کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5102454 1480083 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Solving the patient zero inverse problem by using generalized simulated annealing
ترجمه فارسی عنوان
حل معکوس معکوس بیمار با استفاده از آنالیز شبیه سازی به طور کلی
کلمات کلیدی
مدل های اپیدمی، مورد شاخص، بیماری عفونی، بهینه سازی تصادفی،
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات فیزیک ریاضی
چکیده انگلیسی
Identifying patient zero - the initially infected source of a given outbreak - is an important step in epidemiological investigations of both existing and emerging infectious diseases. Here, the use of the Generalized Simulated Annealing algorithm (GSA) to solve the inverse problem of finding the source of an outbreak is studied. The classical disease natural histories susceptible-infected (SI), susceptible-infected-susceptible (SIS), susceptible-infected-recovered (SIR) and susceptible-infected-recovered-susceptible (SIRS) in a regular lattice are addressed. Both the position of patient zero and its time of infection are considered unknown. The algorithm performance with respect to the generalization parameter q̃v and the fraction ρ of infected nodes for whom infection was ascertained is assessed. Numerical experiments show the algorithm is able to retrieve the epidemic source with good accuracy, even when ρ is small, but present no evidence to support that GSA performs better than its classical version. Our results suggest that simulated annealing could be a helpful tool for identifying patient zero in an outbreak where not all cases can be ascertained.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 490, 15 January 2018, Pages 1513-1521
نویسندگان
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