Recovery, Renewal, Resilience

Lessons for Resilience

Consider how socio-economic and socio-cultural variables can affect the impacts of public health crises
information and data

Research has found that additional statistical modelling based on cultural and demographic factors can help to predict how disease outbreaks such as COVID-19 can accelerate and progress. The aim of this ongoing research is to project the spread of future pandemics by utilising the predictive power of cultural and demographic data. Effectiveness of response interventions should consider cultural values among people in communities. Consider:

  • A data driven approach to modelling disease outbreak prevalence based on cultural and demographic factors such as:
    • Population size
    • Population density
    • Public transport
    • Health (e.g. obesity)
    • Culture (e.g. voting patterns – research has shown that societies/communities with low trust in institutions tended to have higher COVID-19 death rates)

This paper offers a predictive model of COVID-19 prevalence – finding that the above 5 risk factors can predict between 47% and 60% of variation in COVID-19 prevalence in US counties. A second paper explores how cultural values can support the prediction of how outbreaks could progress and also what population groups may be most vulnerable.

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