Volume 72, Issue 6
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645


A dynamic model of S transmission is presented that incorporates effects of infection intensity, age, and sex. We use four infection intensity classes to investigate the impact of ecologic changes and public health interventions on the burden of infection within communities. Age- and sex-specific infection data from three disease-endemic villages in the Philippines are used to estimate the parameters of the model. The model gives good qualitative agreement with observed fecal egg counts adjusted for the accuracy of the Kato-Katz examination. Our results suggest that differences in infection burden between villages are caused by differences in both the infection process and the recovery process in humans. We describe the potential impact of mass treatment of all humans on the numbers with high infection. Furthermore, we show that a sudden reduction in snail population size would affect high prevalence and low prevalence communities in different ways.


Article metrics loading...

The graphs shown below represent data from March 2017
Loading full text...

Full text loading...



  1. Williams GM, Sleigh AC, Li Y, Feng Z, Davis GM, Chen H, Ross AG, Bergquist R, McManus DP, 2002. Mathematical modelling of schistosomiasis japonica: comparison of control strategies in the People’s Republic of China. Acta Trop 82 : 253–262. [Google Scholar]
  2. Mott KE, Nuttall I, Desjeux P, Cattand P, 1995. New geographical approaches to control of some parasitic zoonoses. Bull World Health Organ 73 : 247–257. [Google Scholar]
  3. Ross AG, Bartley PB, Sleigh AC, Olds GR, Li Y, Williams GM, McManus DP, 2002. Schistosomiasis. N Engl J Med 346 : 1212–1220. [Google Scholar]
  4. Olveda RM, Daniel BL, Ramirez BD, Aligui GD, Acosta LP, Fevidal P, Tiu E, de Veyra F, Peters PA, Romulo R, Domingo E, Wiest PM, Olds GR, 1996. Schistosomiasis japonica in the Philippines: the long-term impact of population-based chemotherapy on infection, transmission, and morbidity. J Infect Dis 174 : 163–172. [Google Scholar]
  5. Wiest PM, Wu G, Zhang S, Yuan J, Peters PA, McGarvey ST, Tso M, Olveda R, Olds GR, 1992. Morbidity due to schistosomiasis japonica in the People’s Republic of China. Trans R Soc Trop Med Hyg 86 : 47–50. [Google Scholar]
  6. Zhou XN, Malone JB, Kristensen TK, Bergquist NR, 2001. Application of geographic information systems and remote sensing to schistosomiasis control in China. Acta Trop 79 : 97–106. [Google Scholar]
  7. He YX, Salafsky B, Ramaswamy K, 2001. Host-parasite relationships of Schistosoma japonicum in mammalian hosts. Trends Parasitol 17 : 320–324. [Google Scholar]
  8. Fernandez TJ Jr, Petilla T, Banez B, 1982. An epidemiological study on Schistosoma japonicum in domestic animals in Leyte, Philippines. Southeast Asian J Trop Med Public Health 13 : 575–579. [Google Scholar]
  9. Chan MS, Anderson RM, Medley GF, Bundy DA, 1996. Dynamic aspects of morbidity and acquired immunity in schistosomiasis control. Acta Trop 62 : 105–117. [Google Scholar]
  10. Chan MS, Bundy DA, 1997. Modelling the dynamic effects of community chemotherapy on patterns of morbidity due to Schistosoma mansoni. Trans R Soc Trop Med Hyg 91 : 216–220. [Google Scholar]
  11. Chan MS, Guyatt HL, Bundy DA, Medley GF, 1996. Dynamic models of schistosomiasis morbidity. Am J Trop Med Hyg 55 : 52–62. [Google Scholar]
  12. Hairston NG, 1965. An analysis of age-prevalence data by catalytic models. A contribution to the study of bilharziasis. Bull World Health Organ 33 : 163–165. [Google Scholar]
  13. Barbour AD, 1996. Modeling the transmission of schistosomiasis: an introductory view. Am J Trop Med Hyg 55 : 135–143. [Google Scholar]
  14. Anderson RM, May RM, 1991. Infectious Diseases of Humans: Dynamics and Control: Oxford, United Kingdom: Oxford Science Publications.
  15. Olveda RM, Tiu E, Fevidal P, Deveyra F, Icatlo FC, Domingo EO, 1983. Relationship of prevalence and intensity of infection to morbidity in schistosomiasis japonica - a study of three communities in Leyte, The Philippines. Am J Trop Med Hyg 32 : 1312–1321. [Google Scholar]
  16. Carabin H, Marshall CM, Joseph L, Riley S, Olveda R, McGarvey ST, 2005. Estimating the intensity of infection with Schistosoma japonicum in villagers of Leyte, Philippines. Part I: A Bayesian cumulative logit model. The schistosomiasis transmission & ecology project (STEP). Am J Trop Med Hyg 72 : 745–753. [Google Scholar]
  17. de Bont J, Shaw DJ, Vercruysse J, 2002. The relationship between faecal egg counts, worm burden and tissue egg counts in early Schistosoma mattheei infections in cattle. Acta Trop 81 : 63–76. [Google Scholar]
  18. Liang S, Maszle D, Spear RC, 2002. A quantitative framework for a multi-group model of schistosomiasis japonicum transmission dynamics and control in Sichuan, China. Acta Trop 82 : 263–277. [Google Scholar]
  19. Spear RC, Hubbard A, Liang S, Seto E, 2002. Disease transmission models for public health decision making: toward an approach for designing intervention strategies for schistosomiasis japonica. Environ Health Perspect 110 : 907–915. [Google Scholar]
  20. Vanamail P, Subramanian S, Das PK, Pani SP, Rajagopalan PK, Bundy DA, Grenfell BT, 1989. Estimation of age-specific rates of acquisition and loss of Wuchereria bancrofti infection. Trans R Soc Trop Med Hyg 83 : 689–693. [Google Scholar]
  21. Press WH, Teukolsky SA, Vetterling WT, Flannery BP, 2002. Numerical Recipes in C++: The Art of Scientific Computing. Cambridge, United Kingdom: Cambridge University Press.
  22. Aitchison J, 1982. The statistical-analysis of compositional data. J R Stat Soc B 44 : 139–177. [Google Scholar]
  23. Robert CP, Casella G, 1999. Monte Carlo Statistical Methods. New York: Springer-Verlag.

Data & Media loading...

  • Received : 13 Apr 2004
  • Accepted : 04 Dec 2004

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error