TY - JOUR
T1 - Inferring the effective start dates of non-pharmaceutical interventions during COVID-19outbreaks
AU - Kohanovski, Ilia
AU - Obolski, Uri
AU - Ram, Yoav
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/4
Y1 - 2022/4
N2 - Background: During Feb-Apr. 2020, many countries implemented non-pharmaceutical interventions (NPIs), such as school closures and lockdowns, to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. Overall, these interventions seem to have reduced the spread of the pandemic. We hypothesized that the official and effective start dates of NPIs can be noticeably different, for example, due to slow adoption by the population, and that these differences can lead to errors in the estimation of the impact of NPIs. Methods: SEIR models were fitted to case data from 12 regions to infer the effective start dates of interventions and compare these with the official dates. The impact of NPIs was estimated from the inferred model parameters. Results: We infer mostly late effective start dates of interventions. For example, Italy implemented a lockdown on Mar 11, but we infer the effective start date on Mar 17 (+3.05−2.01 days 95% CI). Moreover, we find that the impact of NPIs can be underestimated if it is assumed they start on their official date. Conclusions: Differences between the official and effective start of NPIs are likely. Neglecting such differences can lead to underestimation of the impact of NPIs, which could cause decision-makers to escalate interventions and guidelines.
AB - Background: During Feb-Apr. 2020, many countries implemented non-pharmaceutical interventions (NPIs), such as school closures and lockdowns, to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. Overall, these interventions seem to have reduced the spread of the pandemic. We hypothesized that the official and effective start dates of NPIs can be noticeably different, for example, due to slow adoption by the population, and that these differences can lead to errors in the estimation of the impact of NPIs. Methods: SEIR models were fitted to case data from 12 regions to infer the effective start dates of interventions and compare these with the official dates. The impact of NPIs was estimated from the inferred model parameters. Results: We infer mostly late effective start dates of interventions. For example, Italy implemented a lockdown on Mar 11, but we infer the effective start date on Mar 17 (+3.05−2.01 days 95% CI). Moreover, we find that the impact of NPIs can be underestimated if it is assumed they start on their official date. Conclusions: Differences between the official and effective start of NPIs are likely. Neglecting such differences can lead to underestimation of the impact of NPIs, which could cause decision-makers to escalate interventions and guidelines.
KW - 3,494
KW - COVID-19
KW - NPI
KW - SEIR
KW - Word count
KW - epidemic
KW - infectious disease
KW - public health
UR - http://www.scopus.com/inward/record.url?scp=85125562317&partnerID=8YFLogxK
U2 - 10.1016/j.ijid.2021.12.364
DO - 10.1016/j.ijid.2021.12.364
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C2 - 34986406
AN - SCOPUS:85125562317
SN - 1201-9712
VL - 117
SP - 361
EP - 368
JO - International Journal of Infectious Diseases
JF - International Journal of Infectious Diseases
ER -