Dataset Information

Lyme Disease Transmission Risk: Seasonal Variation in the Built Environment.

ABSTRACT: Seasonal variation in spatial distribution and pathogen prevalence of Borrelia burgdorferi in blacklegged ticks (Ixodes scapularis) influences human population risk of Lyme disease in peri-urban built environments. Parks, gardens, playgrounds, school campuses and neighborhoods represent a significant risk for Lyme disease transmission. From June 2012 through May 2014, ticks were collected using 1 m² corduroy cloths dragged over low-lying vegetation parallel to walkways with high human foot traffic. DNA was extracted from ticks, purified and presence of B. burgdorferi assessed by polymerase chain reaction amplification. Summer is reported as the time of highest risk for Lyme disease transmission in the United States and our results indicate a higher tick density of 26.0/1000 m² in summer vs. 0.2/1000 m² to 10.5/1000 m² in spring and fall. However, our findings suggest that tick infection rate is proportionally higher during the fall and spring than summer (30.0?54.7% in fall and 36.8?65.6% in spring vs. 20.0?28.2% in summer). Seasonal variation in infected tick density has significant implications for Lyme disease transmission as people are less likely to be aware of ticks in built environments, and unaware of increased infection in ticks in spring and fall. These factors may lead to more tick bites resulting in Lyme infection.

SUBMITTER: Roome A

PROVIDER: S-EPMC6163686 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Lyme Disease Transmission Risk: Seasonal Variation in the Built Environment.

Roome Amanda A Spathis Rita R Hill Leah L Darcy John M JM Garruto Ralph M RM

Healthcare (Basel, Switzerland) 20180719 3

Seasonal variation in spatial distribution and pathogen prevalence of <i>Borrelia burgdorferi</i> in blacklegged ticks (<i>Ixodes scapularis</i>) influences human population risk of Lyme disease in peri-urban built environments. Parks, gardens, playgrounds, school campuses and neighborhoods represent a significant risk for Lyme disease transmission. From June 2012 through May 2014, ticks were collected using 1 m² corduroy cloths dragged over low-lying vegetation parallel to walkways with high hu ...[more]

PMID: 30029458

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Project description:BackgroundSince the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by environmental variables. However, seasonality is expected to be driven by host social behavior, particularly in highly susceptible populations. A key gap in understanding the role of social behavior in respiratory disease seasonality is our incomplete understanding of the seasonality of indoor human activity.MethodsWe leverage a novel data stream on human mobility to characterize activity in indoor versus outdoor environments in the United States. We use an observational mobile app-based location dataset encompassing over 5 million locations nationally. We classify locations as primarily indoor (e.g. stores, offices) or outdoor (e.g. playgrounds, farmers markets), disentangling location-specific visits into indoor and outdoor, to arrive at a fine-scale measure of indoor to outdoor human activity across time and space.ResultsWe find the proportion of indoor to outdoor activity during a baseline year is seasonal, peaking in winter months. The measure displays a latitudinal gradient with stronger seasonality at northern latitudes and an additional summer peak in southern latitudes. We statistically fit this baseline indoor-outdoor activity measure to inform the incorporation of this complex empirical pattern into infectious disease dynamic models. However, we find that the disruption of the COVID-19 pandemic caused these patterns to shift significantly from baseline and the empirical patterns are necessary to predict spatiotemporal heterogeneity in disease dynamics.ConclusionsOur work empirically characterizes, for the first time, the seasonality of human social behavior at a large scale with a high spatiotemporal resolutio and provides a parsimonious parameterization of seasonal behavior that can be included in infectious disease dynamics models. We provide critical evidence and methods necessary to inform the public health of seasonal and pandemic respiratory pathogens and improve our understanding of the relationship between the physical environment and infection risk in the context of global change.FundingResearch reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM123007.

Dataset Information

Lyme Disease Transmission Risk: Seasonal Variation in the Built Environment.

Publications

Lyme Disease Transmission Risk: Seasonal Variation in the Built Environment.

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