Predicted Norovirus Resurgence in 2021-2022 Due to the Relaxation of Nonpharmaceutical Interventions Associated with COVID-19 Restrictions in England: A Mathematical Modelling Study.

COVID-19 Norovirus mathematical modelling seasonality surveillance transmission

Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
03 Sep 2021
Historique:
pubmed: 21 7 2021
medline: 21 7 2021
entrez: 20 7 2021
Statut: epublish

Résumé

To reduce the coronavirus disease burden in England, along with many other countries, the Government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions. Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021. We report that susceptibility to norovirus infection has likely increased between March 2020 to mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages. Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Sections du résumé

BACKGROUND BACKGROUND
To reduce the coronavirus disease burden in England, along with many other countries, the Government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions.
METHODS METHODS
Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021.
RESULTS RESULTS
We report that susceptibility to norovirus infection has likely increased between March 2020 to mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages.
CONCLUSIONS CONCLUSIONS
Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Identifiants

pubmed: 34282423
doi: 10.1101/2021.07.09.21260277
pmc: PMC8288156
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : Medical Research Council
ID : MC_PC_19065
Pays : United Kingdom

Commentaires et corrections

Type : UpdateIn

Déclaration de conflit d'intérêts

Competing interests - The authors declare no competing interests.

Auteurs

Kathleen M O'Reilly (KM)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Frank Sandman (F)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Statistics, Modelling and Economics Department, National Infection Service, Public Health England, London, UK.
NIHR Health Protection Research Unit in Modelling and Health Economics, London School of Hygiene and Tropical Medicine, London, UK.

David Allen (D)

Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Christopher I Jarvis (CI)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Amy Gimma (A)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Amy Douglas (A)

Gastrointestinal Pathogens Unit, National Infection Service, Public Health England, London, UK.

Lesley Larkin (L)

Gastrointestinal Pathogens Unit, National Infection Service, Public Health England, London, UK.

Kerry Lm Wong (KL)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Marc Baguelin (M)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK.

Ralph S Baric (RS)

Department of Epidemiology, University of North Carolina, Chapel Hill, USA.

Lisa C Lindesmith (LC)

Department of Epidemiology, University of North Carolina, Chapel Hill, USA.

Richard A Goldstein (RA)

Division of Infection and Immunity, University College London, London, UK.

Judith Breuer (J)

Division of Infection and Immunity, University College London, London, UK.
Department of Microbiology, Virology and Infection Control, Great Ormond Street Hospital for Children, London, UK.

W John Edmunds (WJ)

Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Classifications MeSH