An Examination of the Demographic and Environmental Variables Correlated with Lyme Disease Emergence in Virginia

Seukep, Sara E.; Kolivras, Korine N.; Hong, Yili; Li, Jie; Prisley, Stephen P.; Campbell, James B.; Gaines, David N.; Dymond, Randel L.

doi:10.1007/s10393-015-1034-3

Cited by 34 publications

(57 citation statements)

References 28 publications

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“…In our study, the forest fragment perimeters (FragPerim06) is not included in the final models for either ecoregions. Seukep et al (2015) found that the percentage of forest was not selected, while our findings support the results in Jackson, Hilborn, and Thomas (2006) and suggest that it is an important variable. Seukep et al (2015) fitted a spatial model using Lyme disease data without considering the ecoregion variable.…”

Section: Virginia Lyme Disease Data Analysissupporting

confidence: 82%

Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence

Xie

et al. 2019

Journal of the American Statistical Association

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Lyme disease is an infectious disease that is caused by a bacterium called Borrelia burgdorferi sensu stricto. In the United States, Lyme disease is one of the most common infectious diseases. The major endemic areas of the disease are New England, Mid-Atlantic, East-North Central, South Atlantic, and West North-Central. Virginia is on the front-line of the disease's diffusion from the northeast to the south. One of the research objectives for the infectious disease community is to identify environmental and economic variables that are associated with the emergence of Lyme disease. In this paper, we use a spatial Poisson regression model to link the spatial disease counts and environmental and economic variables, and develop a spatial variable selection procedure to effectively identify important factors by using an adaptive elastic net penalty. The proposed methods can automatically select important covariates, while adjusting for possible spatial correlations of disease counts. The performance of the proposed method is studied and compared with existing methods via a comprehensive simulation study.We apply the developed variable selection methods to the Virginia Lyme disease data and identify important variables that are new to the literature. Supplementary materials for this paper are available online.

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Section: Virginia Lyme Disease Data Analysissupporting

confidence: 82%

Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence

Xie

et al. 2019

Journal of the American Statistical Association

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“…, Seukep et al. ). However, unlike forest fragmentation resulting from human development (Allan et al.…”

Section: Discussionmentioning

confidence: 99%

“…, Seukep et al. ) or sudden oak death (Swei et al. , ), destruction of forested habitats by wildfire is much more sudden and catastrophic, which may have very different effects on the ecology of tick‐borne disease.…”

Section: Discussionmentioning

confidence: 99%

Risk of vector tick exposure initially increases, then declines through time in response to wildfire in California

et al. 2018

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Abstract. Identifying the effects of human-driven perturbations, such as species introductions or habitat fragmentation, on the ecology and dynamics of infectious disease has become a central focus of disease ecologists. Yet, comparatively little is known about how the ecology of zoonotic disease systems responds to catastrophic disturbance events such as wildfires or hurricanes. In California, wildfire disturbance is centrally important to the ecology of forests and oak woodlands and is projected to increase in severity and extent under future climate change. Here, taking advantage of a recent wildfire as a natural experiment, we investigate the effects of wildfire disturbance on the ecology of tick-borne disease in California oak woodlands. We find that wildfire leads to elevated abundance of questing adult and nymphal western blacklegged ticks (Ixodes pacificus) in the year following fire, relative to unburned control plots, but that vector tick abundance declines sharply in the following two years. We find that the abundance of non-competent hosts (western fence lizards) for the Lyme disease bacterium is unaffected by fire, but that the abundances of important reproductive hosts (deer) for ticks and reservoir hosts (dusky-footed woodrats) for tick-borne pathogens are significantly negatively affected by fire. We found ticks and hosts infected with Borrelia burgdorferi sensu lato only within the burn extent and only in the year following the wildfire, though rates of infection were exceedingly low representing little risk to humans. In aggregate, due to the differential effects of this catastrophic disturbance event on different key host species and vector tick life stages in the transmission of tick-borne pathogens, we conclude that wildfire may potentially increase risk of exposure to vector ticks in the first year following wildfire in California, but that risk is dampened substantially in following years due to tick population declines and loss of key reservoir hosts from the system.

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“…One of our next undertakings in our Lyme disease research in Virginia is to use environmental data and population data to build a model relating Lyme disease occurrence and environmental and demographic variables. 12 This analysis will help us to identify the factors that affect Lyme disease infection risk, explain patterns of Lyme disease spread noted in this study, and provide better guidance to public health practitioners.…”

Section: Discussionmentioning

confidence: 99%

“…Statewide surveillance for Lyme disease in Virginia started in 1989 when it became a reportable disease. 12 This study examined all Lyme disease-positive laboratory reports received by the VDH for patients from commercial testing laboratories as well as Lyme disease case reports provided to the VDH by physicians as part of Virginia's Lyme disease case surveillance. Lyme case classification at the VDH was based on the National Surveillance Case Definition for Lyme disease.…”

Section: Methodsmentioning

confidence: 99%

Spatial and Temporal Emergence Pattern of Lyme Disease in Virginia

Li¹,

Kolivras²,

Hong³

et al. 2014

The American Society of Tropical Medicine and Hygiene

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Abstract. The emergence of infectious diseases over the past several decades has highlighted the need to better understand epidemics and prepare for the spread of diseases into new areas. As these diseases expand their geographic range, cases are recorded at different geographic locations over time, making the analysis and prediction of this expansion complicated. In this study, we analyze spatial patterns of the disease using a statistical smoothing analysis based on areal (census tract level) count data of Lyme disease cases in Virginia from 1998 to 2011. We also use space and space-time scan statistics to reveal the presence of clusters in the spatial and spatiotemporal distribution of Lyme disease. Our results confirm and quantify the continued emergence of Lyme disease to the south and west in states along the eastern coast of the United States. The results also highlight areas where education and surveillance needs are highest.

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An Examination of the Demographic and Environmental Variables Correlated with Lyme Disease Emergence in Virginia

Cited by 34 publications

References 28 publications

Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence

Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence

Risk of vector tick exposure initially increases, then declines through time in response to wildfire in California

Spatial and Temporal Emergence Pattern of Lyme Disease in Virginia

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