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Shifts in the spatiotemporal dynamics of schistosomiasis: a case study in Anhui Province, China.

Hu Y, Li R, Chen Y, Gao F, Wang Q, Zhang S, Zhang Z, Jiang Q - PLoS Negl Trop Dis (2015)

Bottom Line: Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997-2010 in Anhui Province, East China.The POPs associated with these oscillatory components showed that the pattern near the Yangtze River varied markedly and that the disease risk appeared to evolve in a Southwest/Northeast orientation.The POP coefficients showed decreasing tendency until 2001, then increasing during 2002-2005 and decaying afterwards.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.

ABSTRACT

Background: The Chinese national surveillance system showed that the risk of Schistosoma japonicum infection fluctuated temporally. This dynamical change might indicate periodicity of the disease, and its understanding could significantly improve targeted interventions to reduce the burden of schistosomiasis. The goal of this study was to investigate how the schistosomiasis risk varied temporally and spatially in recent years.

Methodology/principal findings: Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997-2010 in Anhui Province, East China. A multivariate autoregressive model, combined with principal oscillation pattern (POP) analysis, was used to evaluate the spatio-temporal variation of schistosomiasis risk. Results showed that the temporal changes of schistosomiasis risk in the study area could be decomposed into two sustained damped oscillatory modes with estimated period of approximately 2.5 years. The POPs associated with these oscillatory components showed that the pattern near the Yangtze River varied markedly and that the disease risk appeared to evolve in a Southwest/Northeast orientation. The POP coefficients showed decreasing tendency until 2001, then increasing during 2002-2005 and decaying afterwards.

Conclusion: The POP analysis characterized the variations of schistosomiasis risk over space and time and demonstrated that the disease mainly varied temporally along the Yangtze River. The schistosomiasis risk declined periodically with a temporal fluctuation. Whether it resulted from previous national control strategies on schistosomiasis needs further investigations.

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Related in: MedlinePlus

Schematic diagram of the time evolution of POP coefficients αt(k) with an initial value α0 = (αr, αi) = (0,1) (From [19]).The complex number αt rotates in slightly more than eight time steps anticlockwise once around the origin. ω is a constant angle in the complex plane. The e-folding time τ, for which /ατ/ = 1/e is marked by an open circle. The amplitude /αt/, in the perspective of epidemiology, corresponds to magnitude of schistosomiasis risk in our study.
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pntd.0003715.g002: Schematic diagram of the time evolution of POP coefficients αt(k) with an initial value α0 = (αr, αi) = (0,1) (From [19]).The complex number αt rotates in slightly more than eight time steps anticlockwise once around the origin. ω is a constant angle in the complex plane. The e-folding time τ, for which /ατ/ = 1/e is marked by an open circle. The amplitude /αt/, in the perspective of epidemiology, corresponds to magnitude of schistosomiasis risk in our study.

Mentions: The eigen-decomposition of M yields the dominant modes of variability from the multivariate dataset in terms of relaxation and oscillation modes. The vectors wk are called the principal oscillation patterns or system normal modes, while the left singular vector vk (the columns of matrix V) are called adjoint bases. The elements of the time series αt = V*Zt are known as POP coefficients. In the spatio-temporal setting, wk provides a spatial map of variability of the observed field. If the eigenvalue λk (the element of diagonal matrix L) is complex, then (where and k = 1,…,m), which can be written in polar form as and . Then, λk = γk(COS(ωk)+i sin(ωk)), where and . Thus, the POP coefficients evolve according to,. Under the condition, γk≤1; αt evolves as a damped spiral in the complex plane (Fig 2) with a characteristic damping rate γk and frequency ωk, for k = 1,…,m. Notice that ωk here is an angle in the complex plane. In the case that λk is real with module less than 1, αt corresponds to damped non-oscillatory modes. In both cases, the amplitude of αt(k) (i.e.,) decreases exponentially with time t and can be characterized by the “e-folding time” (the time needed to reduce the initial amplitude α0(k) to α0(k)/e), τk = -1/log(γk).


