Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-23T12:48:51.661Z Has data issue: false hasContentIssue false

Covariance in parasite burdens: the effect of predisposition to infection

Published online by Cambridge University Press:  06 April 2009

H. I. McCallum
Affiliation:
Department of Zoology, University of Queensland, St Lucia 4067, Australia

Summary

Recently the phenomenon of predisposition to helminth infection has been reported in a number of studies: those individuals which are heavily infected before treatment with an anthelmintic tend also to acquire heavy parasite burdens following a period of reinfection. This correlation between parasite burdens in initial and reinfections is generated by differences between hosts in their exposure to infective stages and in their susceptibility to infection. Inter-host differences in these factors also generate the aggregated or over-dispersed parasite distributions that are usually observed. This paper uses probability theory to predict the correlation between initial and reinfection parasite burdens assuming that those inter-host differences which generate over-dispersion remain constant for a given individual between initial and reinfection periods. The predicted correlation is considerably greater than is observed in most published data sets. Over-dispersion is thus generated by variability between hosts which has components that remain constant between initial and reinfection and also components which vary between infection periods. The model is modified to account for those two sources of variability, and the result applied to published data to determine the contributions made by short and long-term factors to the observed distributions.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1990

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, R. M. & Gordon, D. M. (1982). Processes influencing the distribution of parasite numbers within host populations with special emphasis on parasite-induced host mortalities. Parasitology 85, 373–98.Google Scholar
Anderson, R. M. & May, R. M. (1978). Regulation and stability of host-parasite population interactions. I. Regulatory processes. Journal of Animal Ecology 47, 219–48.CrossRefGoogle Scholar
Anderson, R. M. & Medley, G. F. (1985). Community control of helminth infections of man by mass and selective chemotherapy. Parasitology 90, 629–60.CrossRefGoogle Scholar
Arbous, A. G. & Kerrich, J. E. (1951). Accident statistics and the concept of accident proneness. Biometrics 7, 340432.CrossRefGoogle Scholar
Atkinson, W. D. & Shorrocks, B. (1981). Competition on a divided and ephemeral resource: a simulation model. Journal of Animal Ecology 50, 461–71.Google Scholar
Bliss, C. I. & Owen, A. R. G. (1958). Negative binomial distributions with a common k. Biometrika 45, 3758.Google Scholar
Bundy, D. A. P. & Cooper, E. S. (1988). The evidence for predisposition to trichuriasis in humans: comparison of institutional and community studies. Annals of Tropical Medicine and Parasitology 82, 251–6.CrossRefGoogle ScholarPubMed
Bundy, D. A. P., Cooper, E. S., Thompson, D. E., Anderson, R. M. & Didier, J. M. (1987 a). Age-related prevalence and intensity of Trichuris trichiura infection in a St. Lucian community. Transactions of the Royal Society of Tropical Medicine and Hygiene 81, 8594.CrossRefGoogle Scholar
Bundy, D. A. P., Cooper, E. S., Thompson, D. E., Didier, J. M. & Simmons, I. (1987b). Epidemiology and population dynamics of Ascaris lumbricoides and Trichuris trichiura infection in the same community. Transactions of the Royal Society of Tropical Medicine and Hygiene 81, 987–93.Google Scholar
Bundy, D. A. P., Cooper, E. S., Thompson, D. E., Didier, J. M., Anderson, R. M. & Simmons, I. (1987 c). Predisposition to Trichuris trichiura infection in humans. Epidemiology and Infection 98, 6571.CrossRefGoogle ScholarPubMed
