Stochastic Periodic Solution of a Susceptible-Infective Epidemic Model in a Polluted Environment under Environmental Fluctuation

It is well known that the pollution and environmental fluctuations may seriously affect the outbreak of infectious diseases (e.g., measles). Therefore, understanding the association between the periodic outbreak of an infectious disease and noise and pollution still needs further development. Here we consider a stochastic susceptible-infective (SI) epidemic model in a polluted environment, which incorporates both environmental fluctuations as well as pollution. First, the existence of the global positive solution is discussed. Thereafter, the sufficient conditions for the nontrivial stochastic periodic solution and the boundary periodic solution of disease extinction are derived, respectively. Numerical simulation is also conducted in order to support the theoretical results. Our study shows that (i) large intensity noise may help the control of periodic outbreak of infectious disease; (ii) pollution may significantly affect the peak level of infective population and cause adverse health effects on the exposed population. These results can help increase the understanding of periodic outbreak patterns of infectious diseases.

[1]  S. Riley,et al.  Five challenges for stochastic epidemic models involving global transmission , 2014, Epidemics.

[2]  Jitao Sun,et al.  Global stability of an SI epidemic model with feedback controls , 2014, Appl. Math. Lett..

[3]  Bing Liu,et al.  Dynamics of an SI epidemic model with external effects in a polluted environment , 2012 .

[4]  Ke Wang,et al.  Stochastic periodic solutions of stochastic differential equations driven by Lévy process , 2015 .

[5]  K. Gopalsamy Stability and Oscillations in Delay Differential Equations of Population Dynamics , 1992 .

[6]  O. Bjørnstad,et al.  The dynamics of measles in sub-Saharan Africa , 2008, Nature.

[7]  Meijing Shan,et al.  Periodic solution of a stochastic HBV infection model with logistic hepatocyte growth , 2017, Appl. Math. Comput..

[8]  Juan Li,et al.  Persistence and ergodicity of plant disease model with markov conversion and impulsive toxicant input , 2017, Commun. Nonlinear Sci. Numer. Simul..

[9]  Lifan Chen,et al.  Impact of climate change on human infectious diseases: Empirical evidence and human adaptation. , 2016, Environment international.

[10]  Zhien Ma,et al.  Persistence and periodic orbits for an sis model in a polluted environment , 2004 .

[11]  Roumen Anguelov,et al.  Dynamics of SI epidemic with a demographic Allee effect. , 2015, Theoretical population biology.

[12]  Ke Wang,et al.  Persistence and extinction of a single-species population system in a polluted environment with random perturbations and impulsive toxicant input , 2012 .

[13]  Weiming Wang,et al.  Periodic behavior in a FIV model with seasonality as well as environment fluctuations , 2017, J. Frankl. Inst..

[14]  C. Viboud,et al.  A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks , 2015, Epidemics.

[15]  Douglas W Dockery,et al.  Health effects of particulate air pollution. , 2009, Annals of epidemiology.

[16]  Fengying Wei,et al.  A stochastic single-species population model with partial pollution tolerance in a polluted environment , 2017, Appl. Math. Lett..

[17]  J BOGDANOWICZ,et al.  [MEASLES AND WHOOPING COUGH]. , 1963, Pediatria polska.

[18]  Yun Kang,et al.  A stochastic SIRS epidemic model with nonlinear incidence rate , 2017, Appl. Math. Comput..

[19]  H. Kan,et al.  PM2.5 in Beijing – temporal pattern and its association with influenza , 2014, Environmental Health.

[20]  Y. Kim,et al.  Air pollution and hemorrhagic fever with renal syndrome in South Korea: an ecological correlation study , 2013, BMC Public Health.

[21]  Sanling Yuan,et al.  Analysis of Transmission and Control of Tuberculosis in Mainland China, 2005–2016, Based on the Age-Structure Mathematical Model , 2017, International journal of environmental research and public health.

[22]  Ming Wang,et al.  The effects of weather conditions on measles incidence in Guangzhou, Southern China , 2014, Human vaccines & immunotherapeutics.

[23]  PERIODIC SOLUTIONS OF STOCHASTIC DELAY DIFFERENTIAL EQUATIONS AND APPLICATIONS TO LOGISTIC EQUATION AND NEURAL NETWORKS , 2013 .

[24]  Chao Liu,et al.  Is short‐term exposure to ambient fine particles associated with measles incidence in China? A multi‐city study , 2017, Environmental research.

[25]  Jeffrey Shaman,et al.  Absolute humidity modulates influenza survival, transmission, and seasonality , 2009, Proceedings of the National Academy of Sciences.

[26]  Zhidong Teng,et al.  Dynamics for a class of stochastic SIS epidemic models with nonlinear incidence and periodic coefficients , 2017 .

[27]  Sanling Yuan,et al.  Stochastic periodic solution of a non-autonomous toxic-producing phytoplankton allelopathy model with environmental fluctuation , 2017, Commun. Nonlinear Sci. Numer. Simul..

[28]  Sixu Yang,et al.  Assessment for the impact of dust events on measles incidence in western China , 2017 .

[29]  Ahmed Alsaedi,et al.  Nontrivial periodic solution of a stochastic non-autonomous SISV epidemic model , 2016 .

[30]  X. Mao,et al.  Stochastic Differential Equations and Applications , 1998 .

[31]  Measles and Whooping Cough: Part II , 1937 .

[32]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[33]  Ahmed Alsaedi,et al.  Periodic solution for a stochastic non-autonomous competitive Lotka–Volterra model in a polluted environment ☆ , 2017 .

[34]  D. O’Regan,et al.  Periodic solution for a non-autonomous Lotka–Volterra predator–prey model with random perturbation , 2015 .

[35]  Wenyi Zhang,et al.  The impact of ambient fine particles on influenza transmission and the modification effects of temperature in China: A multi-city study , 2016, Environment International.

[36]  Jiao Li,et al.  Stability of a stochastic SEIS model with saturation incidence and latent period , 2017 .

[37]  John Steel,et al.  Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature , 2007, PLoS pathogens.

[38]  H. Bedford,et al.  Measles , 1889, BMJ.

[39]  Desmond J. Higham,et al.  An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations , 2001, SIAM Rev..