Shifts in the spatiotemporal dynamics of schistosomiasis: a case study in Anhui Province, China.

Hu Y, Li R, Chen Y, Gao F, Wang Q, Zhang S, Zhang Z, Jiang Q - PLoS Negl Trop Dis (2015)

Schematic diagram of the time evolution of POP coefficients αt(k) with an initial value α0 = (αr, αi) = (0,1) (From [19]).The complex number αt rotates in slightly more than eight time steps anticlockwise once around the origin. ω is a constant angle in the complex plane. The e-folding time τ, for which /ατ/ = 1/e is marked by an open circle. The amplitude /αt/, in the perspective of epidemiology, corresponds to magnitude of schistosomiasis risk in our study.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400088&req=5

pntd.0003715.g002: Schematic diagram of the time evolution of POP coefficients αt(k) with an initial value α0 = (αr, αi) = (0,1) (From [19]).The complex number αt rotates in slightly more than eight time steps anticlockwise once around the origin. ω is a constant angle in the complex plane. The e-folding time τ, for which /ατ/ = 1/e is marked by an open circle. The amplitude /αt/, in the perspective of epidemiology, corresponds to magnitude of schistosomiasis risk in our study.
Mentions: The eigen-decomposition of M yields the dominant modes of variability from the multivariate dataset in terms of relaxation and oscillation modes. The vectors wk are called the principal oscillation patterns or system normal modes, while the left singular vector vk (the columns of matrix V) are called adjoint bases. The elements of the time series αt = V*Zt are known as POP coefficients. In the spatio-temporal setting, wk provides a spatial map of variability of the observed field. If the eigenvalue λk (the element of diagonal matrix L) is complex, then (where and k = 1,…,m), which can be written in polar form as and . Then, λk = γk(COS(ωk)+i sin(ωk)), where and . Thus, the POP coefficients evolve according to,. Under the condition, γk≤1; αt evolves as a damped spiral in the complex plane (Fig 2) with a characteristic damping rate γk and frequency ωk, for k = 1,…,m. Notice that ωk here is an angle in the complex plane. In the case that λk is real with module less than 1, αt corresponds to damped non-oscillatory modes. In both cases, the amplitude of αt(k) (i.e.,) decreases exponentially with time t and can be characterized by the “e-folding time” (the time needed to reduce the initial amplitude α0(k) to α0(k)/e), τk = -1/log(γk).

Bottom Line: Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997-2010 in Anhui Province, East China.The POPs associated with these oscillatory components showed that the pattern near the Yangtze River varied markedly and that the disease risk appeared to evolve in a Southwest/Northeast orientation.The POP coefficients showed decreasing tendency until 2001, then increasing during 2002-2005 and decaying afterwards.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.

ABSTRACT

Background: The Chinese national surveillance system showed that the risk of Schistosoma japonicum infection fluctuated temporally. This dynamical change might indicate periodicity of the disease, and its understanding could significantly improve targeted interventions to reduce the burden of schistosomiasis. The goal of this study was to investigate how the schistosomiasis risk varied temporally and spatially in recent years.

Methodology/principal findings: Parasitological data were obtained through repeated cross-sectional surveys that were carried out during 1997-2010 in Anhui Province, East China. A multivariate autoregressive model, combined with principal oscillation pattern (POP) analysis, was used to evaluate the spatio-temporal variation of schistosomiasis risk. Results showed that the temporal changes of schistosomiasis risk in the study area could be decomposed into two sustained damped oscillatory modes with estimated period of approximately 2.5 years. The POPs associated with these oscillatory components showed that the pattern near the Yangtze River varied markedly and that the disease risk appeared to evolve in a Southwest/Northeast orientation. The POP coefficients showed decreasing tendency until 2001, then increasing during 2002-2005 and decaying afterwards.

Conclusion: The POP analysis characterized the variations of schistosomiasis risk over space and time and demonstrated that the disease mainly varied temporally along the Yangtze River. The schistosomiasis risk declined periodically with a temporal fluctuation. Whether it resulted from previous national control strategies on schistosomiasis needs further investigations.

Show MeSH
Related in: MedlinePlus