About: Disease modeling for public health: added value, challenges, and institutional constraints

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Disease modeling for public health: added value, challenges, and institutional constraints
Creator	Kretzschmar, Mirjam
topic	covid:153e4d9cbd7a73873997625991a079fc229b1633#this
Source	PMC
abstract	Public health policymakers face increasingly complex questions and decisions and need to deal with an increasing quantity of data and information. For policy advisors to make use of scientific evidence and to assess available intervention options effectively and therefore indirectly for those deciding on and implementing public health policies, mathematical modeling has proven to be a useful tool. In some areas, the use of mathematical modeling for public health policy support has become standard practice at various levels of decision-making. To make use of this tool effectively within public health organizations, it is necessary to provide good infrastructure and ensure close collaboration between modelers and policymakers. Based on experience from a national public health institute, we discuss the strategic requirements for good modeling practice for public health. For modeling to be of maximal value for a public health institute, the organization and budgeting of mathematical modeling should be transparent, and a long-term strategy for how to position and develop mathematical modeling should be in place.
has issue date	2019-11-28(xsd:dateTime)
bibo:doi	10.1057/s41271-019-00206-0
bibo:pmid	31780754
has license	cc-by
sha1sum (hex)	153e4d9cbd7a73873997625991a079fc229b1633
schema:url	https://doi.org/10.1057/s41271-019-00206-0
resource representing a document's title	Disease modeling for public health: added value, challenges, and institutional constraints
has PubMed Central identifier	PMC7041603
has PubMed identifier	31780754
schema:publication	J Public Health Policy
resource representing a document's body	covid:153e4d9cbd7a73873997625991a079fc229b1633#body_text
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