Evidence map›Paper›PMID 34282423›Full record

ArticlemedRxiv : the preprint server for health sciences2021

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

Kathleen M O'Reilly, Frank Sandman, David Allen, Christopher I Jarvis, Amy Gimma, Amy Douglas, Lesley Larkin, Kerry Lm Wong, Marc Baguelin, Ralph S Baric and 4 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 2 countries.

Kathleen M O'ReillyCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Frank SandmanCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
David AllenDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
Christopher I JarvisCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Amy GimmaCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Amy DouglasGastrointestinal Pathogens Unit, National Infection Service, Public Health England, London, UK.
Lesley LarkinGastrointestinal Pathogens Unit, National Infection Service, Public Health England, London, UK.
Kerry Lm WongCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Marc BaguelinCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Ralph S BaricDepartment of Epidemiology, University of North Carolina, Chapel Hill, USA.
Lisa C LindesmithDepartment of Epidemiology, University of North Carolina, Chapel Hill, USA.
Richard A GoldsteinDivision of Infection and Immunity, University College London, London, UK.
Judith BreuerDivision of Infection and Immunity, University College London, London, UK.
W John EdmundsCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
London School of Hygiene & Tropical Medicine · GBPublic Health England · GBUniversity of North Carolina at Chapel Hill · USGreat Ormond Street Hospital · GBUniversity College London · GB

Funding

Antibody Landscape following Human Norovirus Infection and VaccinationR01AI148260 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BARIC, RALPH S · 2020 to 2024
$3.7M
Medical Research Council MC_PC_19065NIAID NIH HHS R01 AI148260Wellcome Trust
6 · The paper itself

Abstract

backgroundTo 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.

methodsHere 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.

resultsWe 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.

conclusionsContinued 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.

Indexed as

COVID-19mathematical modellingNorovirusseasonalitysurveillancetransmission

Identifiers

PMID34282423
PMCPMC8288156
OpenAlexW3179375621

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.