
pmid: 34061892
pmc: PMC8168842
Abstract An acceleration index is proposed as a novel indicator to track the dynamics of the COVID-19 in real-time. Using French data on cases and tests for the period following the first lock-down - from May 13, 2020, onwards - our acceleration index shows that the ongoing pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration has been stronger than national average for the [59 − 68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19 − 28] age group is the lowest and is about half that of the [69 − 78], as of October 25. In addition, we propose an algorithm to allocate tests among French départements, based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France enters a second lock-down period with indeterminate duration. JEL Classification Numbers I18; H12
sub-national allocation of tests, Adult, Male, Adolescent, Science, Physical Distancing, COVID-19 Testing, indicator of epidemic dynamics, Humans, Child, Pandemics, Aged, Aged, 80 and over, Models, Statistical, SARS-CoV-2, Health Policy, Q, R, Infant, Newborn, COVID-19, Infant, Middle Aged, acceleration Index, Child, Preschool, Medicine, Female, [SHS] Humanities and Social Sciences, France, real-time Analysis, Research Article
sub-national allocation of tests, Adult, Male, Adolescent, Science, Physical Distancing, COVID-19 Testing, indicator of epidemic dynamics, Humans, Child, Pandemics, Aged, Aged, 80 and over, Models, Statistical, SARS-CoV-2, Health Policy, Q, R, Infant, Newborn, COVID-19, Infant, Middle Aged, acceleration Index, Child, Preschool, Medicine, Female, [SHS] Humanities and Social Sciences, France, real-time Analysis, Research Article
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