edoc

Potential impact of seasonal forcing on a SARS-CoV-2 pandemic

Neher, Richard A. and Dyrdak, Robert and Druelle, Valentin and Hodcroft, Emma B. and Albert, Jan. (2020) Potential impact of seasonal forcing on a SARS-CoV-2 pandemic. Swiss Medical Weekly, 150. w20224.

[img]
Preview
PDF - Published Version
Available under License CC BY-NC-ND (Attribution-NonCommercial-NoDerivatives).

1027Kb

Official URL: https://edoc.unibas.ch/79825/

Downloads: Statistics Overview

Abstract

A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The outbreak has been declared a pandemic by the WHO on Mar 11, 2020. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterise our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Computational Modeling of Biological Processes (Neher)
UniBasel Contributors:Neher, Richard A and Druelle, Valentin and Hodcroft, Emma
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:EMH Schweizerischer Ärzteverlag
ISSN:1424-7860
e-ISSN:1424-3997
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Related URLs:
Identification Number:
edoc DOI:
Last Modified:31 Jan 2022 09:43
Deposited On:31 Jan 2022 09:43

Repository Staff Only: item control page