( ies have examined variations in climate...)A new view on Lyme disease: Rodents hold the key to annual risk

ies have examined variations in climate and white-tailed deer population dynamics as determinants of tick abundance and disease risk. But few have investigated the impacts of fluctuations in the abundance of hosts for larval ticks, and none have examined all of these variables--temperature, precipitation, deer, mice, chipmunks, and acorns--simultaneously over such a long period. From 1991 to 2004, the researchers collected temperature and precipitation data, and estimated the abundance of acorns and animals on six plots of land. From this 13-year dataset, they developed computer models to estimate how each of the 11 variables (including multiple climate and deer indexes) contributed to yearly variations in the density of infected ticks and thus risk of human exposure.

While none of the climate variables influenced nymphal infection prevalence, higher temperatures in the previous year and precipitation patterns in the current year had weak, though unexpected, effects on total density and density of infected nymphs. It's thought that higher temperatures keep tick populations down, but the models showed them increasing both total density and density of infected nymphs. And though tick survival is expected to rise with precipitation, the models found the highest tick numbers at intermediate precipitation levels. These inconsistencies can be explored by incorporating other variables with documented effects into the approach outlined here. Also surprising, the researchers found that even a 3-fold variation in deer numbers had no impact on subsequent nymph abundance.

Density of infected nymphs--the principal determinant of Lyme disease risk--varied significantly from year to year, fueled mostly by large fluctuations in total nymph density, which in turn depended mostly on fluctuations in abundance of acorns, mice, and chipmunks. Interestingly, though chipmunk densities are generally lower than mice, their numbers were the best predictor of total nymph d
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Source:Public Library of Science

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