Literature DB >> 9220682

Simulation of blacklegged tick (Acari:Ixodidae) population dynamics and transmission of Borrelia burgdorferi.

G A Mount1, D G Haile, E Daniels.   

Abstract

A model (LYMESIM) was developed for computer simulation of blacklegged tick, Ixodes scapularis Say, population dynamics and transmission of the Lyme disease agent. Borrelia burgdorferi Johnson. Schmid, Hyde, Steigerwalt & Brenner, LYMESIM simulates the effects of ambient temperature, saturation deficit, precipitation, habitat type, and host type and density on tick populations. Epidemiological parameters including host infectivity, tick infectivity, transovarial transmission, and transstadial transmission are included in the model to simulate transmission of the Lyme disease spirochete between vector ticks and vertebrate hosts. Validity of LYMESIM was established by comparing simulated and observed populations of immature I. scapularis on white-footed mice. Peromyscus leucopus, (Rafinesque), at 2 locations in Massachusetts. Validity also was indicated by comparisons of simulated and observed seasonality of blacklegged ticks in New York, Massachusetts, Florida, and Oklahoma-Arkansas. Further model validity was shown by correlation between simulated and observed numbers of immature ticks engorging on white-footed mice at 3 sites in Massachusetts. The model produced acceptable values for initial population growth rate, generation time, and 20-yr population density when historical meteorological data for 16 locations in eastern North America were used. Realistic rates of infection in ticks were produced for locations in the northeastern and northcentral United States. LYMESIM was used to study the effect of white-footed mouse and white-tailed deer, Odocoileus virginianus (Zimmerman), densities on tick density and infection rates. The model was also used to estimate tick density thresholds for maintenance of B. burgdorferi.

Entities:  

Mesh:

Year:  1997        PMID: 9220682     DOI: 10.1093/jmedent/34.4.461

Source DB:  PubMed          Journal:  J Med Entomol        ISSN: 0022-2585            Impact factor:   2.278


  16 in total

1.  How ticks keep ticking in the adversity of host immune reactions.

Authors:  Rachel Jennings; Yang Kuang; Horst R Thieme; Jianhong Wu; Xiaotian Wu
Journal:  J Math Biol       Date:  2018-11-26       Impact factor: 2.259

Review 2.  Will Culling White-Tailed Deer Prevent Lyme Disease?

Authors:  K J Kugeler; R A Jordan; T L Schulze; K S Griffith; P S Mead
Journal:  Zoonoses Public Health       Date:  2015-12-18       Impact factor: 2.702

3.  Climate change influences on the annual onset of Lyme disease in the United States.

Authors:  Andrew J Monaghan; Sean M Moore; Kevin M Sampson; Charles B Beard; Rebecca J Eisen
Journal:  Ticks Tick Borne Dis       Date:  2015-05-15       Impact factor: 3.744

4.  Prevalence of Lyme disease Borrelia spp. in ticks from migratory birds on the Japanese mainland.

Authors:  F Ishiguro; N Takada; T Masuzawa; T Fukui
Journal:  Appl Environ Microbiol       Date:  2000-03       Impact factor: 4.792

Review 5.  Prevention of lyme disease and other tick-borne infections.

Authors:  Roger P Clark; Linden T Hu
Journal:  Infect Dis Clin North Am       Date:  2008-09       Impact factor: 5.982

6.  Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach.

Authors:  Sen Li; Nienke Hartemink; Niko Speybroeck; Sophie O Vanwambeke
Journal:  PLoS One       Date:  2012-06-25       Impact factor: 3.240

7.  LYMESIM 2.0: An Updated Simulation of Blacklegged Tick (Acari: Ixodidae) Population Dynamics and Enzootic Transmission of Borrelia burgdorferi (Spirochaetales: Spirochaetaceae).

Authors:  Holly Gaff; Rebecca J Eisen; Lars Eisen; Robyn Nadolny; Jenna Bjork; Andrew J Monaghan
Journal:  J Med Entomol       Date:  2020-05-04       Impact factor: 2.435

8.  Increasing habitat suitability in the United States for the tick that transmits Lyme disease: a remote sensing approach.

Authors:  Agustín Estrada-Peña
Journal:  Environ Health Perspect       Date:  2002-07       Impact factor: 9.031

9.  Climate, deer, rodents, and acorns as determinants of variation in lyme-disease risk.

Authors:  Richard S Ostfeld; Charles D Canham; Kelly Oggenfuss; Raymond J Winchcombe; Felicia Keesing
Journal:  PLoS Biol       Date:  2006-05-09       Impact factor: 8.029

10.  A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.

Authors:  John S Brownstein; Theodore R Holford; Durland Fish
Journal:  Environ Health Perspect       Date:  2003-07       Impact factor: 9.031

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.