tetano
Editor, Senior Moderator
PLoS Comput Biol. 2019 Sep 16;15(9):e1007111. doi: 10.1371/journal.pcbi.1007111. [Epub ahead of print]
[h=1]Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints.[/h] Venkatramanan S[SUP]1[/SUP], Chen J[SUP]1[/SUP], Fadikar A[SUP]2,[/SUP][SUP]3[/SUP], Gupta S[SUP]4[/SUP], Higdon D[SUP]2,[/SUP][SUP]3[/SUP], Lewis B[SUP]1[/SUP], Marathe M[SUP]1,[/SUP][SUP]5[/SUP], Mortveit H[SUP]1,[/SUP][SUP]6[/SUP], Vullikanti A[SUP]1,[/SUP][SUP]5[/SUP].
[h=3]Author information[/h] 1 Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America. 2 Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America. 3 Fralin Life Science Institute, Virginia Tech, Blacksburg, Virginia, United States of America. 4 Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, United States of America. 5 Department of Computer Science, University of Virginia, Charlottesville, Virginia, United States of America. 6 Department of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, United States of America.
[h=3]Abstract[/h] 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 DOI: 10.1371/journal.pcbi.1007111
[h=1]Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints.[/h] Venkatramanan S[SUP]1[/SUP], Chen J[SUP]1[/SUP], Fadikar A[SUP]2,[/SUP][SUP]3[/SUP], Gupta S[SUP]4[/SUP], Higdon D[SUP]2,[/SUP][SUP]3[/SUP], Lewis B[SUP]1[/SUP], Marathe M[SUP]1,[/SUP][SUP]5[/SUP], Mortveit H[SUP]1,[/SUP][SUP]6[/SUP], Vullikanti A[SUP]1,[/SUP][SUP]5[/SUP].
[h=3]Author information[/h] 1 Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia, United States of America. 2 Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America. 3 Fralin Life Science Institute, Virginia Tech, Blacksburg, Virginia, United States of America. 4 Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, United States of America. 5 Department of Computer Science, University of Virginia, Charlottesville, Virginia, United States of America. 6 Department of Engineering Systems and Environment, University of Virginia, Charlottesville, Virginia, United States of America.
[h=3]Abstract[/h] 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 DOI: 10.1371/journal.pcbi.1007111