Shapiro, Michael and DelgadoEckert, Edgar. (2012) Finding the probability of infection in an SIR network is NPHard. Mathematical biosciences, 240 (2). pp. 7784.
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Abstract
It is the purpose of this article to review results that have long been known to communications network engineers and have direct application to epidemiology on networks. A common approach in epidemiology is to study the transmission of a disease in a population where each individual is initially susceptible (S), may become infective (I) and then removed or recovered (R) and plays no further epidemiological role. Much of the recent work gives explicit consideration to the network of social interactions or diseasetransmitting contacts and attendant probability of transmission for each interacting pair. The state of such a network is an assignment of the values {S,I,R} to its members. Given such a network, an initial state and a particular susceptible individual, we would like to compute their probability of becoming infected in the course of an epidemic. It turns out that this and related problems are NPhard. In particular, it belongs in a class of problems for which no efficient algorithms for their solution are known. Moreover, finding an efficient algorithm for the solution of any problem in this class would entail a major breakthrough in computer science.
Faculties and Departments:  03 Faculty of Medicine > Bereich Kinder und Jugendheilkunde (Klinik) > Kinder und Jugendheilkunde (UKBB) 03 Faculty of Medicine > Departement Klinische Forschung > Bereich Kinder und Jugendheilkunde (Klinik) > Kinder und Jugendheilkunde (UKBB) 03 Faculty of Medicine > Departement Biomedical Engineering 

UniBasel Contributors:  DelgadoEckert, Edgar 
Item Type:  Article, refereed 
Article Subtype:  Research Article 
Publisher:  Elsevier 
ISSN:  00255564 
Note:  Publication type according to Uni Basel Research Database: Journal article 
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Last Modified:  02 Dec 2020 15:20 
Deposited On:  02 Dec 2020 15:20 
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