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Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility
Lyme disease is the most prevalent tick-borne disease in the United States, which humans acquire from an infected tick of the genus Ixodes (primarily Ixodes scapularis). While previous studies have provided useful insights into various aspects of Lyme disease, the tick's host preference in the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453107/ https://www.ncbi.nlm.nih.gov/pubmed/30997436 http://dx.doi.org/10.1016/j.idm.2019.03.001 |
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author | Nguyen, Aileen Mahaffy, Joseph Vaidya, Naveen K. |
author_facet | Nguyen, Aileen Mahaffy, Joseph Vaidya, Naveen K. |
author_sort | Nguyen, Aileen |
collection | PubMed |
description | Lyme disease is the most prevalent tick-borne disease in the United States, which humans acquire from an infected tick of the genus Ixodes (primarily Ixodes scapularis). While previous studies have provided useful insights into various aspects of Lyme disease, the tick's host preference in the presence of multiple hosts has not been considered in the existing models. In this study, we develop a transmission dynamics model that includes the interactions between the primary vectors involved: blacklegged ticks (I. scapularis), white-footed mice (Peromyscus leucopus), and white-tailed deer (Odocoileus virginianus). Our model shows that the presence of multiple vectors may have a significant impact on the dynamics and spread of Lyme disease. Based on our model, we also calculate the basic reproduction number, [Formula: see text] , a threshold value that predicts whether a disease exists or dies out. Subsequent extensions of the model consider seasonality of the tick's feeding period and mobility of deer between counties. Our results suggest that a longer tick peak feeding period results in a higher infection prevalence. Moreover, while the deer mobility may not be a primary factor for short-term emergence of Lyme disease epidemics, in the long-run it can significantly contribute to local infectiousness in neighboring counties, which eventually reach the endemic steady state. |
format | Online Article Text |
id | pubmed-6453107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-64531072019-04-17 Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility Nguyen, Aileen Mahaffy, Joseph Vaidya, Naveen K. Infect Dis Model Original Research Article Lyme disease is the most prevalent tick-borne disease in the United States, which humans acquire from an infected tick of the genus Ixodes (primarily Ixodes scapularis). While previous studies have provided useful insights into various aspects of Lyme disease, the tick's host preference in the presence of multiple hosts has not been considered in the existing models. In this study, we develop a transmission dynamics model that includes the interactions between the primary vectors involved: blacklegged ticks (I. scapularis), white-footed mice (Peromyscus leucopus), and white-tailed deer (Odocoileus virginianus). Our model shows that the presence of multiple vectors may have a significant impact on the dynamics and spread of Lyme disease. Based on our model, we also calculate the basic reproduction number, [Formula: see text] , a threshold value that predicts whether a disease exists or dies out. Subsequent extensions of the model consider seasonality of the tick's feeding period and mobility of deer between counties. Our results suggest that a longer tick peak feeding period results in a higher infection prevalence. Moreover, while the deer mobility may not be a primary factor for short-term emergence of Lyme disease epidemics, in the long-run it can significantly contribute to local infectiousness in neighboring counties, which eventually reach the endemic steady state. KeAi Publishing 2019-03-28 /pmc/articles/PMC6453107/ /pubmed/30997436 http://dx.doi.org/10.1016/j.idm.2019.03.001 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Article Nguyen, Aileen Mahaffy, Joseph Vaidya, Naveen K. Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title | Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title_full | Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title_fullStr | Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title_full_unstemmed | Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title_short | Modeling transmission dynamics of lyme disease: Multiple vectors, seasonality, and vector mobility |
title_sort | modeling transmission dynamics of lyme disease: multiple vectors, seasonality, and vector mobility |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453107/ https://www.ncbi.nlm.nih.gov/pubmed/30997436 http://dx.doi.org/10.1016/j.idm.2019.03.001 |
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