title: Dynamical immunization strategy for seasonal epidemics.
abstract: The topic of finding an effective strategy to halt virus in a complex network is of current interest. We propose an immunization strategy for seasonal epidemics that occur periodically. Based on the local information of the infection status from the previous epidemic season, the selection of vaccinated nodes is optimized gradually. The evolution of vaccinated nodes during iterations demonstrates that the immunization tends to locate in both global hubs and local hubs. We analyze the epidemic prevalence using a heterogeneous mean-field method, and we present numerical simulations of our model. This immunization performs better than some other previously known strategies. Our work highlights an alternative direction in immunization for seasonal epidemics.
authors.affiliation: LMIB and School of Mathematics and Systems Science, Beihang University, Beijing 100191, China.
authors.forename: Shu
authors.initials: S
authors.lastname: Yan
authors.affiliation: LMIB and School of Mathematics and Systems Science, Beihang University, Beijing 100191, China.
authors.forename: Shaoting
authors.initials: S
authors.lastname: Tang
authors.affiliation: LMIB and School of Mathematics and Systems Science, Beihang University, Beijing 100191, China.
authors.forename: Sen
authors.initials: S
authors.lastname: Pei
authors.affiliation: School of Mathematical Sciences, Peking University, Beijing 100871, China.
authors.forename: Shijin
authors.initials: S
authors.lastname: Jiang
authors.affiliation: LMIB and School of Mathematics and Systems Science, Beihang University, Beijing 100191, China.
authors.forename: Zhiming
authors.initials: Z
authors.lastname: Zheng
mesh_terms: D003198:Computer Simulation; D058872:Epidemics / Q000517:prevention & control*; D007114:Immunization / Q000379:methods*; D008954:Models, Biological; D015995:Prevalence; D012008:Recurrence; D012621:Seasons; D014777:Virus Diseases / Q000517:prevention & control*