Relevance of Indirect Transmission for Wildlife Disease Surveillance.

Martin Lange,Hans-Hermann Thulke,Stephanie Kramer-Schadt

doi:10.3389/fvets.2016.00110

Abstract

Epidemiological models of infectious diseases are essential tools in support of risk assessment, surveillance design, and contingency planning in public and animal health. Direct pathogen transmission from host to host is an essential process of each host–pathogen system and respective epidemiological modeling concepts. It is widely accepted that numerous diseases involve indirect transmission (IT) through pathogens shed by infectious hosts to their environment. However, epidemiological models largely do not represent pathogen persistence outside the host explicitly. We hypothesize that this simplification might bias management-related model predictions for disease agents that can persist outside their host for a certain time span. We adapted an individual-based, spatially explicit epidemiological model that can mimic both transmission processes. One version explicitly simulated indirect pathogen transmission through a contaminated environment. The second version simulated direct host-to-host transmission only. We aligned the model variants by the transmission potential per infectious host (i.e., basic reproductive number R0) and the spatial transmission kernel of the infection to allow unbiased comparison of predictions. The quantitative model results are provided for the example of surveillance plans for early detection of foot-and-mouth disease in wild boar, a social host. We applied systematic sampling strategies on the serological status of randomly selected host individuals in both models. We compared between the model variants the time to detection and the area affected prior to detection, measures that strongly influence mitigation costs. Moreover, the ideal sampling strategy to detect the infection in a given time frame was compared between both models. We found the simplified, direct transmission model to underestimate necessary sample size by up to one order of magnitude but to overestimate the area put under control measures. Thus, the model predictions underestimated surveillance efforts but overestimated mitigation costs. We discuss parameterization of IT models and related knowledge gaps. We conclude that the explicit incorporation of IT mechanisms in epidemiological modeling may reward by adapting surveillance and mitigation efforts.

Highlights

Host–pathogen models play an essential role in epidemiology [1]
For a wildlife host–pathogen system with a social host species, we investigated the consequences of an a priori assumption of direct host-to-host transmission in models for surveillance design
We show that the simplified, direct transmission (DT) model underestimated necessary sampling efforts by up to one order of magnitude, but overestimated the outbreak area that would receive control or mitigation measures

Summary

Introduction

Epidemiological models are widely used to support risk assessment, surveillance design, and contingency planning [2,3,4,5]. The driving force of any infectious disease is the transmission of the pathogen to susceptible hosts [6, 7], and its adequate representation in epidemiological models is of crucial importance [8, 9]. The relevance of indirect transmission (IT) without a vector or reservoir, but through contaminated environment, was demonstrated for pathogenic viruses, bacteria, prions, and macroparasites. Zoonotics and diseases of man with IT mode include infections with influenza viruses [21], cholera bacteria [22, 23], hantaviruses [24], and Salmonella bacteria [25]. Longevity outside the host was investigated under experimental conditions [see, e.g., Ref. [26] for FMD, CSF, BVDV, and PPV; [27] review FMD; [28] review poultry diseases; [29] review CSF; [30] CSF; [31, 32] AIV; [33] Influenza A, B; [34] cholera]

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