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Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission
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Series / Report no.
Open Access
Type
Preprint
Language
en
Date
2024-05-03
Research Projects
Organizational Units
Journal Issue
Title
Estimating the effectiveness of non-pharmaceutical interventions against COVID-19 transmission
Translated Title
Published in
Abstract
During the COVID-19 pandemic non-pharmaceutical interventions (NPIs) were taken to mitigate
virus spread. Many of these measures were taken together and interacted with each other, and
compliance may have changed over the course of the pandemic, making it difficult to
disentangle the effectiveness of single measures. It can be more meaningful to consider the
overall effectiveness of sets of NPIs during the pandemic.
We estimate the overall effectiveness of sets of NPIs in reducing transmission by comparing the
observed reproduction number, which is the number of secondary infections caused by a
typically infected person, to a counterfactual reproduction number if no NPIs were taken. The
counterfactual reproduction number is based on a reproduction number that accounts for
seasonal variations in transmissibility, for emergence of more transmissible variants, and for
changes in immunity in the population. The population immunity is reconstructed from
longitudinal serological surveys and vaccination coverage data, taking immunity waning after
infection and vaccination into account. We estimate the effectiveness of NPIs as taken in the
Netherlands from the start of the pandemic in March 2020 until the emergence of the Omicron
variant in November 2021.
We find that the effectiveness of NPIs was high in March and April 2020 during the first
pandemic wave and it was high in January and February 2021, coinciding with the two periods
with the most stringent measures. For both periods the effectiveness was estimated at
approximately 50%, i.e. without any measures the reproduction number would have been
twice as high as observed.
This approach to estimate overall effectiveness of NPIs against transmission over time
combines data from different sources, while making relatively few assumptions on the
transmission process. This method can be applied to any region with sufficient data to
2
reconstruct the population immunity. Also during a future pandemic of any directly transmitted
disease, this method can provide a quick insight into the effect of control measures.