Prevention of tick-borne diseases.

Center for Disease Control and Prevention, National Center for Emerging and Zoonotic Infectious Diseases, Division of Vector-Borne Diseases, Fort Collins, CO 80521, USA.
Journal of environmental health (Impact Factor: 1.01). 06/2012; 74(10):30-2. DOI: 10.1016/S0025-7125(03)00084-1
Source: PubMed
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    ABSTRACT: The basic reproduction number of a pathogen, R0, determines whether a pathogen will spread (R0>1), when introduced into a fully susceptible population or fade out (R0<1), because infected hosts do not, on average, replace themselves. In this paper we develop a simple mechanistic model for the basic reproduction number for a group of tick-borne pathogens that wholly, or almost wholly, depend on horizontal transmission to and from vertebrate hosts. This group includes the causative agent of Lyme disease, Borrelia burgdorferi, and the causative agent of human babesiosis, Babesia microti, for which transmission between co-feeding ticks and vertical transmission from adult female ticks are both negligible. The model has only 19 parameters, all of which have a clear biological interpretation and can be estimated from laboratory or field data. The model takes into account the transmission efficiency from the vertebrate host as a function of the days since infection, in part because of the potential for this dynamic to interact with tick phenology, which is also included in the model. This sets the model apart from previous, similar models for R0 for tick-borne pathogens. We then define parameter ranges for the 19 parameters using estimates from the literature, as well as laboratory and field data, and perform a global sensitivity analysis of the model. This enables us to rank the importance of the parameters in terms of their contribution to the observed variation in R0. We conclude that the transmission efficiency from the vertebrate host to Ixodes scapularis ticks, the survival rate of Ixodes scapularis from fed larva to feeding nymph, and the fraction of nymphs finding a competent host, are the most influential factors for R0. This contrasts with other vector borne pathogens where it is usually the abundance of the vector or host, or the vector-to-host ratio, that determine conditions for emergence. These results are a step towards a better understanding of the geographical expansion of currently emerging horizontally-transmitted tick-borne pathogens such as Babesia microti, as well as providing a firmer scientific basis for targeted use of acaricide or the application of wildlife vaccines that are currently in development.
    Journal of Theoretical Biology 07/2013; · 2.35 Impact Factor
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    ABSTRACT: Abstract Ixodes scapularis, the blacklegged tick, is capable of transmitting the pathogens that cause Lyme disease (Borrelia burgdorferi), babesiosis (Babesia microti), anaplasmosis (Anaplasma phagocytophilum), and to a lesser extent Powassan encephalitis (deer tick virus [DTV]). These pathogens represent significant public health problems, but little is known about the occurrence and co-infection prevalence of these pathogens in I. scapularis. Here, we used standard PCR and pathogen-specific primers to estimate the prevalence of infection of A. phagocytophilium, B. burgdorferi, B. microti, and Ehrlichia chaffeensis in questing nymph and adult I. scapularis collected from sites in Putnam and Dutchess counties in southern New York in 2011. To detect DTV infection, cell cultures were observed for the presence of cytopathic effects and positive results were confirmed via real time RT-PCR. In 466 individually sampled adult ticks, B. burgdorferi had the highest prevalence of infection (55%) followed by A. phagocytophilum (18.2%), DTV (3.4%), B. microti (3.2%), and E. chaffeensis (1.5%). Infection with two pathogens occurred in 13.3% of ticks, and 10 ticks were infected with three combinations of three pathogens. These results provide an estimate of the rate of co-infection, which then can help inform the epidemiological risk of contracting multiple zoonotic tick-borne pathogens within the Hudson Valley region of New York State.
    Vector borne and zoonotic diseases (Larchmont, N.Y.) 04/2014; · 2.61 Impact Factor
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    ABSTRACT: Peridomestic exposure to Borrelia burgdorferi-infected Ixodes scapularis nymphs is considered the dominant means of infection with black-legged tick-borne pathogens in the eastern United States. Population level studies have detected a positive association between the density of infected nymphs and Lyme disease incidence. At a finer spatial scale within endemic communities, studies have focused on individual level risk behaviors, without accounting for differences in peridomestic nymphal density. This study simultaneously assessed the influence of peridomestic tick exposure risk and human behavior risk factors for Lyme disease infection on Block Island, Rhode Island. Tick exposure risk on Block Island properties was estimated using remotely sensed landscape metrics that strongly correlated with tick density at the individual property level. Behavioral risk factors and Lyme disease serology were assessed using a longitudinal serosurvey study. Significant factors associated with Lyme disease positive serology included one or more self-reported previous Lyme disease episodes, wearing protective clothing during outdoor activities, the average number of hours spent daily in tick habitat, the subject's age and the density of shrub edges on the subject's property. The best fit multivariate model included previous Lyme diagnoses and age. The strength of this association with previous Lyme disease suggests that the same sector of the population tends to be repeatedly infected. The second best multivariate model included a combination of environmental and behavioral factors, namely hours spent in vegetation, subject's age, shrub edge density (increase risk) and wearing protective clothing (decrease risk). Our findings highlight the importance of concurrent evaluation of both environmental and behavioral factors to design interventions to reduce the risk of tick-borne infections.
    PLoS ONE 01/2014; 9(1):e84758. · 3.73 Impact Factor