2 AND 3 DIMENSIONAL INSTABILITIES OF A SPATIALLY PERIODIC SHEAR-LAYER
BULLETIN OF THE AMERICAN PHYSICAL SOCIETY 25:9 (1980) 1085-1085
A stratospheric prognostic ozone for seamless Earth System Models: performance, impacts and future
Aeolus wind lidar observations of the 2019/2020 Quasi-Biennial Oscillation disruption with comparison to radiosondes and reanalysis
An observation-based climatology of middle atmospheric meridional circulation
Assessing the spread of the novel coronavirus in the absence of mass testing
International Journal of Clinical Practice, 75, 4, 2020
Abstract:
Background
Assessing why the spread of the COVID-19 virus slowed down in many countries in March through to May of 2020 is of great significance. The relative role of restrictions on behaviour (鈥渓ockdowns鈥) and of a natural slowing for other reasons is difficult to assess when mass testing was not widely done. This paper assesses the evolution of the spread of the COVID-19 virus over this period when there was no data on test results for a large, random sample of the population.
Method
We estimate a version of the susceptible-infected-recovered model applied to data on the numbers who were tested positive in several countries over the period when the virus spread very fast and then its spread slowed sharply. Up to the end of April 2020, test data came from non-random samples of populations who were overwhelmingly those who displayed symptoms. Using data from a period when the criteria used for testing (which was that people had clear symptoms) was relatively consistent is important in drawing out the message from test results. We use this data to assess two things: how large might be the group of those infected who were not recorded and how effective were lockdown measures in slowing the spread of the infection.
Results
We find that to match data on daily new cases of the virus, the estimated model favours high values for the number of people infected but not recorded.
Conclusions
Our findings suggest that the infection may have spread far enough in many countries by April 2020 to have been a significant factor behind the fall in measured new cases. Government restrictions on behaviour鈥攍ockdowns鈥攚ere only one factor behind slowing in the spread of the virus.
Assessing why the spread of the COVID-19 virus slowed down in many countries in March through to May of 2020 is of great significance. The relative role of restrictions on behaviour (鈥渓ockdowns鈥) and of a natural slowing for other reasons is difficult to assess when mass testing was not widely done. This paper assesses the evolution of the spread of the COVID-19 virus over this period when there was no data on test results for a large, random sample of the population.
Method
We estimate a version of the susceptible-infected-recovered model applied to data on the numbers who were tested positive in several countries over the period when the virus spread very fast and then its spread slowed sharply. Up to the end of April 2020, test data came from non-random samples of populations who were overwhelmingly those who displayed symptoms. Using data from a period when the criteria used for testing (which was that people had clear symptoms) was relatively consistent is important in drawing out the message from test results. We use this data to assess two things: how large might be the group of those infected who were not recorded and how effective were lockdown measures in slowing the spread of the infection.
Results
We find that to match data on daily new cases of the virus, the estimated model favours high values for the number of people infected but not recorded.
Conclusions
Our findings suggest that the infection may have spread far enough in many countries by April 2020 to have been a significant factor behind the fall in measured new cases. Government restrictions on behaviour鈥攍ockdowns鈥攚ere only one factor behind slowing in the spread of the virus.