Dataset Information

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour's model.

ABSTRACT:

Background

Schistosomiasis japonica, caused by infection with Schistosoma japonicum, is still recognized as a major public health problem in the Peoples' Republic of China. Mathematical modelling of schistosomiasis transmission has been undertaken in order to assess and project the effects of various control strategies for elimination of the disease. Seasonal fluctuations in transmission may have the potential to impact on the population dynamics of schistosomiasis, yet no model of S. japonicum has considered such effects. In this paper, we characterize the transmission dynamics of S. japonicum using a modified version of Barbour's model to account for seasonal variation (SV), and investigate the effectiveness of the control strategy adopted in Liaonan village of Xingzi county, Jiangxi Province.

Methods

We use mathematical tools for stability analysis of periodic systems and derive expressions for the basic reproduction ratio of S. japonicum in humans; we parameterise such expressions with surveillance data to investigate the conditions for persistence or elimination of the disease in the study village. We perform numerical simulations and parametric sensitivity analysis to understand local transmission conditions and compare values of the basic reproductive ratio with and without seasonal fluctuations.

Results

The explicit formula of the basic reproduction ratio for the SV-modified Barbour's model is derived. Results show that the value of the basic reproduction ratio, R0, of Liaonan village, Xingzi county is located between 1.064 and 1.066 (very close to 1), for schistosomiasis transmission during 2006 to 2010, after intensification of control efforts.

Conclusions

Our modified version of the Barbour model to account for seasonal fluctuations in transmission has the potential to provide better estimations of infection risk than previous models. Ignoring seasonality tends to underestimate R0 values albeit only marginally. In the absence of simultaneous R0 estimations for villages not under control interventions (such villages do not currently exist in China), it is difficult to assess whether control strategies have had a substantial impact on levels of transmission, as the parasite population would still be able to maintain itself at an endemic level, highlighting the difficulties faced by elimination efforts.

SUBMITTER: Gao SJ

PROVIDER: S-EPMC3667069 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour's model.

Gao Shu-Jing SJ He Yu-Ying YY Liu Yu-Jiang YJ Yang Guo-Jing GJ Zhou Xiao-Nong XN

Parasites & vectors 20130516

<h4>Background</h4>Schistosomiasis japonica, caused by infection with Schistosoma japonicum, is still recognized as a major public health problem in the Peoples' Republic of China. Mathematical modelling of schistosomiasis transmission has been undertaken in order to assess and project the effects of various control strategies for elimination of the disease. Seasonal fluctuations in transmission may have the potential to impact on the population dynamics of schistosomiasis, yet no model of S. ja ...[more]

PMID: 23680335

Similar Datasets

Project description:BackgroundSchistosomiasis is one of the most common parasitic diseases affecting millions of humans and animals worldwide. Understanding the signal transduction pathways and the molecular basis of reproductive regulation in schistosomes is critically important for developing new strategies for preventing and treating these infections. Syk kinases regulate the proliferation, differentiation, morphogenesis, and survival of various types of cells and have been identified in invertebrates. Tyrosine kinase 4 (TK4), a member of the Syk kinase family, plays a pivotal role in gametogenesis in S. mansoni, affecting the development of the testis and ovaries in this parasite. The role of TK4, however, in the reproduction of S. japonicum is poorly understood.MethodsHere, the complete coding sequence of TK4 gene in S. japonicum (SjTK4) was cloned and characterized. The expression of SjTK4 was analyzed at different life-cycle stages and in various tissues of S. japonicum by qPCR. Piceatannol, a Syk kinase inhibitor, was applied to S. japonicum in vitro. The piceatannol-induced morphological changes of the parasites were observed using confocal laser scanning microscopy and the alterations in important egg-shell synthesis-related genes were examined using qPCR analyses.ResultsSjTK4 mRNA was differentially expressed throughout the life-cycle of S. japonicum. SjTK4 mRNA was highly expressed in the ovary and testis of S. japonicum, with the level of gene expression significantly higher in males than in females. The expression levels of some important egg-shell synthesis related genes were higher in the piceatannol-treated groups than in the vehicle-treated control group and the number of eggs and germ cells also decreased in a concentration-dependent manner. Importantly, large pore-like structures can be found in the testis and ovaries of males and females after treating with piceatannol.ConclusionThe results suggest that SjTK4 may play an important role in regulating gametogenesis of S. japonicum. The findings may help better understand the fundamental biology of S. japonicum. Moreover, the effect of S. japonicum treatment by piceatannol provides us with a new idea that inhibition of SjTK4 signaling pathway can effectively retard the development of the testis and ovaries.

Dataset Information

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour's model.

Background

Methods

Results

Conclusions

Publications

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour's model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets