According to the Centers for Disease Control (CDC) reports 1990-2008, New York state was the most affected by Lyme disease outbreaks, followed by Pennsylvania, Connecticut, New Jersey, Massachusetts, Wisconsin and Maryland. The risk of exposure to Lyme disease is considered less in other states but anyone spending time outdoors in vegetated areas should exercise precaution over tick bites. The most infamous of cases in the history of Lyme disease is the outbreak in Old Lyme, Connecticut, which led to the disease’s classification in the 1970s.
Lyme disease is the most prevalent tick-borne condition in the US and is more of a concern there than in the rest of the world. However, many doctors remain unaware of the risk of Lyme disease and its symptoms which may mean that the disease is vastly under-reported. The CDC estimated around 35,000 new cases in 2008 but the true incidence may be considerably higher. Most cases are reported in June and July each year, with the vast majority occurring between April and October. In places such as Texas, where Lyme disease is not considered endemic, the rate of confirmed cases is only around 0.4 per 100,000 people. The likelihood is that many cases are not being recognized by physicians in Texas and may be misdiagnosed.
The Lone Star tick (Amblyomma americanum) is also thought to carry Borrelia burgdorferi, the bacterium that causes Lyme disease outbreaks, and this may mean that patients are suffering co-infections which remain undiagnosed and untreated. Differences in how cases are reported around the world can mean that rates of incidence in Europe, Asia, and Russia may not be directly comparable to those in North America.
Lyme Disease Cases Increasing
The presence of ticks in a particular area is connected to climatic conditions and research in recent years appears to show that tick population can be fairly accurately predicted using a combination of temperature measurements and NDVI (Normalized Difference Vegetation Index). NDVI is a tool where the distribution of living green vegetation is able to be detected, usually using satellite imagery and remote sensing techniques (Kitron et al. 1997, Estrada-Peña 2002). Ticks are much more likely to be present where lush vegetation is available, particularly where this vegetation is fairly continuous and not broken by open spaces or dry areas.
Using such assessments it is possible to create predictive Lyme disease maps and tailor public health warnings to the likely risk of a Lyme disease outbreak. Such maps have been used in North America at both the state and national level and similar techniques are also in use in Europe (Nicholson and Mather 1996, Dister et al. 1997, Kitron et al. 1997, Estrada-Peña 1998, Randolph 2001, Randolph 2000). Mapping the distribution of the Ixodes ticks is not the only way that health authorities are looking at predicting or, more optimistically, preventing Lyme disease outbreaks.
Connecting Animal Populations with Lyme Disease Outbreaks
Researchers at the Institute of Ecosystem Studies in Millbrook, New York, issued a warning in 1999 that that the large fall acorn crop could mean a major Lyme disease outbreak the following year. Their reasoning was that animals such as mice and deer would be attracted to the area and that these are the major host-animals for ticks which transmit Lyme disease. As it was, there were no reports of major Lyme disease outbreaks in the area connected to the oak forests, perhaps due to people being more aware of the risk and taking steps to prevent tick bites or due to other factors.
Further research at the University of Connecticut and Oregon State University established a clear connection between the size of an acorn crop and the number of ticks in an area. Where acorn production increased so did the numbers of gypsy moths, white-footed mice, and deer, and in years after a large acorn crop the numbers of tick larvae were said to be eight times those of poor years for acorns. The number of ticks on each mouse were also stated as being about 40% higher following a good acorn crop. This kind of research is helpful, perhaps, in giving guidance on the avoidance of tick-endemic areas and in assessing the risk levels for Lyme disease outbreaks but there is little that can be done to reduce the levels of ticks without also affecting the wider ecosystem of an area.
Nicholson MC, Mather TN. (1996) Methods for evaluating Lyme disease risks using geographic information systems and geospatial analysis. Journal of Medical Entomology, 33(5): 711-720.
Estrada-Peña A. (1998) Geostatistics and remote sensing as predictive tools of tick distribution: a cokriging system to estimate Ixodes scapularis (Acari : Ixodidae) habitat suitability in the United States and Canada from advanced very high resolution radiometer satellite imagery. Journal of Medical Entomology, 35(6): 989-995.
Dister SW, et al. (1997) Landscape characterization of peridomestic risk for Lyme disease using satellite imagery. American Journal of Tropical Medicine and Hygiene, 57(6): 687-692.
Randolph SE. (2001). The shifting landscape of tick-borne zoonoses: tick-borne encephalitis and Lyme borreliosis in Europe. Philosophical Transactions of the Royal Society of London Series B Biological Sciences.; 356:1045-56
Randolph SE. (2000) Ticks and tick-borne disease systems in space and from space. Advances in Parasitology, 47: 217-243.
WHO | Using climate to predict disease outbreaks: a review http://j.mp/llirjl
Kitron U, et al. (1997) Spatial analysis of the distribution of lacrosse encephalitis in Illinois, using a geographic information system and local and global spatial statistics. American Journal of Tropical Medicine and Hygiene, 57(4): 469-475.
Orloski KA, et al. (2000) Surveillance for Lyme disease – United States 1992-1998. Morbidity and Mortality Weekly Report, Centres for Disease Control, Atlanta, 28: 1-11.