Tuesday, June 15 at 02:15pm (PDT)Tuesday, June 15 at 10:15pm (BST)Wednesday, June 16 06:15am (KST)
SMB2021 FollowTuesday (Wednesday) during the "CT04" time block.
Tuğba Akman Yildiz
University of Turkish Aeronautical Association
"Modeling vaccination against COVID-19 in Turkey with effective reproduction number"
A mathematical model with the compartments of susceptible, exposed, mildly infected individuals, patients staying in intensive care units (ICUs) and ventilation units is developed and fitted with the daily reported symptomatic cases, deaths, patients staying in ICUs and ventilation units in Turkey for the period 11 March-31 May 2020. Then, this model has been modified after May 31, 2020 due to updated public restrictions and a time-dependent contact rate is derived via the effective reproduction number Rt, which is calculated using the daily reported cases, to capture the dynamics of the outbreak until vaccination. With the start of vaccination on January 13, 2021, the model is extended and COVID-19 outbreak in Turkey is successfully simulated and it is observed that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.
Joshua C. Macdonald
University of Louisiana at Lafayette
"Modeling COVID-19 outbreaks in United States with distinct testing, lockdown speed and fatigue rates"
Each state in the United States exhibited a unique response to the COVID-19 outbreak, along with variable levels of testing, leading to different actual case burdens in the country. In this study, via per-capita testing dependent ascertainment rates, along with case and death data, we fit a minimal epidemic model for each state. We estimate infection-level responsive lockdown entry and exit rates (representing government and behavioral reaction), along with the true number of cases as of May 31, 2020. Ultimately we provide error corrected estimates for commonly used metrics such as infection fatality ratio and overall case ascertainment for all 55 states and territories considered, along with the United States in aggregate, in order to correlate outbreak severity with first wave intervention attributes and suggest potential management strategies for future outbreaks. We observe a theoretically predicted inverse proportionality relation between outbreak size and lockdown rate, with scale dependent on the underlying reproduction number and simulations suggesting a critical population quarantine ``half-life'' of 30 days independent of other model parameters.
Tarleton State University Department of Mathematics
"Dynamics of Eastern Equine Encephalitis Infection Rates: A Mathematical Approach"
The Eastern Equine Encephalitis Virus (EEEV) is an erratic and deadly neurological disease that spans across the northeastern coast of the United States. To determine the rate at which the virus is spread between the Black-Tailed Mosquito (Culiseta melanura) and select avian species we began by analyzing the migration patterns of both the mosquito and the avian species. It was found that certain species of avians shared similar, or even identical, flight patterns with the Black-Tailed Mosquito. Through this research, we develop and analyze a system of Ordinary Differential Equations (ODEs) to gain insight into how and when transmission of the virus to avians is at its highest. We incorporate a host stage-structured model where the avian host group is split into two categories, adults and young-of-the-year birds (YOY). Using this we explored the extent to which fluctuations occurred in transmission rates according to host/vector abundances, mosquito biting rate, and type of host. We evaluate the hypothesis that YOY avians are more readily exposed to the mosquito vector as they lack a defense mechanism, unlike their adult counterpart using the compartmental model.