Forecasting COVID-19 cases in the Philippines using various mathematical models

Buhat, Christian Alvin H.; Bpb, Dela Cruz; Efo, Felix; Eb, Gemida; Mamplata, Jonathan B.

doi:10.1101/2020.10.07.20208421

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…[40] [41]. Such models have been instrumental in forecasting COVID-19 cases, providing projections essential for policy-makers and healthcare professionals [42] [43] [44].…”

Section: Disease Offering Vital Insights Into Its Spread and Evolutio...mentioning

confidence: 99%

Unraveling COVID-19: Descriptive Analytics in a Middle-Income Country, Paving the Path Forward

Bansilan,

Rabajante

2023

Preprint

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The outbreak of COVID-19 unleashed an unprecedented global pandemic, leaving a profound impact on lives and economies worldwide. Recognizing its severity, the World Health Organization swiftly declared it a public health emergency of international concern. Tragically, the Philippines reported the first death case outside China, leading to a surge in cases following the first instance of local transmission. In response to this crisis, collaborative efforts have been underway to control the disease and minimize its health and socio-economic impacts. The COVID-19 epidemic curve holds vital insights into the history of exposure, transmission, testing, tracing, social distancing measures, community lockdowns, quarantine, isolation, and treatment, offering a comprehensive perspective on the nation's response. One approach to gaining crucial insights is through meticulous analysis of available datasets, empowering us to inform future strategies and responses effectively. This paper aims to provide descriptive data analytics of the COVID-19 pandemic in the Philippines, summarizing the country's fight by visualizing epidemiological and mobility datasets, revisiting scientific papers and news articles, and creating a timeline of the key issues faced during the pandemic. By leveraging these multifaceted analyses, policymakers and health authorities can make informed decisions to enhance preparedness, expand inter-agency cooperation, and combat future public health crises effectively. This study seeks to serve as a valuable resource, guiding nations worldwide in comprehending and responding to the challenges posed by COVID-19 and beyond.

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“…[40] [41]. Such models have been instrumental in forecasting COVID-19 cases, providing projections essential for policy-makers and healthcare professionals [42] [43] [44].…”

Section: Disease Offering Vital Insights Into Its Spread and Evolutio...mentioning

confidence: 99%

Unraveling COVID-19: Descriptive Analytics in a Middle-Income Country, Paving the Path Forward

Bansilan,

Rabajante

2023

Preprint

View full text Add to dashboard Cite

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“…They also prepared a survey about the data mining tools applied for tracking and preventing COVID-19. Torres et al (2020) studied COVID-19 infection cases to forecast daily cases using numerous mathematical models. Their results verified that the autoregressive integrated moving average model has the highest prediction accuracy value.…”

Section: Related Workmentioning

confidence: 99%

Predicting the severity of COVID‐19 patients using a multi‐threaded evolutionary feature selection algorithm

et al. 2022

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The COVID-19 pandemic has huge effects on the global community and an extreme burden on health systems. There are more than 185 million confirmed cases and 4 million deaths as of July 2021. Besides, the exponential rise in COVID-19 cases requires a quick prediction of the patients' severity for better treatment. In this study, we propose a Multi-threaded Genetic feature selection algorithm combined with Extreme Learning Machines (MG-ELM) to predict the severity level of the COVID-19 patients. We conduct a set of experiments on a recently published real-world dataset.We reprocess the dataset via feature construction to improve the learning performance of the algorithm. Upon comprehensive experiments, we report the most impactful features and symptoms for predicting the patients' severity level. Moreover, we investigate the effects of multi-threaded implementation with statistical analysis. In order to verify the efficiency of MG-ELM, we compare our results with traditional and state-of-the-art techniques. The proposed algorithm outperforms other algorithms in terms of prediction accuracy.

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“…COVID-19 intervention qualitative analysis vaccination contact tracing [3] studied COVID-19 infection cases to forecast daily cases using numerous mathematical models, including the Susceptible-Exposed-Infected-Recovered (SEIR) model. Arcede et al [4] also considered an SEIR-type model of COVID-19, emphasizing that the infected can be either symptomatic or not.…”

Section: Introductionmentioning

confidence: 99%

Qualitative analysis of a Mathematical model of COVID-19 with intervention strategies in the Philippines

Apdo,

Paluga

2023

Jambura J. Biomath.

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This paper focuses on the development of a mathematical model to analyze the transmission dynamics of COVID-19 in the Philippines, where the pandemic has significantly impacted the population despite several quarantine measures, testing, contact tracing, and vaccinations. The model considers the impact of contact tracing and vaccination campaigns on disease transmission. The model is analyzed qualitatively and numerically, and the results show that increasing the contact tracing rate and vaccination rate can effectively reduce the reproduction number of the virus. The disease-free equilibrium is found to be locally asymptotically stable when the basic reproduction number is less than one, and the disease-endemic equilibrium is locally asymptotically stable when the basic reproduction number is greater than one. The study suggests that a contact tracing rate greater than 0.08847694 is required to effectively manage the transmission of COVID-19 in the target population. These findings provide insights for policymakers and public health officials in developing effective strategies to mitigate the impact of the pandemic.

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Forecasting COVID-19 cases in the Philippines using various mathematical models

Cited by 5 publications

References 24 publications

Unraveling COVID-19: Descriptive Analytics in a Middle-Income Country, Paving the Path Forward

Unraveling COVID-19: Descriptive Analytics in a Middle-Income Country, Paving the Path Forward

Predicting the severity of COVID‐19 patients using a multi‐threaded evolutionary feature selection algorithm

Qualitative analysis of a Mathematical model of COVID-19 with intervention strategies in the Philippines

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