New predictive model correlates tick abundance with climate KINGSTON, R.I. — May 11, 2001 — Using elements of a new climate model being developed at the University of Rhode Island, tick expert Thomas Mather, professor of entomology and director of the URI Center for Vector-Borne Disease, said that the summer of 2001 should be an average year for deer ticks and Lyme disease in Rhode Island. “Tick abundance should be about the same as it was last year, which means that we should expect about 500 to 700 cases of Lyme disease in the state,” said Mather. Through much of the 1990s, deer ticks were abundant in alternating years, and Mather correlated that occurrence with high precipitation levels in those years. When the weather is dry, tick abundance and risk for disease is low. Last year was an average year for both precipitation and deer ticks, the same as is being predicted for this year. The peak transmission period for Lyme disease is from May to July, when the pin-head size nymphal stage ticks are most active. In addition to Lyme disease, deer ticks also carry a malaria-like protozoan that causes babesiosis and a bacterium that causes human granulocytic ehrlichiosis (HGE). Like Lyme disease, both of these other infections carried by deer ticks cause flu-like symptoms, are difficult to diagnose, and can be fatal. “We’ve clearly seen evidence that in years with high moisture levels there are more ticks,” explained Mather. “Because of this relationship between climate and vectors, we should be able to develop climate-driven predictive models that will determine whether we’ll have more ticks in a given year, and also identify where the highest concentrations will be.” Working with Michael Brewer, a terrestrial climatologist at URI, Mather hopes to develop predictive maps, much like those found on some weather reports that point to severe weather, heat disease risk, or high pollen counts. Mather said the maps will indicate where and when Lyme disease risk is greatest. Brewer is evaluating 22 climate parameters, like precipitation, soil moisture, temperature and others, to identify the most accurate predictive measures for inclusion in the model. Mather and Brewer have applied to the National Oceanographic and Atmospheric Administration for funding to further develop the model to include a tick watch/warning system, similar to the hurricane watch/warning system used to alert residents in particular areas of approaching storms. “Being able to predict the levels of risk will allow us to anticipate the public health response necessary in a given area,” Mather said. “Under ‘watch’ conditions, for instance, we might recommend increased surveillance for ticks and targeted tick bite prevention education programs to be delivered by local officials, while under ‘warning’ conditions we might advocate more aggressive tick bite prevention measures, including pesticide spraying. It will help local communities prepare in a timely way for the necessary public health response.” Mather hopes to eventually also use the model to predict mosquito abundance and risk of West Nile virus and Eastern equine encephalitis. Predicting mosquito abundance is much more complicated, however, because there are so many different species of mosquitoes, each responding somewhat differently to climate factors. The mosquitoes that carry West Nile virus, for instance, are most abundant in dry years while those carrying EEE are most abundant in high moisture years. “What we can do, though, is look at virus activity in general, determine which of the viruses are active in similar ecological cycles, and then look at the climate factors associated with them.” Mather expects that, with funding, a preliminary watch-warning system for predicting tick-borne disease risk will be in place for the next tick-season. Until then, watch the weather. For Information: Thomas Mather 874-5616, Todd McLeish 874-7892