Modeling the Impact of Climate and Landscape on the Efficacy of White Tailed Deer Vaccination for Cattle Tick Control in Northeastern Mexico

Abstract

Cattle ticks are distributed worldwide and affect animal health and livestock production. White tailed deer (WTD) sustain and spread cattle tick populations. The aim of this study was to model the efficacy of anti-tick vaccination of WTD to control tick infestations in the absence of cattle vaccination in a territory where both host species coexist and sustain cattle tick populations. Agent-based models that included land cover/landscape properties (patch size, distances to patches) and climatic conditions were built in a GIS environment to simulate WTD vaccine effectiveness under conditions where unvaccinated cattle shared the landscape. Published and validated information on tick life cycle was used to build models describing tick mortality and developmental rates. Data from simulations were applied to a large territory in northeastern Mexico where cattle ticks are endemic and WTD and cattle share substantial portions of the habitat. WTD movements were simulated together with tick population dynamics considering the actual landscape and climatic features. The size of the vegetation patches and the distance between patches were critical for the successful control of tick infestations after WTD vaccination. The presence of well-connected, large vegetation patches proved essential for tick control, since the tick could persist in areas of highly fragmented habitat. The continued application of one yearly vaccination on days 1-70 for three years reduced tick abundance/animal/patch by a factor of 40 and 60 for R. annulatus and R. microplus, respectively when compared to non-vaccinated controls. The study showed that vaccination of WTD alone during three consecutive years could result in the reduction of cattle tick populations in northeastern Mexico. Furthermore, the results of the simulations suggested the possibility of using vaccines to prevent the spread and thus the re-introduction of cattle ticks into tick-free areas.

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

“…We identified 8/168 studies that explicitly incorporated climactic factors, all of them published in 2010 or later (Table S3). Most of these studies are centred on environmental factors affecting the vector lifecycle and reproduction, primarily for ticks (Estrada‐Peña, Carreón, Almazán, & De La Fuente, ; Li et al., ; Wang, Grant, & Teel, ; Wang, Grant, Teel, & Hamer, ; Wang, Teel, Grant, Schuster, & Pérez de León, ) and fleas (Laperrière et al., ). Spatial models could also play an important role in parsing out spatial and temporal autocorrelation as a function of seasonality (e.g., Duke‐Sylvester, Bolzoni, & Real, ).…”

Quantitative models of Rhipicephalus (Boophilus) ticks: historical review and synthesis

“…Estrada‐Peña et al. () predicted effects of white‐tailed deer vaccination on R. annulatus and R. microplus in northeastern Mexico, while Wang et al. () developed a spatially explicit, individual‐based, stochastic R. microplus model for south Texas rangelands.…”

“…In response, wildlife hosts are now explicitly represented in Rhipicephalus ( Boophilus ) models (e.g., Zeman and Lynen , Estrada‐Peña et al. , Phillips et al. , Wang et al.…”

Translating Ecology, Physiology, Biochemistry, and Population Genetics Research to Meet the Challenge of Tick and Tick‐borne Diseases in North America

“…r 43 change scenarios have been used to predict the efficacy of white-tailed deer vaccination (Estrada-Pena et al, 2014) to understand the onset week of LD (Monaghan et al, 2015), and to assess how temperature affects the basic reproductive number (R 0 ) (Ogden et al, 2014;Levi et al, 2015). In this last case, authors formulated a model based on several complex equations that simulated the long-term effect of climatic variability on the basic reproductive number (R 0 ) of I. scapularis.…”

“…In addition to modeling vector's distribution, SDM and GIS are useful to predict the impact of climate variability on other important aspects in the epidemiology of vector‐borne diseases. For instance, models built under climate change scenarios have been used to predict the efficacy of white‐tailed deer vaccination (Estrada‐Pena et al., ) to understand the onset week of LD (Monaghan et al, ), and to assess how temperature affects the basic reproductive number ( R 0 ) (Ogden et al., ; Levi et al., ). In this last case, authors formulated a model based on several complex equations that simulated the long‐term effect of climatic variability on the basic reproductive number ( R 0 ) of I. scapularis .…”