The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters—such as the number and placement of sur...

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Pubblicato in:PLoS Comput Biol
Autori principali: Cheng, Qu, Collender, Philip A., Heaney, Alexandra K., Li, Xintong, Dasan, Rohini, Li, Charles, Lewnard, Joseph A., Zelner, Jonathan L., Liang, Song, Chang, Howard H., Waller, Lance A., Lopman, Benjamin A., Yang, Changhong, Remais, Justin V.
Natura: Artigo
Lingua:Inglês
Pubblicazione: Public Library of Science 2020
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Research Article
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7744064/
https://ncbi.nlm.nih.gov/pubmed/33275606
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1008477
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