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Multi-host transmission dynamics of Schistosoma japonicum in Samar province, the Philippines.

Riley S, Carabin H, Bélisle P, Joseph L, Tallo V, Balolong E, Willingham AL, Fernandez TJ, Gonzales RO, Olveda R, McGarvey ST - PLoS Med. (2008)

Bottom Line: Our data provided substantially more support for model structure (a) than for model structure (b).Fitted values for the village-level transmission intensity from snails to mammals appeared to be strongly spatially correlated, which is consistent with results from descriptive hierarchical analyses.These findings have implications for the prioritization of mitigating interventions against S. japonicum transmission.

View Article: PubMed Central - PubMed

Affiliation: Department of Community Medicine and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. steven.riley@hku.hk

ABSTRACT

Background: Among the 6.7 million people living in areas of the Philippines where infection with Schistosoma japonicum is considered endemic, even within small geographical areas levels of infection vary considerably. In general, the ecological drivers of this variability are not well described. Unlike other schistosomes, S. japonicum is known to infect several mammalian hosts. However, the relative contribution of different hosts to the transmission cycle is not well understood. Here, we characterize the transmission dynamics of S. japonicum using data from an extensive field study and a mathematical transmission model.

Methods and findings: In this study, stool samples were obtained from 5,623 humans and 5,899 potential nonhuman mammalian hosts in 50 villages in the Province of Samar, the Philippines. These data, with variable numbers of samples per individual, were adjusted for known specificities and sensitivities of the measurement techniques before being used to estimate the parameters of a mathematical transmission model, under the assumption that the dynamic transmission processes of infection and recovery were in a steady state in each village. The model was structured to allow variable rates of transmission from different mammals (humans, dogs, cats, pigs, domesticated water buffalo, and rats) to snails and from snails to mammals. First, we held transmission parameters constant for all villages and found that no combination of mammalian population size and prevalence of infectivity could explain the observed variability in prevalence of infection between villages. We then allowed either the underlying rate of transmission (a) from snails to mammals or (b) from mammals to snails to vary by village. Our data provided substantially more support for model structure (a) than for model structure (b). Fitted values for the village-level transmission intensity from snails to mammals appeared to be strongly spatially correlated, which is consistent with results from descriptive hierarchical analyses.

Conclusions: Our results suggest that the process of acquiring mammalian S. japonicum infection is more important in explaining differences in prevalence of infection between villages than the process of snails becoming infected. Also, the contribution from water buffaloes to human S. japonicum infection in the Philippines is less important than has been recently observed for bovines in China. These findings have implications for the prioritization of mitigating interventions against S. japonicum transmission.

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Structure of the Dynamic ModelSubscripts denote species (H, human; S, snail; X, one of dog, cat, water buffalo, pig, or rat). Infection states are E, exposed and infected but not yet infectious; H, heavily infected; I, infected; L, lightly infected; and S, susceptible. Solid lines show the natural history of infection assumed for each species and dashed lines show the contribution by one species to the force-of-infection of another. The line below IS, terminated by a small circle, indicates the death of infected snails. We assume that the birth rate of susceptible snails is equal to the death rate of infected snails to ensure a constant snail population size.
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pmed-0050018-g001: Structure of the Dynamic ModelSubscripts denote species (H, human; S, snail; X, one of dog, cat, water buffalo, pig, or rat). Infection states are E, exposed and infected but not yet infectious; H, heavily infected; I, infected; L, lightly infected; and S, susceptible. Solid lines show the natural history of infection assumed for each species and dashed lines show the contribution by one species to the force-of-infection of another. The line below IS, terminated by a small circle, indicates the death of infected snails. We assume that the birth rate of susceptible snails is equal to the death rate of infected snails to ensure a constant snail population size.

Mentions: We developed a mathematical model of S. japonicum transmission between humans, snails, and the five different animal host species (Figure 1). The force of infection at a given time in a transmission model is defined as the hazard of infection experienced by one susceptible individual as a result of all currently infectious individuals. We defined the number of humans in the ith village to be NH(i). Similarly, the number of animals from potential reservoir species was NX(i), where X∈{C,D,P,R,W} denotes the mammal species: cat (C), dog (D), pig (P), rat (R), and water buffalo (W). A door-to-door census was conducted in 2002–2003 by our research group for humans and all potential reservoir species [8,10] other than rats. We assumed that the size of rat populations in different villages was proportional to the number that were trapped. Due to the very dense water-course landscape in Samar, it proved difficult to obtain reliable estimates of the size of snail populations. Therefore, we model proportions of snails in each infection class, rather than actual numbers. All state variables described below are functions of time, and some transmission parameters are also functions of village index j. We omit the (j,t) notation where not necessary for convenience.


