arXiv subjects

Vena Pearl Bongolan

Publications and source records attributed to Vena Pearl Bongolan.

6 recordsLinked to original sources

arXiv2026

Cascading Effects of the COVID-19 Pandemic on Barangays in the Philippines

The COVID-19 pandemic disrupted socio-economic and healthcare systems in the Philippines, significantly affecting barangays. This study analyzes the cascading effects of the COVID-19 pandemic on key aspects of a barangay, namely mobility, accessibility of public services, economic and financial health, food security, educational engagement, and physical health. It focuses on data from 2,122 Filipino households collected during May to June 2021 as part of the World Bank COVID-19 Households Survey. A Bayesian network model was constructed to programmatically map the conditional dependencies among these variables, utilizing Python libraries. Survey responses were grouped into common variables based on shared characteristics and standardized through z-score normalization to serve as nodes in the Bayesian network. By extending the Bayesian network into an influence diagram, the results will help identify interventions to guide local government units (LGUs) and policymakers in crafting tailored recovery programs and strategies that address impacts on physical health, economic and financial health, food security, public service access, mobility, and educational engagement. These efforts ultimately aim to enhance barangay resilience and preparedness for future public health crises. The results indicate that interventions aimed at boosting food production, stabilizing market prices, and expanding income opportunities are the most effective in improving community outcomes. This highlights the vital role of targeted economic and food security measures in mitigating the socio-economic impacts of the pandemic and offers valuable insights for shaping future response and recovery efforts.

econ.GN↗

arXiv2022

Sustainable Development Goal Target Interactions in the Philippines: A Two-Method Approach

In 2015, the United Nations adopted 17 Sustainable Development Goals (SDGs) with 169 targets for transformation toward a more sustainable future by 2030. This study seeks to evaluate and analyze SDG target interactions in the Philippines to resolve conflicting targets, and prioritize targets that reinforce others and have no conflicts. To evaluate all 14196 target interactions, two methods are employed. First, experts with over five years of SDG-related experience evaluated interactions using a 7-point scale. Second, a non-parametric Spearman rank correlation is used on official indicator data with resulting coefficients serving as interaction scores. Interaction scores are then coded as synergies (interact positively), trade-offs (negatively) or non-classified (neutrally). Targets are also modelled as nodes and interactions as edges in graphs presented in sdginteractions.herokuapp.com. Results from the two methods were synthesized to formulate recommendations for concerned parties. This includes resolving negative intra-goal target interactions involving targets 3.1 'Reduce maternal mortality', 3.6 'Reduce road injuries and deaths', and 3.7 'Universal access to sexual and reproductive care, family planning, and education'. Ugly targets (at least one negative interaction) including target 3.6, 3.7, and 8.2 'Diversify, innovate, and upgrade for economic productivity' need to be resolved. Targets that reinforce their corresponding SDGs should be prioritized, including 1.1 'Eradicate extreme poverty', 4.2 'Equal access to quality pre-primary education', 6.2 'End open defecation and provide access to sanitation and hygiene', 8.1 'Sustainable economic growth', and 9.4 'Upgrade all industries and infrastructures for sustainability'. Beautiful targets (no negative interactions) should also be prioritized, including target 8.5 and 17.5 'Invest in least developed countries'.

cs.SI↗

arXiv2021

SDG Target Interactions: The Philippine Analysis of Indivisible and Cancelling Targets

The United Nations developed the 17 Sustainable Development Goals (SDGs), with 169 targets, to serve as a plan for solving the world's problems and achieving a more sustainable future. This is modeled as a graph with the targets as nodes, and with the interaction between targets as the edges of the graph. An exhaustive binary comparison is done to analyze the intra- and inter-goal target interactions, entailing over 14000 comparisons. The task is to assign a 'color' to an edge: positive (indivisible), zero (consistent) or negative (cancelling). This is done via a panel of experts who will evaluate the target interactions, through a web application that was developed for coloring the edges. This is an on-going study, and so far, of the 1256 edges colored, only 36 are cancelling (negative), or 2.86%; more than 97% are positive interactions. So far, the "most negative" interactions involve: "Climate Change"; "Life Below Water"; "Peace, Justice and Strong Institutions"; and "Decent Work and Economic Growth". Most useful for planning might be the 'graph of beautiful targets' feature, which shows target with non-negative interactions, and how they connect to each other. These are the targets that may be worked on simultaneously, and currently has more than 130 nodes. This study can help researchers analyze which targets enable or constrain each other, what mitigation can be done to avoid conflicts, and can be configured for sub-national or regional study. Web app at: http://sdg-interactions.herokuapp.com/

cs.SI↗

arXiv2021

COVID-19 Agent-Based Model with Multi-objective Optimization for Vaccine Distribution

Now that SARS-CoV-2 (COVID-19) vaccines are developed, it is very important to plan its distribution strategy. In this paper, we formulated a multi-objective linear programming model to optimize vaccine distribution and applied it to the agent-based version of our age-stratified and quarantine-modified SEIR with non-linear incidence rates (ASQ-SEIR-NLIR) compartmental model. Simulations were performed using COVID-19 data from Quezon City and results were analyzed under various scenarios: (1) no vaccination, (2) base vaccination (prioritizing essential workers and vulnerable population), (3) prioritizing mobile workforce, (4) prioritizing elderly, and (5) prioritizing mobile workforce and elderly; in terms of (a) reducing infection rates and (b) reducing mortality incidence. After 10 simulations on distributing 500,000 vaccine courses, results show that prioritizing mobile workforce minimizes further infections by 24.14%, which is better than other scenarios. On the other hand, prioritizing the elderly yields the highest protection (439%) for the Quezon City population compared to other scenarios. This could be due to younger people, when contracted the disease, has higher chances of recovery than the elderly. Thus, this leads to reduction of mortality cases.

q-bio.PE↗

arXiv2013

A Probabilistic Approach to Risk Mapping for Mt. Etna

We evaluate susceptibility to lava flows on Mt. Etna based on specially designed die-toss experiments using probabilities for type, time and place of activation from the volcano's 400-year recorded history and current studies on its known fractures and fissures. The types of activations were forcast using a table of probabilities for events, typed by duration and volume of ejecta. Lengths of time were represented by the number of activations to expect within a given time-frame, calculated assuming Poisson-distributed inter-arrival times for activations. Locations of future activations were forecast with a probability distribution function for activation probabilities. Most likely scenarios for risk and resulting topography were generated for Etna's next activation (average 7.76 years), the next 25, 50 and 100 years. Forecasts for areas most likely affected are in good agreement with previous risk studies made. Forecasts for risks of lava invasions, as well as future topographies might be a first. Threats to lifelines are also discussed.

cs.CE↗

arXiv2013

Metaheuristics in Flood Disaster Management and Risk Assessment

A conceptual area is divided into units or barangays, each was allowed to evolve under a physical constraint. A risk assessment method was then used to identify the flood risk in each community using the following risk factors: the area's urbanized area ratio, literacy rate, mortality rate, poverty incidence, radio/TV penetration, and state of structural and non-structural measures. Vulnerability is defined as a weighted-sum of these components. A penalty was imposed for reduced vulnerability. Optimization comparison was done with MatLab's Genetic Algorithms and Simulated Annealing; results showed 'extreme' solutions and realistic designs, for simulated annealing and genetic algorithm, respectively.

cs.AI↗