Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts

Nicolas Franco

doi:10.1101/2020.09.07.20190108

Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts

Nicolas Franco

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Résumé

We model the evolution of the covid-19 epidemic in Belgium with an age-structured extended SEIR-QD epidemic model with separated consideration for nursery homes. All parameters of the model are estimated using a MCMC method, except integrated data on social contacts. The model is calibrated on hospitals' data, number of deaths, nursery homes' tests and serological tests. We present the current situation on September 2020 as well as long-term scenarios-based forecasts with the possibility of a second wave in function of new transmissions from contacts at school.

langue originale	Anglais
Numéro d'article	100490
Nombre de pages	12
journal	Epidemics
Volume	37
Numéro de publication	100490
Les DOIs	https://doi.org/10.1101/2020.09.07.20190108 https://doi.org/10.1016/j.epidem.2021.100490
Etat de la publication	Publié - 27 août 2021

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10.1101/2020.09.07.20190108License: CC BY-NC-ND
10.1016/j.epidem.2021.100490License: CC BY-NC-ND

1-s2.0-S1755436521000414-mainVersion finale publiée, 12,6 MBLicense: CC BY-NC-ND

https://arxiv.org/abs/2009.03450License: CC BY-NC-ND

CÉCI – Consortium des Équipements de Calcul Intensif
CHAMPAGNE, B. (Responsable du Projet), Lazzaroni, R. (Responsable du Projet), Geuzaine , C. (Co-investigateur), Chatelain, P. (Co-investigateur) & Knaepen, B. (Co-investigateur)
1/01/18 → 31/12/22
Projet: Recherche

Plateforme Technologique Calcul Intensif
Champagne, B. (!!Manager)
Plateforme technologique Calcul intensif
Equipement/installations: Plateforme technolgique

Conférence de presse - 1er ministre de Belgique
Franco, N.
22/08/21
1 élément de Couverture média
Presse/Médias: Activités publiques

Namurois de l'année 2020 - Catégorie Science
Franco, N. (Bénéficiaire), 4 mars 2021
Prix: Mise à l'honneur nationale/internationale

Contient cette citation

@article{9a93400cbc0a4a69821440120a96f4f6,

title = "Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts",

abstract = "Following the spread of the COVID-19 pandemic and pending the establishment of vaccination campaigns, several non pharmaceutical interventions such as partial and full lockdown, quarantine and measures of physical distancing have been imposed in order to reduce the spread of the disease and to lift the pressure on healthcare system. Mathematical models are important tools for estimating the impact of these interventions, for monitoring the current evolution of the epidemic at a national level and for estimating the potential long-term consequences of relaxation of measures. In this paper, we model the evolution of the COVID-19 epidemic in Belgium with a deterministic age-structured extended compartmental model. Our model takes special consideration for nursing homes which are modelled as separate entities from the general population in order to capture the specific delay and dynamics within these entities. The model integrates social contact data and is fitted on hospitalisations data (admission and discharge), on the daily number of COVID-19 deaths (with a distinction between general population and nursing home related deaths) and results from serological studies, with a sensitivity analysis based on a Bayesian approach. We present the situation as in November 2020 with the estimation of some characteristics of the COVID-19 deduced from the model. We also present several mid-term and long-term projections based on scenarios of reinforcement or relaxation of social contacts for different general sectors, with a lot of uncertainties remaining.",

author = "Nicolas Franco",

year = "2021",

month = aug,

day = "27",

doi = "10.1101/2020.09.07.20190108",

language = "English",

volume = "37",

journal = "Epidemics",

issn = "1755-4365",

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number = "100490",

}

TY - JOUR

T1 - Covid-19 Belgium

T2 - Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts

AU - Franco, Nicolas

PY - 2021/8/27

Y1 - 2021/8/27

N2 - Following the spread of the COVID-19 pandemic and pending the establishment of vaccination campaigns, several non pharmaceutical interventions such as partial and full lockdown, quarantine and measures of physical distancing have been imposed in order to reduce the spread of the disease and to lift the pressure on healthcare system. Mathematical models are important tools for estimating the impact of these interventions, for monitoring the current evolution of the epidemic at a national level and for estimating the potential long-term consequences of relaxation of measures. In this paper, we model the evolution of the COVID-19 epidemic in Belgium with a deterministic age-structured extended compartmental model. Our model takes special consideration for nursing homes which are modelled as separate entities from the general population in order to capture the specific delay and dynamics within these entities. The model integrates social contact data and is fitted on hospitalisations data (admission and discharge), on the daily number of COVID-19 deaths (with a distinction between general population and nursing home related deaths) and results from serological studies, with a sensitivity analysis based on a Bayesian approach. We present the situation as in November 2020 with the estimation of some characteristics of the COVID-19 deduced from the model. We also present several mid-term and long-term projections based on scenarios of reinforcement or relaxation of social contacts for different general sectors, with a lot of uncertainties remaining.

AB - Following the spread of the COVID-19 pandemic and pending the establishment of vaccination campaigns, several non pharmaceutical interventions such as partial and full lockdown, quarantine and measures of physical distancing have been imposed in order to reduce the spread of the disease and to lift the pressure on healthcare system. Mathematical models are important tools for estimating the impact of these interventions, for monitoring the current evolution of the epidemic at a national level and for estimating the potential long-term consequences of relaxation of measures. In this paper, we model the evolution of the COVID-19 epidemic in Belgium with a deterministic age-structured extended compartmental model. Our model takes special consideration for nursing homes which are modelled as separate entities from the general population in order to capture the specific delay and dynamics within these entities. The model integrates social contact data and is fitted on hospitalisations data (admission and discharge), on the daily number of COVID-19 deaths (with a distinction between general population and nursing home related deaths) and results from serological studies, with a sensitivity analysis based on a Bayesian approach. We present the situation as in November 2020 with the estimation of some characteristics of the COVID-19 deduced from the model. We also present several mid-term and long-term projections based on scenarios of reinforcement or relaxation of social contacts for different general sectors, with a lot of uncertainties remaining.

U2 - 10.1101/2020.09.07.20190108

DO - 10.1101/2020.09.07.20190108

M3 - Article

SN - 1755-4365

VL - 37

JO - Epidemics

JF - Epidemics

IS - 100490

M1 - 100490

ER -

Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts

Résumé

SDG des Nations Unies

Accès au document

Empreinte digitale

Projets

CÉCI – Consortium des Équipements de Calcul Intensif

Équipement

Plateforme Technologique Calcul Intensif

Presse/médias

Conférence de presse - 1er ministre de Belgique

Prix

Namurois de l'année 2020 - Catégorie Science

Contient cette citation