A COVID-19 vaccine effectiveness model using the susceptible-exposed-infectious-recovered model

• Published in: Healthcare analytics (New York, N.Y.) Vol. 4; p. 100269
• Main Authors: Saharan, Sabariah, Tee, Cunzhe
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.12.2023; Elsevier
• Subjects: COVID-19; Susceptible-exposed-infectious-recovered; COVID-19; Susceptible-exposed-infectious-recovered
• ISSN: 2772-4425; 2772-4425
• DOI: 10.1016/j.health.2023.100269

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused the start of the COVID-19 outbreak in the world, including Malaysia and Thailand. This study identifies the trend of the COVID-19 outbreak before and after the vaccination campaign by using the Susceptible-Exposed-Infectious-Recovered (SEIR) and Susceptible-Exposed-Infectious-Recovered-Vaccinated (SEIRV) models. Moreover, we predict the daily reported death and recovery cases using the SEIR model and Holt's linear trend method and then evaluate their performance. The data used in this study is real data from Malaysia and Thailand. The SEIRV model provides a comprehensive view of the efficacy of COVID-19 vaccinations in curbing the COVID-19 outbreak. This research reveals that the SEIR model outperforms Holt's linear trend method in predicting daily reported cases. •Use the susceptible-exposed-infectious-recovered model to analyze and predict the effectiveness of COVID-19 vaccines.•Use the susceptible-exposed-infectious-recovered model and Holt's linear trend method to analyze the daily reported death and recovery cases.•Show the efficacy of COVID-19 vaccinations in curbing the outbreak with the susceptible-exposed-infectious-recovered-vaccinated model.•Show susceptible-exposed-infectious-recovered model outperforms Holt's linear trend method in predicting daily reported cases.•The susceptible-exposed-infectious-recovered model outperforms Holt's linear trend method in predicting daily reported death cases.