Md Nazmul Hassan1,2, Md Shahriar Mahmud3, Kaniz Fatema Nipa1, Md Kamrujjaman4,5. 1. Department of Mathematics and Statistics, Texas Tech University, Lubbock, Texas, USA. 2. Department of Sciences and Mathematics, Schreiner University, Kerrville, Texas, USA. 3. Department of Computer Science and Engineering, State University of Bangladesh, Dhaka 1205, Bangladesh. 4. Department of Mathematics, University of Dhaka, Dhaka 1000, Bangladesh. 5. Department of Mathematics and Statistics, University of Calgary, Calgary, T2N 1N4, AB, Canada.
Abstract
BACKGROUND: Response to the unprecedented COVID-19 outbreak needs to be augmented in Texas, USA, where the first 5 cases were reported on March 6, 2020, were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas. METHODS: Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas and WHO Coronavirus Disease (COVID-19) Dashboard. Four-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection case in Texas. Since the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak. RESULTS: The estimated mean basic reproduction number of COVID-19 in Texas is predicted 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May of 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available,or this vaccination program fails for some reason in this area. CONCLUSION: Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels of Texas, thereby emphasizing promoting more coordinated and disciplined actions by both policymakers and the population to contain its devastating impact.
BACKGROUND: Response to the unprecedented COVID-19 outbreak needs to be augmented in Texas, USA, where the first 5 cases were reported on March 6, 2020, were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas. METHODS: Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas and WHO Coronavirus Disease (COVID-19) Dashboard. Four-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection case in Texas. Since the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak. RESULTS: The estimated mean basic reproduction number of COVID-19 in Texas is predicted 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May of 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available,or this vaccination program fails for some reason in this area. CONCLUSION: Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels of Texas, thereby emphasizing promoting more coordinated and disciplined actions by both policymakers and the population to contain its devastating impact.
Authors: Abdullah Al Mamun; Muhammad Khalilur Rahman; Qing Yang; Taslima Jannat; Anas A Salameh; Syed Ali Fazal Journal: Front Public Health Date: 2022-07-04
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Authors: Stacia M DeSantis; Luis G León-Novelo; Michael D Swartz; Ashraf S Yaseen; Melissa A Valerio-Shewmaker; Yashar Talebi; Frances A Brito; Jessica A Ross; Harold W Kohl; Sarah E Messiah; Steve H Kelder; Leqing Wu; Shiming Zhang; Kimberly A Aguillard; Michael O Gonzalez; Onyinye S Omega-Njemnob; David Lakey; Jennifer A Shuford; Stephen Pont; Eric Boerwinkle Journal: PLoS One Date: 2022-09-09 Impact factor: 3.752