Mathematical modelling of COVID-19: a systematic review and quality assessment in the early epidemic response phase

I. Dhaoui; W. Van Bortel; E. Arsevska; C. Hautefeuille; S. Tablado Alonso; E. V. Kleef

doi:10.1016/j.ijid.2021.12.260

Mathematical modelling of COVID-19: a systematic review and quality assessment in the early epidemic response phase

I. Dhaoui, W. Van Bortel, E. Arsevska, C. Hautefeuille, S. Tablado Alonso, E. V. Kleef

Research output: Contribution to journal › Meeting abstract in journal

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Original language	English
Article number	PS25.02
Journal	International Journal of Infectious Diseases
Volume	116
Pages (from-to)	S110-S110
Number of pages	1
ISSN	1201-9712
DOIs	https://doi.org/10.1016/j.ijid.2021.12.260
Publication status	Published - 2022

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10.1016/j.ijid.2021.12.260Licence: CC BY-NC-ND

2022ijidS110Final published version, 82.7 KBLicence: CC BY-NC-ND

MOOD: MOnitoring Outbreak events for Disease surveillance in a data science context
Müller, R., Van Bortel, W., Müller, R. & van Kleef, E.
European Commission
1/01/20 → 31/12/24
Project: Research Project

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@article{cb0abe0727b04e23968feefa692a04b3,

title = "Mathematical modelling of COVID-19: a systematic review and quality assessment in the early epidemic response phase",

author = "I. Dhaoui and {Van Bortel}, W. and E. Arsevska and C. Hautefeuille and Alonso, {S. Tablado} and Kleef, {E. V.}",

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doi = "10.1016/j.ijid.2021.12.260",

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T1 - Mathematical modelling of COVID-19: a systematic review and quality assessment in the early epidemic response phase

AU - Dhaoui, I.

AU - Van Bortel, W.

AU - Arsevska, E.

AU - Hautefeuille, C.

AU - Alonso, S. Tablado

AU - Kleef, E. V.

N1 - FTX; DOAJ; (CC BY-NC-ND 4.0)

PY - 2022

Y1 - 2022

U2 - 10.1016/j.ijid.2021.12.260

DO - 10.1016/j.ijid.2021.12.260

M3 - Meeting abstract in journal

SN - 1201-9712

VL - 116

SP - S110-S110

JO - International Journal of Infectious Diseases

JF - International Journal of Infectious Diseases

M1 - PS25.02

ER -

Mathematical modelling of COVID-19: a systematic review and quality assessment in the early epidemic response phase

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Projects

MOOD: MOnitoring Outbreak events for Disease surveillance in a data science context

Cite this