scholarly journals Impact of vaccine supplies and delays on optimal control of the COVID-19 pandemic: mapping interventions for the Philippines

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Carlo Delfin S. Estadilla ◽  
Joshua Uyheng ◽  
Elvira P. de Lara-Tuprio ◽  
Timothy Robin Teng ◽  
Jay Michael R. Macalalag ◽  
...  
Keyword(s):  
Optimal Control ◽  
Optimal Strategy ◽  
Minimum Principle ◽  
Treatment Strategies ◽  
Optimal Strategies ◽  
The Philippines ◽  
Case Detection ◽  
Local Data ◽  
Vaccine Administration ◽  
Precautionary Measures

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 $$>99\%$$ > 99 % 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 $$25\%$$ 25 % , 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 $$18\%$$ 18 % 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. Graphic Abstract

scholarly journals Modelling Optimal Control of In-Host HIV Dynamics Using Different Control Strategies

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Purity Ngina ◽  
Rachel Waema Mbogo ◽  
Livingstone S. Luboobi
Keyword(s):  
Optimal Control ◽  
Deterministic Model ◽  
Control Strategies ◽  
Treatment Strategies ◽  
Optimal Strategies ◽  
Hiv Treatment ◽  
Sub Saharan Africa ◽  
System Control ◽  
Hiv Dynamics

HIV is one of the major causes of deaths, especially in Sub-Saharan Africa. In this paper, an in vivo deterministic model of differential equations is presented and analyzed for HIV dynamics. Optimal control theory is applied to investigate the key roles played by the various HIV treatment strategies. In particular, we establish the optimal strategies for controlling the infection using three treatment regimes as the system control variables. We have applied Pontryagin’s Maximum Principle in characterizing the optimality control, which then has been solved numerically by applying the Runge-Kutta forth-order scheme. The numerical results indicate that an optimal controlled treatment strategy would ensure significant reduction in viral load and also in HIV transmission. It is also evident from the results that protease inhibitor plays a key role in virus suppression; this is not to underscore the benefits accrued when all the three drug regimes are used in combination.

scholarly journals Optimal Control Model of Tumor Treatment with Oncolytic Virus and MEK Inhibitor

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yongmei Su ◽  
Chen Jia ◽  
Ying Chen
Keyword(s):  
Optimal Control ◽  
Cancer Cells ◽  
Oncolytic Virus ◽  
Tumor Therapy ◽  
Treatment Strategies ◽  
Optimal Strategies ◽  
Mek Inhibitor ◽  
Mitogen Activated Protein Kinase ◽  
Mitogen Activated Protein ◽  
Negative Effect

Tumors are a serious threat to human health. The oncolytic virus is a kind of tumor killer virus which can infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. Mathematical models can help us to understand the tumor-virus dynamics and find better treatment strategies. This paper gives a new mathematical model of tumor therapy with oncolytic virus and MEK inhibitor. Stable analysis was given. Because mitogen-activated protein kinase (MEK) can not only lead to greater oncolytic virus infection into cancer cells, but also limit the replication of the virus, in order to provide the best dosage of MEK inhibitors and balance the positive and negative effect of the inhibitors, we put forward an optimal control problem of the inhibitor. The optimal strategies are given by theory and simulation.

scholarly journals Optimal, near-optimal, and robust epidemic control

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Dylan H. Morris ◽  
Fernando W. Rossine ◽  
Joshua B. Plotkin ◽  
Simon A. Levin
Keyword(s):  
Robust Control ◽  
Disease Control ◽  
Epidemic Model ◽  
Optimal Strategy ◽  
Policy Design ◽  
Optimal Strategies ◽  
Economic Costs ◽  
Short Period ◽  
Intervention Policy ◽  
Pharmaceutical Interventions

AbstractIn the absence of drugs and vaccines, policymakers use non-pharmaceutical interventions such as social distancing to decrease rates of disease-causing contact, with the aim of reducing or delaying the epidemic peak. These measures carry social and economic costs, so societies may be unable to maintain them for more than a short period of time. Intervention policy design often relies on numerical simulations of epidemic models, but comparing policies and assessing their robustness demands clear principles that apply across strategies. Here we derive the theoretically optimal strategy for using a time-limited intervention to reduce the peak prevalence of a novel disease in the classic Susceptible-Infectious-Recovered epidemic model. We show that broad classes of easier-to-implement strategies can perform nearly as well as the theoretically optimal strategy. But neither the optimal strategy nor any of these near-optimal strategies is robust to implementation error: small errors in timing the intervention produce large increases in peak prevalence. Our results reveal fundamental principles of non-pharmaceutical disease control and expose their potential fragility. For robust control, an intervention must be strong, early, and ideally sustained.

scholarly journals Improving the criteria for choosing the strategies in management by geotechnical systems

2019 ◽  
Vol 109 ◽  
pp. 00048
Author(s):  
Yevhen Lapshyn ◽  
Robert Molchanov ◽  
Borys Blyuss ◽  
Nataliia Osadcha
Keyword(s):  
Game Theory ◽  
Optimal Strategy ◽  
Optimal Strategies ◽  
Mineral Deposits ◽  
Underground Space ◽  
Infrastructure Development ◽  
Main Indicator ◽  
Geological Conditions ◽  
Geological Faults

The conclusion has been made about the necessity to choose the optimal strategies for management by geotechnical systems, based on the analysis of geological faults, which are the main indicator of the mining and geological conditions that characterize the mineral deposits, as well as on the parameters for the infrastructure development of the underground space. The methodological peculiarity of solving the problems set is the use of game theory with modified criteria of Wald, maximax and Savage, since the manifestation of specific geological faults is probabilistic in nature. When choosing the optimal strategy, the average linear deviations of gains or risks are taken into account.

