Managing bed capacity and timing of interventions: a COVID-19 model considering behavior and underreporting

Victoria May P. Mendoza; Renier Mendoza; Youngsuk Ko; Jongmin Lee; Eunok Jung; Victoria May P. Mendoza; Renier Mendoza; Youngsuk Ko; Jongmin Lee; Eunok Jung

doi:10.3934/math.2023114

AIMS Mathematics

2023, Volume 8, Issue 1: 2201-2225. doi: 10.3934/math.2023114

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Managing bed capacity and timing of interventions: a COVID-19 model considering behavior and underreporting

1.
Department of Mathematics, Konkuk University, Seoul 05029, Korea
2.
Institute of Mathematics, University of the Philippines Diliman, Quezon City 1101, Philippines

Received: 06 August 2022 Revised: 06 October 2022 Accepted: 20 October 2022 Published: 31 October 2022
MSC : 65K05, 90C26, 92-10, 92D30

We develop a mathematical model considering behavioral changes and underreporting to describe the first major COVID-19 wave in Metro Manila, Philippines. Key parameters are fitted to the cumulative cases in the capital from March to September 2020. A bi-objective optimization problem is formulated that allows for the easing of restrictions at an earlier time and minimizes the number of additional beds ensuring sufficient capacity in healthcare facilities. The well-posedness of the model and stability of the disease-free equilibria are established. Simulations show that if the behavior was changed one to four weeks earlier before the easing of restrictions, cumulative cases can be reduced by up to 55% and the peak delayed by up to four weeks. If reporting is increased threefold in the first three months of the estimation period, cumulative cases can be reduced by 61% by September 2020. Among the Pareto optimal solutions, the peak of cases is lowest if strict restrictions were eased on May 20, 2020 and with at least 56 additional beds per day.
- COVID-19,
- mathematical model,
- behavior change,
- underreporting,
- Metro Manila,
- Philippines,
- community quarantine,
- bi-objective optimization
Citation: Victoria May P. Mendoza, Renier Mendoza, Youngsuk Ko, Jongmin Lee, Eunok Jung. Managing bed capacity and timing of interventions: a COVID-19 model considering behavior and underreporting[J]. AIMS Mathematics, 2023, 8(1): 2201-2225. doi: 10.3934/math.2023114

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Abstract

We develop a mathematical model considering behavioral changes and underreporting to describe the first major COVID-19 wave in Metro Manila, Philippines. Key parameters are fitted to the cumulative cases in the capital from March to September 2020. A bi-objective optimization problem is formulated that allows for the easing of restrictions at an earlier time and minimizes the number of additional beds ensuring sufficient capacity in healthcare facilities. The well-posedness of the model and stability of the disease-free equilibria are established. Simulations show that if the behavior was changed one to four weeks earlier before the easing of restrictions, cumulative cases can be reduced by up to 55% and the peak delayed by up to four weeks. If reporting is increased threefold in the first three months of the estimation period, cumulative cases can be reduced by 61% by September 2020. Among the Pareto optimal solutions, the peak of cases is lowest if strict restrictions were eased on May 20, 2020 and with at least 56 additional beds per day.

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