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A data-validated temporary immunity model of COVID-19 spread in Michigan.
Pell, Bruce; Johnston, Matthew D; Nelson, Patrick.
  • Pell B; Department of Mathematics & Computer Science, Lawrence Technological University, 21000 W 10 Mile Rd, Southfield, MI 48075, USA.
  • Johnston MD; Department of Mathematics & Computer Science, Lawrence Technological University, 21000 W 10 Mile Rd, Southfield, MI 48075, USA.
  • Nelson P; Department of Mathematics & Computer Science, Lawrence Technological University, 21000 W 10 Mile Rd, Southfield, MI 48075, USA.
Math Biosci Eng ; 19(10): 10122-10142, 2022 07 18.
Article in English | MEDLINE | ID: covidwho-1974985
ABSTRACT
We introduce a distributed-delay differential equation disease spread model for COVID-19 spread. The model explicitly incorporates the population's time-dependent vaccine uptake and incorporates a gamma-distributed temporary immunity period for both vaccination and previous infection. We validate the model on COVID-19 cases and deaths data from the state of Michigan and use the calibrated model to forecast the spread and impact of the disease under a variety of realistic booster vaccine strategies. The model suggests that the mean immunity duration for individuals after vaccination is 350 days and after a prior infection is 242 days. Simulations suggest that both high population-wide adherence to vaccination mandates and a more-than-annually frequency of booster doses will be required to contain outbreaks in the future.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Math Biosci Eng Year: 2022 Document Type: Article Affiliation country: Mbe.2022474

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Math Biosci Eng Year: 2022 Document Type: Article Affiliation country: Mbe.2022474