Multi-host transmission dynamics of Schistosoma japonicum in Samar province, the Philippines.

Riley S, Carabin H, Bélisle P, Joseph L, Tallo V, Balolong E, Willingham AL, Fernandez TJ, Gonzales RO, Olveda R, McGarvey ST - PLoS Med. (2008)

Structure of the Dynamic ModelSubscripts denote species (H, human; S, snail; X, one of dog, cat, water buffalo, pig, or rat). Infection states are E, exposed and infected but not yet infectious; H, heavily infected; I, infected; L, lightly infected; and S, susceptible. Solid lines show the natural history of infection assumed for each species and dashed lines show the contribution by one species to the force-of-infection of another. The line below IS, terminated by a small circle, indicates the death of infected snails. We assume that the birth rate of susceptible snails is equal to the death rate of infected snails to ensure a constant snail population size.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2211559&req=5

pmed-0050018-g001: Structure of the Dynamic ModelSubscripts denote species (H, human; S, snail; X, one of dog, cat, water buffalo, pig, or rat). Infection states are E, exposed and infected but not yet infectious; H, heavily infected; I, infected; L, lightly infected; and S, susceptible. Solid lines show the natural history of infection assumed for each species and dashed lines show the contribution by one species to the force-of-infection of another. The line below IS, terminated by a small circle, indicates the death of infected snails. We assume that the birth rate of susceptible snails is equal to the death rate of infected snails to ensure a constant snail population size.
Mentions: We developed a mathematical model of S. japonicum transmission between humans, snails, and the five different animal host species (Figure 1). The force of infection at a given time in a transmission model is defined as the hazard of infection experienced by one susceptible individual as a result of all currently infectious individuals. We defined the number of humans in the ith village to be NH(i). Similarly, the number of animals from potential reservoir species was NX(i), where X∈{C,D,P,R,W} denotes the mammal species: cat (C), dog (D), pig (P), rat (R), and water buffalo (W). A door-to-door census was conducted in 2002–2003 by our research group for humans and all potential reservoir species [8,10] other than rats. We assumed that the size of rat populations in different villages was proportional to the number that were trapped. Due to the very dense water-course landscape in Samar, it proved difficult to obtain reliable estimates of the size of snail populations. Therefore, we model proportions of snails in each infection class, rather than actual numbers. All state variables described below are functions of time, and some transmission parameters are also functions of village index j. We omit the (j,t) notation where not necessary for convenience.

Bottom Line: Our data provided substantially more support for model structure (a) than for model structure (b).Fitted values for the village-level transmission intensity from snails to mammals appeared to be strongly spatially correlated, which is consistent with results from descriptive hierarchical analyses.These findings have implications for the prioritization of mitigating interventions against S. japonicum transmission.

View Article: PubMed Central - PubMed

Affiliation: Department of Community Medicine and School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. steven.riley@hku.hk

ABSTRACT

Background: Among the 6.7 million people living in areas of the Philippines where infection with Schistosoma japonicum is considered endemic, even within small geographical areas levels of infection vary considerably. In general, the ecological drivers of this variability are not well described. Unlike other schistosomes, S. japonicum is known to infect several mammalian hosts. However, the relative contribution of different hosts to the transmission cycle is not well understood. Here, we characterize the transmission dynamics of S. japonicum using data from an extensive field study and a mathematical transmission model.

Methods and findings: In this study, stool samples were obtained from 5,623 humans and 5,899 potential nonhuman mammalian hosts in 50 villages in the Province of Samar, the Philippines. These data, with variable numbers of samples per individual, were adjusted for known specificities and sensitivities of the measurement techniques before being used to estimate the parameters of a mathematical transmission model, under the assumption that the dynamic transmission processes of infection and recovery were in a steady state in each village. The model was structured to allow variable rates of transmission from different mammals (humans, dogs, cats, pigs, domesticated water buffalo, and rats) to snails and from snails to mammals. First, we held transmission parameters constant for all villages and found that no combination of mammalian population size and prevalence of infectivity could explain the observed variability in prevalence of infection between villages. We then allowed either the underlying rate of transmission (a) from snails to mammals or (b) from mammals to snails to vary by village. Our data provided substantially more support for model structure (a) than for model structure (b). Fitted values for the village-level transmission intensity from snails to mammals appeared to be strongly spatially correlated, which is consistent with results from descriptive hierarchical analyses.

Conclusions: Our results suggest that the process of acquiring mammalian S. japonicum infection is more important in explaining differences in prevalence of infection between villages than the process of snails becoming infected. Also, the contribution from water buffaloes to human S. japonicum infection in the Philippines is less important than has been recently observed for bovines in China. These findings have implications for the prioritization of mitigating interventions against S. japonicum transmission.

Show MeSH
Related in: MedlinePlus