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ノーベル化学賞の吉野さん 理事長務める大阪の研究施設に出勤

ノーベル化学賞に選ばれた吉野彰さんが、受賞決定後初めて、自身が理事長を務める大阪府内のリチウムイオン電池の研究施設に出勤し、研究への変わらぬ意欲を示しました。

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Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints.

著者 Venkatramanan S , Chen J , Fadikar A , Gupta S , Higdon D , Lewis B , Marathe M , Mortveit H , Vullikanti A
PLoS Comput Biol.2019 Sep 16 ; 15(9):e1007111.
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Prophylactic interventions such as vaccine allocation are some of the most effective public health policy planning tools. The supply of vaccines, however, is limited and an important challenge is to optimally allocate the vaccines to minimize epidemic impact. This resource allocation question (which we refer to as VaccIntDesign) has multiple dimensions: when, where, to whom, etc. Most of the existing literature in this topic deals with the latter (to whom), proposing policies that prioritize individuals by age and disease risk. However, since seasonal influenza spread has a typical spatial trend, and due to the temporal constraints enforced by the availability schedule, the when and where problems become equally, if not more, relevant. In this paper, we study the VaccIntDesign problem in the context of seasonal influenza spread in the United States. We develop a national scale metapopulation model for influenza that integrates both short and long distance human mobility, along with realistic data on vaccine uptake. We also design GreedyAlloc, a greedy algorithm for allocating the vaccine supply at the state level under temporal constraints and show that such a strategy improves over the current baseline of pro-rata allocation, and the improvement is more pronounced for higher vaccine efficacy and moderate flu season intensity. Further, the resulting strategy resembles a ring vaccination applied spatiallyacross the US.
PMID: 31525184 [PubMed - as supplied by publisher]
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