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Go local: the key to COVID-19 lockdown release

Pandemics, such as COVID-19, are usually assumed to spread rapidly within the population. In reality, the population is more heterogeneous with regard to risk, and there will be large variation on the basis of geography, workplace and other key factors.

Analysing data on a national level therefore risks hiding this heterogeneity and compromises the most effective public health response. New analysis from i-sense researchers at University College London suggests COVID-19 has such diverse effects on the different local authorities in the UK.

Tracking COVID-19 using online search data

i-sense researchers from University College London, led by Dr Vasileios Lampos, in collaboration with Public Health England, Microsoft Research, and Harvard Medical School are looking at ways of tracking COVID-19 using online search data to better understand the true extent of community spread.

Their current analysis, which uses machine learning models to make predictions of potential prevalence of COVID-19 in a population, focuses on a number of countries, including the United Kingdom, United States of America, Canada, Australia, France, and Italy.

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