Influenza H1N1 has been found to exhibit oscillatory levels of incidence in large pop- ulations. Clear peaks for influenza H1N1 are observed in several countries including Vietnam each year [M. F. Boni, B. H. Manh, P....Influenza H1N1 has been found to exhibit oscillatory levels of incidence in large pop- ulations. Clear peaks for influenza H1N1 are observed in several countries including Vietnam each year [M. F. Boni, B. H. Manh, P. Q. Thai, J. Farrar, T. Hien, N. T. Hien, N. Van Kinh and P. Horby, Modelling the progression of pandemic influenza A （H1N1） in Vietnam and the opportunities for reassortment with other influenza viruses, BMC Med. 7 （2009） 43, Doi： 10.1186/1741-7015-%43]. So it is important to study seasonal forces and factors which can affect the transmission of this disease. This paper studies an SIRS epidemic model with seasonal vaccination rate. This SIRS model has a unique disease-free solution （DFS）. The value Ro, the basic reproduction number is obtained when the vaccination is a periodic function. Stability results for the DFS are obtained when R0 〈 1. The disease persists in the population and remains endemic if R0 〉 1. Also when R0 〉 1 existence of a nonzero periodic solution is proved. These results obtained for our model when the vaccination strategy is a non-constant time-dependent function.展开更多
Aims The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years.Three of the problems that have been ...Aims The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years.Three of the problems that have been identified are(i)the absence of frequency-dependence,which is important for long-term coexistence of species,(ii)the need to take unmeasured(often unmeasurable)variables influencing individual performance into account(e.g.spatial variation in soil nutrients or pathogens)and(iii)the need to separate measurement error from biological variation.Methods We modified the classical Lotka–Volterra competition models to address these limitations.We fitted eight alternative models to pin-point cover data on Festuca ovina and Agrostis capillaris over 3 years in an herbaceous plant community in Denmark.A Bayesian modeling framework was used to ascertain whether the model amendments improve the performance of the models and increase their ability to predict community dynamics and to test hypotheses.Important Findings Inclusion of frequency-dependence and measurement error,but not unmeasured variables,improved model performance greatly.Our results emphasize the importance of comparing alternative models in quantitative studies of plant community dynamics.Only by considering possible alternative models can we identify the forces driving community assembly and change,and improve our ability to predict the behavior of plant communities.展开更多
文摘Influenza H1N1 has been found to exhibit oscillatory levels of incidence in large pop- ulations. Clear peaks for influenza H1N1 are observed in several countries including Vietnam each year [M. F. Boni, B. H. Manh, P. Q. Thai, J. Farrar, T. Hien, N. T. Hien, N. Van Kinh and P. Horby, Modelling the progression of pandemic influenza A （H1N1） in Vietnam and the opportunities for reassortment with other influenza viruses, BMC Med. 7 （2009） 43, Doi： 10.1186/1741-7015-%43]. So it is important to study seasonal forces and factors which can affect the transmission of this disease. This paper studies an SIRS epidemic model with seasonal vaccination rate. This SIRS model has a unique disease-free solution （DFS）. The value Ro, the basic reproduction number is obtained when the vaccination is a periodic function. Stability results for the DFS are obtained when R0 〈 1. The disease persists in the population and remains endemic if R0 〉 1. Also when R0 〉 1 existence of a nonzero periodic solution is proved. These results obtained for our model when the vaccination strategy is a non-constant time-dependent function.
文摘Aims The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years.Three of the problems that have been identified are(i)the absence of frequency-dependence,which is important for long-term coexistence of species,(ii)the need to take unmeasured(often unmeasurable)variables influencing individual performance into account(e.g.spatial variation in soil nutrients or pathogens)and(iii)the need to separate measurement error from biological variation.Methods We modified the classical Lotka–Volterra competition models to address these limitations.We fitted eight alternative models to pin-point cover data on Festuca ovina and Agrostis capillaris over 3 years in an herbaceous plant community in Denmark.A Bayesian modeling framework was used to ascertain whether the model amendments improve the performance of the models and increase their ability to predict community dynamics and to test hypotheses.Important Findings Inclusion of frequency-dependence and measurement error,but not unmeasured variables,improved model performance greatly.Our results emphasize the importance of comparing alternative models in quantitative studies of plant community dynamics.Only by considering possible alternative models can we identify the forces driving community assembly and change,and improve our ability to predict the behavior of plant communities.
