Mathematical models for assessing vaccination scenarios in several provinces in Indonesia

N. Nuraini; K. K. Sukandar; P. Hadisoemarto; H. Susanto; A. I. Hasan; N. Sumarti

doi:10.1016/j.idm.2021.09.002

Mathematical models for assessing vaccination scenarios in several provinces in Indonesia

N. Nuraini, K. K. Sukandar, P. Hadisoemarto, H. Susanto, A. I. Hasan, N. Sumarti

Mathematics

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

To mitigate casualties from the COVID-19 outbreak, this study aims at assessing the optimal vaccination scenarios, considering several existing healthcare conditions and assumptions, by developing SIQRD (Susceptible-Infected-Quarantine-Recovery-Death) models for Jakarta, West Java, and Banten, in Indonesia. The models include an age-structured dynamic transmission model that naturally allows for different treatments among different age groups of the population. The simulation results show that the timing and period of the vaccination should be well planned and prioritizing particular age groups will give a significant impact on the total number of casualties.

Original language	British English
Pages (from-to)	1236-1258
Number of pages	23
Journal	Infectious Disease Modelling
Volume	6
DOIs	https://doi.org/10.1016/j.idm.2021.09.002
State	Published - Jan 2021

Keywords

Age groups
COVID-19
Healthcare capacity
SIQRD model
Vaccination strategy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.idm.2021.09.002

Cite this

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title = "Mathematical models for assessing vaccination scenarios in several provinces in Indonesia",

abstract = "To mitigate casualties from the COVID-19 outbreak, this study aims at assessing the optimal vaccination scenarios, considering several existing healthcare conditions and assumptions, by developing SIQRD (Susceptible-Infected-Quarantine-Recovery-Death) models for Jakarta, West Java, and Banten, in Indonesia. The models include an age-structured dynamic transmission model that naturally allows for different treatments among different age groups of the population. The simulation results show that the timing and period of the vaccination should be well planned and prioritizing particular age groups will give a significant impact on the total number of casualties.",

keywords = "Age groups, COVID-19, Healthcare capacity, SIQRD model, Vaccination strategy",

author = "N. Nuraini and Sukandar, {K. K.} and P. Hadisoemarto and H. Susanto and Hasan, {A. I.} and N. Sumarti",

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doi = "10.1016/j.idm.2021.09.002",

language = "British English",

volume = "6",

pages = "1236--1258",

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T1 - Mathematical models for assessing vaccination scenarios in several provinces in Indonesia

AU - Nuraini, N.

AU - Sukandar, K. K.

AU - Hadisoemarto, P.

AU - Susanto, H.

AU - Hasan, A. I.

AU - Sumarti, N.

N1 - Funding Information: NN and KKS gratefully acknowledges the financial support provided by PDUPT 2021. Funding Information: NN and KKS gratefully acknowledges the financial support provided by PDUPT 2021. Publisher Copyright: © 2021 The Authors

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N2 - To mitigate casualties from the COVID-19 outbreak, this study aims at assessing the optimal vaccination scenarios, considering several existing healthcare conditions and assumptions, by developing SIQRD (Susceptible-Infected-Quarantine-Recovery-Death) models for Jakarta, West Java, and Banten, in Indonesia. The models include an age-structured dynamic transmission model that naturally allows for different treatments among different age groups of the population. The simulation results show that the timing and period of the vaccination should be well planned and prioritizing particular age groups will give a significant impact on the total number of casualties.

AB - To mitigate casualties from the COVID-19 outbreak, this study aims at assessing the optimal vaccination scenarios, considering several existing healthcare conditions and assumptions, by developing SIQRD (Susceptible-Infected-Quarantine-Recovery-Death) models for Jakarta, West Java, and Banten, in Indonesia. The models include an age-structured dynamic transmission model that naturally allows for different treatments among different age groups of the population. The simulation results show that the timing and period of the vaccination should be well planned and prioritizing particular age groups will give a significant impact on the total number of casualties.

KW - Age groups

KW - COVID-19

KW - Healthcare capacity

KW - SIQRD model

KW - Vaccination strategy

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DO - 10.1016/j.idm.2021.09.002

M3 - Article

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SP - 1236

EP - 1258

JO - Infectious Disease Modelling

JF - Infectious Disease Modelling

ER -

Mathematical models for assessing vaccination scenarios in several provinces in Indonesia

Abstract

Keywords

UN SDGs

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