Literature DB >> 1684260

On the application of mathematical models of schistosome transmission dynamics. I. Natural transmission.

M E Woolhouse1.   

Abstract

The many mathematical models of the transmission dynamics of schistosomes that have been published since 1965 have had little impact on field studies or on the design of schistosome control programmes. At least in part, this is due to limited interaction between theoretician and field worker, resulting in unrealistic models that are not easily applied to field data. This review aims to make explicit the assumptions and limitations of existing models and their relationships with field data. A basic model is described which considers the mean number of schistosomes per person and the prevalence of patent infections of snails. Various modifications to this model are introduced. These include: prepatent infections of snails; loss of infection of snails; the effects of snail population dynamics; the effects of miracidia and cercariae population dynamics; miracidia searching efficiency; reservoir hosts; heterogeneous patterns of transmission; seasonality; and predisposition to infection. Variation in levels of infection with age and the effects of acquired immunity to infection are also considered. Published models of schistosome transmission dynamics are reviewed within this framework. Approaches to the modelling of schistosome control measures are considered in a companion paper. It is suggested that future theoretical studies give greater attention to the details of snail population dynamics, heterogeneous patterns of transmission and the effects of acquired immunity. There is a need for field studies explicitly designed to provide estimates of transmission parameters and for studies of the epidemiological effects of acquired immunity.

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Year:  1991        PMID: 1684260     DOI: 10.1016/0001-706x(91)90077-w

Source DB:  PubMed          Journal:  Acta Trop        ISSN: 0001-706X            Impact factor:   3.112


  23 in total

1.  The consequences of uncertainty for the prediction of the effects of schistosomiasis control programmes.

Authors:  M S Chan
Journal:  Epidemiol Infect       Date:  1996-12       Impact factor: 2.451

2.  A new approach to modelling schistosomiasis transmission based on stratified worm burden.

Authors:  D Gurarie; C H King; X Wang
Journal:  Parasitology       Date:  2010-07-13       Impact factor: 3.234

Review 3.  Schistosomiasis in the People's Republic of China: the era of the Three Gorges Dam.

Authors:  Donald P McManus; Darren J Gray; Yuesheng Li; Zheng Feng; Gail M Williams; Donald Stewart; Jose Rey-Ladino; Allen G Ross
Journal:  Clin Microbiol Rev       Date:  2010-04       Impact factor: 26.132

Review 4.  Modeling the dynamics and control of transmission of Schistosoma japonicum and S. mekongi in Southeast Asia.

Authors:  Hirofumi Ishikawa; Hiroshi Ohmae
Journal:  Korean J Parasitol       Date:  2009-03-12       Impact factor: 1.341

5.  Observed reductions in Schistosoma mansoni transmission from large-scale administration of praziquantel in Uganda: a mathematical modelling study.

Authors:  Michael D French; Thomas S Churcher; Manoj Gambhir; Alan Fenwick; Joanne P Webster; Narcis B Kabatereine; Maria-Gloria Basáñez
Journal:  PLoS Negl Trop Dis       Date:  2010-11-23

6.  Effects of Snail Density on Growth, Reproduction and Survival of Biomphalaria alexandrina Exposed to Schistosoma mansoni.

Authors:  T D Mangal; S Paterson; A Fenton
Journal:  J Parasitol Res       Date:  2010-06-08

Review 7.  A research agenda for helminth diseases of humans: modelling for control and elimination.

Authors:  María-Gloria Basáñez; James S McCarthy; Michael D French; Guo-Jing Yang; Martin Walker; Manoj Gambhir; Roger K Prichard; Thomas S Churcher
Journal:  PLoS Negl Trop Dis       Date:  2012-04-24

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

Authors:  Shu-Jing Gao; Yu-Ying He; Yu-Jiang Liu; Guo-Jing Yang; Xiao-Nong Zhou
Journal:  Parasit Vectors       Date:  2013-05-16       Impact factor: 3.876

9.  Predicting the impact of long-term temperature changes on the epidemiology and control of schistosomiasis: a mechanistic model.

Authors:  Tara D Mangal; Steve Paterson; Andrew Fenton
Journal:  PLoS One       Date:  2008-01-16       Impact factor: 3.240

10.  Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities.

Authors:  David Gurarie; Edmund Y W Seto
Journal:  J R Soc Interface       Date:  2008-09-09       Impact factor: 4.118

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