Bundy, D. A. P., Thompson, D. E., Golden, M. H. N., Cooper, E. S., Anderson, R. M. & Harland, P. S. E. (1985). Population distribution of Trichuris trichiura in a community of Jamaican children. Transactions of the Royal Society of Tropical Medicine and Hygiene 79, 232–7.Google Scholar
Crofton, H. D. (1971). A quantitative approach to parasitism. Parasitology 62, 179–94.CrossRefGoogle Scholar
Dietz, K. (1982). Overall population patterns in the transmission cycle of infectious disease agents. In Population Biology of Infectious Diseases (ed. Anderson, R. M. & May, R. M.), pp. 87102. Berlin: Springer.Google Scholar
Greenwood, M. & Yule, G. U. (1920). An enquiry into the nature of frequency distributions representative of multiple happenings with particular reference to the occurrence of multiple attacks of disease or of repeated accidents. Journal of the Royal Statistical Society 83, 255–79.Google Scholar
Haswell-Elkins, M. R., Elkins, D. B. & Anderson, R. M. (1987). Evidence for predisposition in humans to infection with Ascaris, hookworm, Enterobius and Trichuris in a South Indian fishing community. Parasitology 95, 323–37.CrossRefGoogle Scholar
Haswell-Elkins, M. R., Elkins, D. B. & Anderson, R. M. (1989). The influence of individual, social group and household factors on the distribution of Ascaris lumbricoides within a community and implications for control strategies. Parasitology 98, 125–34.CrossRefGoogle ScholarPubMed
Haswell-Elkins, M. R., Elkins, D. B., Manjula, K., Michael, E. &Anderson, R. M.(1988). An investigation of hookworm infection and reinfection following mass anthelmintic treatment in the South Indian fishing community of Vairavankuppam. Parasitology 96, 565–77.CrossRefGoogle ScholarPubMed
Irwin, J. O. (1968). The generalized Waring distribution applied to accident theory. Journal of the Royal Statistical Society, A131, 205–25.Google Scholar
Kemp, C. D. (1970). ‘Accident proneness’ and discrete distribution theory. In Random Counts in Biomedical and Social Sciences, Vol 2. (ed. Patil, G. P.). pp. 3965. University Park, Pennsylvania: Pennsylvania State University Press.Google Scholar
Keymer, A. E. & Pagel, M. (1989). Predisposition to helminth infection. In Hookworm Disease: Current Status and New Direction (ed. Schadd, G. A. & Warren, K.) Taylor & Francis (in the Press).Google Scholar
Mccallum, H. I. (1982). Infection dynamics of Ichthyophthirius multifiliis. Parasitology 85, 475–88.Google Scholar
Mccallum, H. I. & Anderson, R. M. (1984). Systematic temporal changes in host susceptibility to infection: demographic mechanisms. Parasitology 89, 195208.CrossRefGoogle ScholarPubMed
Mccallum, H. I. & Singleton, G. R. (1989). Models to assess the potential of Capillaria hepatica to control population outbreaks of house mice. Parasitology 98, 425–37.Google Scholar
Pielou, E. C. (1977). Mathematical Ecology. New York: John Wiley & Sons.Google Scholar
Pennycuick, L. (1971) Frequency distributions of parasites in a population of three-spined sticklebacks, Gasterosteus aculeatus L., with particular reference to the negative binomial distribution. Parasitology 63, 389406.CrossRefGoogle Scholar
Schad, G. A. & Anderson, R. M. (1985). Predisposition to hookworm infection in humans. Science 228, 1537–40.CrossRefGoogle ScholarPubMed
Scott, M. E. (1987). Temporal changes in aggregation: a laboratory study. Parasitology 94, 583–95.Google Scholar
Scott, M. E. (1988). Predisposition of mice to Heligmosomoides polygyrus and Aspiculuris tetraptera (Nematoda). Parasitology 97, 114.Google ScholarPubMed
Taylor, L. R., Woiwod, I. P. & Perry, J. N. (1979). The negative binomial as a dynamic ecological model for aggregation, and the density dependence of k. Journal of Animal Ecology 48, 289304.CrossRefGoogle Scholar
Thein, hlaing, Saw, Than & Lwin, Myint (1987). Reinfection of people with Ascaris lumbricoides following single, 6-month and 12-month interval mass chemotherapy in Okpo village, rural Burma. Transactions of the Royal Society of Tropical Medicine and Hygiene 81, 140–6.Google Scholar