Pontryagin maximum principle and second order optimality conditions for optimal control problems governed by 2D nonlocal Cahn–Hilliard–Navier–Stokes equations

Analysis ◽  
2020 ◽  
Vol 40 (3) ◽  
pp. 127-150
Author(s):  
Tania Biswas ◽  
Sheetal Dharmatti ◽  
Manil T. Mohan
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Stokes Equations ◽  
Minimum Principle ◽  
Immiscible Fluids ◽  
Second Order ◽  
Navier Stokes ◽  
Distributed Optimal Control ◽  
Navier Stokes Equations

AbstractIn this paper, we formulate a distributed optimal control problem related to the evolution of two isothermal, incompressible, immiscible fluids in a two-dimensional bounded domain. The distributed optimal control problem is framed as the minimization of a suitable cost functional subject to the controlled nonlocal Cahn–Hilliard–Navier–Stokes equations. We describe the first order necessary conditions of optimality via the Pontryagin minimum principle and prove second order necessary and sufficient conditions of optimality for the problem.

Co-Evolutionary Algorithm between Helicopter and Submarine

2015 ◽  
Vol 719-720 ◽  
pp. 1229-1235
Author(s):  
Ying Chun Chen ◽  
Xian Hua Wang
Keyword(s):  
Evolutionary Algorithm ◽  
Optimal Strategy ◽  
Theoretical Foundation ◽  
Optimal Strategies ◽  
Evaluation Methods ◽  
Movement Model ◽  
Fitness Evaluation ◽  
Detection Model ◽  
Ocean Environment

A co-evolutionary algorithm is proposed for the play between a submarine and a helicopter equipped with dipping sonar. First, the theoretical foundation of co-evolution is elaborated. The movement model of helicopter and submarine, the detection model of dipping sonar under certain ocean environment are established. After defining the strategies of helicopter and submarine and fitness evaluation methods, the process of co-evolutionary algorithm is described. The optimal strategy of helicopter after helicopter evolution, and the optimal strategies of both helicopter and submarine after co-evolution are given

scholarly journals Optimal control of acute myeloid leukaemia

2018 ◽  
Author(s):  
Jesse A Sharp ◽  
Alexander P Browning ◽  
Tarunendu Mapder ◽  
Kevin Burrage ◽  
Matthew J Simpson
Keyword(s):  
Optimal Control ◽  
Immune Response ◽  
Acute Myeloid Leukaemia ◽  
Myeloid Leukaemia ◽  
Cell Model ◽  
Control Strategies ◽  
Treatment Strategies ◽  
Numerical Convergence ◽  
Stem Cell Model ◽  
Acute Myeloid

AbstractAcute myeloid leukaemia (AML) is a blood cancer affecting haematopoietic stem cells. AML is routinely treated with chemotherapy, and so it is of great interest to develop optimal chemotherapy treatment strategies. In this work, we incorporate an immune response into a stem cell model of AML, since we find that previous models lacking an immune response are inappropriate for deriving optimal control strategies. Using optimal control theory, we produce continuous controls and bang-bang controls, corresponding to a range of objectives and parameter choices. Through example calculations, we provide a practical approach to applying optimal control using Pontryagin’s Maximum Principle. In particular, we describe and explore factors that have a profound influence on numerical convergence. We find that the convergence behaviour is sensitive to the method of control updating, the nature of the control, and to the relative weighting of terms in the objective function. All codes we use to implement optimal control are made available.

scholarly journals Optimal Control of a Dengue-Dengvaxia Model: Comparison Between Vaccination and Vector Control

2021 ◽  
Vol 9 (1) ◽  
pp. 198-212
Author(s):  
Cheryl Q. Mentuda
Keyword(s):  
Optimal Control ◽  
Vector Control ◽  
Basic Reproduction Number ◽  
Human Population ◽  
Model Comparison ◽  
Reproduction Number ◽  
Control Strategies ◽  
Minimum Principle ◽  
Transmitted Disease ◽  
The Basic Reproduction Number

Abstract Dengue is the most common mosquito-borne viral infection transmitted disease. It is due to the four types of viruses (DENV-1, DENV-2, DENV-3, DENV-4), which transmit through the bite of infected Aedes aegypti and Aedes albopictus female mosquitoes during the daytime. The first globally commercialized vaccine is Dengvaxia, also known as the CYD-TDV vaccine, manufactured by Sanofi Pasteur. This paper presents a Ross-type epidemic model to describe the vaccine interaction between humans and mosquitoes using an entomological mosquito growth population and constant human population. After establishing the basic reproduction number ℛ0, we present three control strategies: vaccination, vector control, and the combination of vaccination and vector control. We use Pontryagin’s minimum principle to characterize optimal control and apply numerical simulations to determine which strategies best suit each compartment. Results show that vector control requires shorter time applications in minimizing mosquito populations. Whereas vaccinating the primary susceptible human population requires a shorter time compared to the secondary susceptible human.

Sign in / Sign up

Export Citation Format

Share Document