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SUMMARY:Prof. Scott Sheffield (Massachusetts Institute of Technology)
DTSTART:20210210T123000Z
DTEND:20210210T133000Z
DTSTAMP:20260423T005723Z
UID:tmc-dls/9
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/tmc-dls/9/">
 Pandemics and paradox</a>\nby Prof. Scott Sheffield (Massachusetts Institu
 te of Technology) as part of TMC Distinguished Lecture Series\n\n\nAbstrac
 t\nIn one of the simplest epidemic models\, one lets p_n denote the number
  of new infections during week n and assumes that (during the early stages
  of the epidemic) p_{n+1} = R_0  p_n  c_n where  c_n  measures the “frac
 tion of usual contact” that takes place between people during the nth we
 ek. Within this simplistic model\, intermittent strategies (taking  c_n  s
 mall some weeks and large other weeks) lead to lower infection rates than 
 consistent strategies with the same total amount of contact.\n\nBut what h
 appens in more life-like models (such as SEIR and its network-based varian
 ts)? What factors cause intermittent strategies to outperform consistent s
 trategies? What changes when there are multiple subpopulations with differ
 ent controls? I will discuss some work with public health researchers that
  explores these questions for simple examples. Some of the models are coun
 terintuitive: the strategy one expects to be “best possible” turns out
  to be “worst possible” and vice versa.\n
LOCATION:https://researchseminars.org/talk/tmc-dls/9/
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