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Impact of vaccine supplies and delays on optimal control of the COVID-19 pandemic: mapping interventions for the Philippines.
Estadilla, Carlo Delfin S; Uyheng, Joshua; de Lara-Tuprio, Elvira P; Teng, Timothy Robin; Macalalag, Jay Michael R; Estuar, Maria Regina Justina E.
  • Estadilla CDS; Department of Mathematics, Ateneo de Manila University, Katipunan Ave., Brgy. Loyola Heights, 1102, Quezon City, Philippines. cestadilla@ateneo.edu.
  • Uyheng J; Department of Psychology, Ateneo de Manila University, Quezon City, Philippines.
  • de Lara-Tuprio EP; Department of Mathematics, Ateneo de Manila University, Katipunan Ave., Brgy. Loyola Heights, 1102, Quezon City, Philippines.
  • Teng TR; Department of Mathematics, Ateneo de Manila University, Katipunan Ave., Brgy. Loyola Heights, 1102, Quezon City, Philippines.
  • Macalalag JMR; Department of Mathematics, Caraga State University, Butuan City, Philippines.
  • Estuar MRJE; Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City, Philippines.
Infect Dis Poverty ; 10(1): 107, 2021 Aug 09.
Article in English | MEDLINE | ID: covidwho-1350155
ABSTRACT

BACKGROUND:

Around the world, controlling the COVID-19 pandemic requires national coordination of multiple intervention strategies. As vaccinations are globally introduced into the repertoire of available interventions, it is important to consider how changes in the local supply of vaccines, including delays in administration, may be addressed through existing policy levers. This study aims to identify the optimal level of interventions for COVID-19 from 2021 to 2022 in the Philippines, which as a developing country is particularly vulnerable to shifting assumptions around vaccine availability. Furthermore, we explore optimal strategies in scenarios featuring delays in vaccine administration, expansions of vaccine supply, and limited combinations of interventions.

METHODS:

Embedding our work within the local policy landscape, we apply optimal control theory to the compartmental model of COVID-19 used by the Philippine government's pandemic surveillance platform and introduce four controls (a) precautionary measures like community quarantines, (b) detection of asymptomatic cases, (c) detection of symptomatic cases, and (d) vaccinations. The model is fitted to local data using an L-BFGS minimization procedure. Optimality conditions are identified using Pontryagin's minimum principle and numerically solved using the forward-backward sweep method.

RESULTS:

Simulation results indicate that early and effective implementation of both precautionary measures and symptomatic case detection is vital for averting the most infections at an efficient cost, resulting in [Formula see text] reduction of infections compared to the no-control scenario. Expanding vaccine administration capacity to 440,000 full immunizations daily will reduce the overall cost of optimal strategy by [Formula see text], while allowing for a faster relaxation of more resource-intensive interventions. Furthermore, delays in vaccine administration require compensatory increases in the remaining policy levers to maintain a minimal number of infections. For example, delaying the vaccines by 180 days (6 months) will result in an [Formula see text] increase in the cost of the optimal strategy.

CONCLUSION:

We conclude with practical insights regarding policy priorities particularly attuned to the Philippine context, but also applicable more broadly in similar resource-constrained settings. We emphasize three key takeaways of (a) sustaining efficient case detection, isolation, and treatment strategies; (b) expanding not only vaccine supply but also the capacity to administer them, and; (c) timeliness and consistency in adopting policy measures.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: Asia Language: English Journal: Infect Dis Poverty Year: 2021 Document Type: Article Affiliation country: S40249-021-00886-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: Asia Language: English Journal: Infect Dis Poverty Year: 2021 Document Type: Article Affiliation country: S40249-021-00886-5