearing, mobility restrictions, social distancing, and consequently leading to higher levels of morbidity and
mortality.
Methods: This project employs different quantitative and research methodologies to estimate the effects of behavioural resistance on
the epidemic spread and excess mortality and whether online misinformation explains this resistance behaviour. First, we link real-world data on vaccine refusal, fines for non-compliance and the frequency and scale of anti-mask/vax/digital COVID-19 certificate
protests to the local epidemic spread, hospitalisation and excess mortality rate over time. Second, after identifying the different types
of online misinformation on COVID-19 and vaccines, we use geo-tagged digital records on search engines and social media to analyse
the association between online sentiments towards public health measures and real-world resistance behaviour at a specific geographic unit.
Impact: The project will not only provide hard evidence on the linkage between resistance behaviour and population health
outcomes, but will also present the gravity of precariously allowing misinformation to flourish on the internet.
consequences of resistant behaviour against epidemic measures, leveraging social science insights, economic and statistical methods
and data science techniques.
Background: In the advent of the COVID-19 pandemic, one pressing challenge for the public health response is the general resistance
to legitimate public health policies driven by news media, influencers, extremist politicians, and rampant misinformation circulated
on the internet – a potential information disorder due to an “infodemic”. There is, however, little understanding of the mechanism
through which these potentially malicious messages propagate and how they, in turn, influence the behaviour of the population in
opposing vaccine, mask-wearing, mobility restrictions, social distancing, and consequently leading to higher levels of morbidity and
mortality.
Methods: This project employs different quantitative and research methodologies to estimate the effects of behavioural resistance on
the epidemic spread and excess mortality and whether online misinformation explains this resistance behaviour. First, we link real-world data on vaccine refusal, fines for non-compliance and the frequency and scale of anti-mask/vax/digital COVID-19 certificate
protests to the local epidemic spread, hospitalisation and excess mortality rate over time. Second, after identifying the different types
of online misinformation on COVID-19 and vaccines, we use geo-tagged digital records on search engines and social media to analyse
the association between online sentiments towards public health measures and real-world resistance behaviour at a specific geographic unit.
Impact: The project will not only provide hard evidence on the linkage between resistance behaviour and population health
outcomes, but will also present the gravity of precariously allowing misinformation to flourish on the internet.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101107454 |
| Start date: | 04-09-2023 |
| End date: | 03-09-2025 |
| Total budget - Public funding: | - 211 754,00 Euro |
Cordis data
Original description
Aim: The REMEDY project will provide innovative interdisciplinary empirical research that explores the driver and healthconsequences of resistant behaviour against epidemic measures, leveraging social science insights, economic and statistical methods
and data science techniques.
Background: In the advent of the COVID-19 pandemic, one pressing challenge for the public health response is the general resistance
to legitimate public health policies driven by news media, influencers, extremist politicians, and rampant misinformation circulated
on the internet – a potential information disorder due to an “infodemic”. There is, however, little understanding of the mechanism
through which these potentially malicious messages propagate and how they, in turn, influence the behaviour of the population in
opposing vaccine, mask-wearing, mobility restrictions, social distancing, and consequently leading to higher levels of morbidity and
mortality.
Methods: This project employs different quantitative and research methodologies to estimate the effects of behavioural resistance on
the epidemic spread and excess mortality and whether online misinformation explains this resistance behaviour. First, we link real-world data on vaccine refusal, fines for non-compliance and the frequency and scale of anti-mask/vax/digital COVID-19 certificate
protests to the local epidemic spread, hospitalisation and excess mortality rate over time. Second, after identifying the different types
of online misinformation on COVID-19 and vaccines, we use geo-tagged digital records on search engines and social media to analyse
the association between online sentiments towards public health measures and real-world resistance behaviour at a specific geographic unit.
Impact: The project will not only provide hard evidence on the linkage between resistance behaviour and population health
outcomes, but will also present the gravity of precariously allowing misinformation to flourish on the internet.
Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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