Analyzing the dynamics of COVID-19 transmission in select regions of the Philippines: A modeling approach to assess the impact of various tiers of community quarantines

The COVID-19 pandemic has significantly impacted communities worldwide, and effective management strategies are critical to reduce transmission rates and minimize the impact of the disease. In this study, we modeled and analyzed the COVID-19 transmission dynamics and derived relevant epidemiological values for three regions of the Philippines, namely, the National Capital Region (NCR), Davao City, and Baguio City, under different community quarantine implementations. The unique features and differences of these regions-of-interest were accounted for in simulating the disease spread and in estimating key epidemiological parameters fitted to the reported COVID-19 cases. Results support the robustness of the model formulated and provides insights into the effect of the government's implemented intervention protocols. With a forecasting feature, this modeling framework is beneficial for science-based decision support, policy making, and assessment for recent and future pandemics wherever regions-of-interest.

Authors

Institutions

Publication Details

Journal
Heliyon
Published
2024-10-17
DOI
https://doi.org/10.1016/j.heliyon.2024.e39330
Citations
2
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.79

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analyzing the dynamics of COVID-19 transmission in select regions of the Philippines: A modeling approach to assess the impact of various tiers of community quarantines

Jhunas Paul T. Viernes, Bryan S. Hernandez, May Anne Mata, Rey Audie S. Escosio et al.
2 citations
Heliyon
COVID-19 epidemiological studies
0.79
article

Analyzing the dynamics of COVID-19 transmission in select regions of the Philippines: A modeling approach to assess the impact of various tiers of community quarantines

Jhunas Paul T. Viernes, Bryan S. Hernandez, May Anne Mata, Rey Audie S. Escosio, Joel M. Addawe, El Veena Grace A Rosero, Rizavel C. Addawe, Carlene P. C. Pilar-Arceo, Victoria Mendoza, Aurelio A. de los Reyes V, Loreniel E. Añonuevo
article en
2 citations

Abstract

The COVID-19 pandemic has significantly impacted communities worldwide, and effective management strategies are critical to reduce transmission rates and minimize the impact of the disease. In this study, we modeled and analyzed the COVID-19 transmission dynamics and derived relevant epidemiological values for three regions of the Philippines, namely, the National Capital Region (NCR), Davao City, and Baguio City, under different community quarantine implementations. The unique features and differences of these regions-of-interest were accounted for in simulating the disease spread and in estimating key epidemiological parameters fitted to the reported COVID-19 cases. Results support the robustness of the model formulated and provides insights into the effect of the government's implemented intervention protocols. With a forecasting feature, this modeling framework is beneficial for science-based decision support, policy making, and assessment for recent and future pandemics wherever regions-of-interest.

HeliyonVol. 10(21)
University of Lisbon (PT), University of the Philippines Baguio (PH), University of the Philippines Mindanao (PH), Caraga State University (PH), University of Mindanao (PH), University of the Philippines Diliman (PH)
University of the Philippines, Philippine Council for Health Research and Development
Reduced inequalities
Openalex Percentile: Top 30%
COVID-19 epidemiological studies
0.79
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.