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. 2014 Mar 20;8(3):e2731.
doi: 10.1371/journal.pntd.0002731. eCollection 2014 Mar.

Dynamics of the force of infection: insights from Echinococcus multilocularis infection in foxes

Fraser I Lewis  1 , Belen Otero-Abad  1 , Daniel Hegglin  2 , Peter Deplazes  2 , Paul R Torgerson  1
Affiliations

Dynamics of the force of infection: insights from Echinococcus multilocularis infection in foxes

Fraser I Lewis et al. PLoS Negl Trop Dis. .

Abstract

Characterizing the force of infection (FOI) is an essential part of planning cost effective control strategies for zoonotic diseases. Echinococcus multilocularis is the causative agent of alveolar echinococcosis in humans, a serious disease with a high fatality rate and an increasing global spread. Red foxes are high prevalence hosts of E. multilocularis. Through a mathematical modelling approach, using field data collected from in and around the city of Zurich, Switzerland, we find compelling evidence that the FOI is periodic with highly variable amplitude, and, while this amplitude is similar across habitat types, the mean FOI differs markedly between urban and periurban habitats suggesting a considerable risk differential. The FOI, during an annual cycle, ranges from (0.1,0.8) insults (95% CI) in urban habitat in the summer to (9.4, 9.7) (95% CI) in periurban (rural) habitat in winter. Such large temporal and spatial variations in FOI suggest that control strategies are optimal when tailored to local FOI dynamics.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Transmission model for E.multilocularis in foxes.
State variables are: formula image, formula image, formula image and formula image, where formula image represents the proportion of hosts (foxes) which are not infected and not immune at age formula image, the other state variables are similarly defined. Parameter formula image denotes the infection pressure (force of infection), measured in insults (exposures) per year; formula image is the probability of immunity on exposure; formula image is the rate of loss of host immunity; formula image is the parasite death rate.
Figure 2
Figure 2. Exploratory analyses.
Panel (a) shows observed prevalence across age groups of 30-days blocks up to age 36 months (where 1 month = 30 days). Panel (b) shows smoothed prevalence using a locally weighted regression smoother (lowess() in R) applied to the 0/1 observation for all individuals aged less than 3 years. Panel (c) shows observed prevalence across age groups of 30-days blocks for all ages (maximum 108 months where again one month = 30 days). Panel (d) shows the smoother applied to data of all ages.
Figure 3
Figure 3. Transmission Model 1-P.
Panel (a): joint marginal posterior density for formula image on log scale. The red contour is the 95% limit and the two points marked are those used to produce approx. 95% confidence intervals in panels b and c. Panel (b): dynamics of force of infection by age, 95% CI is for the mean force of infection at age formula image. Panel (c): Smoothed observed prevalence and prevalence predicted by Model 1-P, 95% CI are for the mean prevalence at age formula image. All results use the informative prior for formula image with mean = 1.2 and sd = 0.2.
Figure 4
Figure 4. Heterogeneous habitat transmission Model 1-P0.
Panel (a): joint marginal posterior densities for formula image, formula image, formula image on log scale. The red contour is the 95% limit and the two points marked are those used to produce approx. 95% confidence intervals in panel b. Panel (b): dynamics of force of infection by age, approx 95% CI is for the mean force of infection at age formula image (see main text for explanation of why these lines cross). All results use the informative prior for formula image with mean = 1.2 and sd = 0.2.
See this image and copyright information in PMC

References

    1. Anderson R, May R (1992) Infectious Diseases of Humans: Dynamics and Control. New York, USA: Oxford Science Publications, Oxford University Press.
    1. Mueller I, Schoepin S, Smith TA, Benton KL, Bretscher MT, et al. (2012) Force of infection is key to understanding the epidemiology of Plasmodium falciparum Malaria in Papua New Guinean children. Proceedings of the National Academy of Sciences of the United States of America 109: 10030–10035. - PMC - PubMed
    1. Sutton AJ, Gay NJ, Edmunds WJ, Hope VD, Gill ON, et al. (2006) Modelling the force of infection for Hepatitis B and Hepatitis C in injecting drug users in England and Wales. BMC Infectious Diseases 6: 93. - PMC - PubMed
    1. Gupta S, Snow RW, Donnelly C, Newbold C (1999) Acquired immunity and postnatal clinical protection in childhood cerebral Malaria. Proceedings of the Royal Society B-biological Sciences 266: 33–38. - PMC - PubMed
    1. Budke CM, Jiamin Q, Craig PS, Torgerson PR (2005) Modeling the transmission of Echinococ-cus granulosus and Echinococcus multilocularis in dogs for a high endemic region of the Tibetan plateau. International Journal For Parasitology 35: 163–170. - PubMed

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