Experimental investigation of alternative transmission functions: Quantitative evidence for the importance of nonlinear transmission dynamics in host–parasite systems. (4th January 2018)

• Record Type: Journal Article
• Authors: Orlofske, Sarah A.; Flaxman, Samuel M.; Joseph, Maxwell B.; Fenton, Andy; Melbourne, Brett A.; Johnson, Pieter T. J.
• Editors: Dunn, Jenny
• Is Part Of: Journal of animal ecology. Volume 87:Number 3(2018:May)
• Page Start: 703
• Page End: 715
• Publication Date: 2018-01-04
• Subjects: behaviour -- epidemiology -- infectious disease -- macroparasite -- mathematical model -- Ribeiroia ondatrae; Animal ecology -- Periodicals; 591.7
• DOI: 10.1111/1365-2656.12783
• Languages: English
• ISSNs: 0021-8790

Abstract

Abstract: Understanding pathogen transmission is crucial for predicting and managing disease. Nonetheless, experimental comparisons of alternative functional forms of transmission remain rare, and those experiments that are conducted are often not designed to test the full range of possible forms. To differentiate among 10 candidate transmission functions, we used a novel experimental design in which we independently varied four factors—duration of exposure, numbers of parasites, numbers of hosts and parasite density—in laboratory infection experiments. We used interactions between amphibian hosts and trematode parasites as a model system and all candidate models incorporated parasite depletion. An additional manipulation involving anaesthesia addressed the effects of host behaviour on transmission form. Across all experiments, nonlinear transmission forms involving either a power law or a negative binomial function were the best‐fitting models and consistently outperformed the linear density‐dependent and density‐independent functions. By testing previously published data for two other host–macroparasite systems, we also found support for the same nonlinear transmission forms. Although manipulations of parasite density are common in transmission studies, the comprehensive set of variables tested in our experiments revealed that variation in density alone was least likely to differentiate among competing transmission functions. Across host–pathogen systems, nonlinear functions may often more accurately represent transmission dynamics and thus provide more realistic predictions for infection. Abstract : The authors tested 10 candidate functions representing the transmission of trematode parasites to amphibian hosts using laboratory experiments varying the duration of exposure, numbers of parasites, numbers of hosts and parasite density. Nonlinear functions outperformed classical frequency‐ and density‐dependent transmission functions and may provide more realistic predictions for infection.