arXiv subjects

Renier Mendoza

Publications and source records attributed to Renier Mendoza.

3 recordsLinked to original sources

arXiv2026

Cost-Effective Strategies for Infectious Diseases: A Multi-Objective Framework with an Interactive Dashboard

During an infectious disease outbreak, policymakers must balance medical costs with social and economic burdens and seek interventions that minimize both. To support this decision-making process, we developed a framework that integrates multi-objective optimization, cost-benefit analysis, and an interactive dashboard. This platform enables users to input cost parameters and immediately obtain a cost-optimal intervention strategy. We applied this framework to the early outbreak of COVID-19 in South Korea. The results showed that cost-optimal solutions for costs per infection ranging from 4,410 USD to 361,000 USD exhibited a similar pattern. This indicates that once the cost per infection is specified, our approach generates the corresponding cost-optimal solution without additional calculations. Our framework supports decision-making by accounting for trade-offs between policy and infection costs. It delivers rapid optimization and cost-benefit analysis results, enabling timely and informed decision-making during the critical phases of a pandemic.

math.OC↗

arXiv2026

Balancing Economic Cost and Disease Impact: Optimization Models for Wolbachia-Based Dengue Control

Dengue, which affects millions of people each year, is one of the most common diseases transmitted by infected \textit{Aedes aegypti} mosquitoes. In the Philippines, the annual economic cost of dengue infections is estimated at around PHP 17 billion. Previous studies have shown that controlling the population of mosquitoes capable of transmitting the dengue virus can effectively reduce dengue infection rates. This study explores the use of Wolbachia as a strategy for dengue control by targeting mosquitoes. Since the release of Wolbachia-infected mosquitoes involves substantial costs, careful planning is necessary to balance disease control with the associated economic burden. To address this, we propose a mathematical model that captures the dynamics of releasing Wolbachia-carrying mosquitoes and the transmission of dengue in a population. We formulate single- and multi-objective optimization frameworks to minimize the economic costs associated with releasing Wolbachia-infected mosquitoes and the hospitalization costs resulting from dengue infections. This study aims to provide insights into the practical application of Wolbachia-based interventions for controlling dengue transmission. While the analysis is grounded in the Philippine context, the approach is general enough to be applicable to other dengue-endemic countries.

math.OC↗

arXiv2025

Nature-inspired optimization, the Philippine Eagle, and cosmological parameter estimation

Precise and accurate estimation of cosmological parameters is crucial for understanding the Universe's dynamics and addressing cosmological tensions. In this methods paper, we explore bio-inspired metaheuristic algorithms, including the Improved Multi-Operator Differential Evolution scheme and the Philippine Eagle Optimization Algorithm (PEOA), alongside the relatively known genetic algorithm, for cosmological parameter estimation. Using mock data that underlay a true fiducial cosmology, we test the viability of each optimization method to recover the input cosmological parameters with confidence regions generated by bootstrapping on top of optimization. We compare the results with Markov chain Monte Carlo (MCMC) in terms of accuracy and precision, and show that PEOA performs comparably well under the specific circumstances provided. Understandably, Bayesian inference and optimization serve distinct purposes, but comparing them highlights the potential of nature-inspired algorithms in cosmological analysis, offering alternative pathways to explore parameter spaces and validate standard results.

astro-ph.CO↗