Your browser doesn't support javascript.
Intensity and lag-time of non-pharmaceutical interventions on COVID-19 dynamics in German hospitals.
Montcho, Yvette; Klingler, Paul; Lokonon, Bruno Enagnon; Tovissodé, Chénangnon Frédéric; Glèlè Kakaï, Romain; Wolkewitz, Martin.
  • Montcho Y; Laboratoire de Biomathématiques et d'Estimations Forestières, Université d'Abomey-Calavi, Cotonou, Benin.
  • Klingler P; Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
  • Lokonon BE; Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
  • Tovissodé CF; Laboratoire de Biomathématiques et d'Estimations Forestières, Université d'Abomey-Calavi, Cotonou, Benin.
  • Glèlè Kakaï R; Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
  • Wolkewitz M; Laboratoire de Biomathématiques et d'Estimations Forestières, Université d'Abomey-Calavi, Cotonou, Benin.
Front Public Health ; 11: 1087580, 2023.
Article in English | MEDLINE | ID: covidwho-2272722
ABSTRACT

Introduction:

Evaluating the potential effects of non-pharmaceutical interventions on COVID-19 dynamics is challenging and controversially discussed in the literature. The reasons are manifold, and some of them are as follows. First, interventions are strongly correlated, making a specific contribution difficult to disentangle; second, time trends (including SARS-CoV-2 variants, vaccination coverage and seasonality) influence the potential effects; third, interventions influence the different populations and dynamics with a time delay.

Methods:

In this article, we apply a distributed lag linear model on COVID-19 data from Germany from January 2020 to June 2022 to study intensity and lag time effects on the number of hospital patients and the number of prevalent intensive care patients diagnosed with polymerase chain reaction tests. We further discuss how the findings depend on the complexity of accounting for the seasonal trends. Results and

discussion:

Our findings show that the first reducing effect of non-pharmaceutical interventions on the number of prevalent intensive care patients before vaccination can be expected not before a time lag of 5 days; the main effect is after a time lag of 10-15 days. In general, we denote that the number of hospital and prevalent intensive care patients decrease with an increase in the overall non-pharmaceutical interventions intensity with a time lag of 9 and 10 days. Finally, we emphasize a clear interpretation of the findings noting that a causal conclusion is challenging due to the lack of a suitable experimental study design.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Disease Control / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines / Variants Limits: Humans Country/Region as subject: Europa Language: English Journal: Front Public Health Year: 2023 Document Type: Article Affiliation country: Fpubh.2023.1087580

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Disease Control / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines / Variants Limits: Humans Country/Region as subject: Europa Language: English Journal: Front Public Health Year: 2023 Document Type: Article Affiliation country: Fpubh.2023.1087580