Mapping Lyme Disease Incidence for Diagnostic and Preventive Decisions, Maryland

Abstract

To support diagnostic and preventive decision making, we analyzed incidence of Lyme disease in Maryland on the zip code level. Areas of high incidence were identified on the Upper Eastern Shore of the Chesapeake Bay and in counties north and east of Baltimore City. These latter foci, especially, are not visible when mapping Lyme disease on the county level.”

Timely access to health care: Customer-focused resource allocation in a hospital network

“…We use universal kriging to recreate the heterogeneity in the disease incidence data that may be lost due to aggregation at the ZIP code level (Frank, Fix, Pena, & Strickland, 2002). Since we are dealing with twelve different types of diseases, the results of kriging would give us twelve different spatio-temporally smoothed patterns.…”

Genetic Diversity of Borrelia burgdorferi Sensu Stricto in Peromyscus leucopus , the Primary Reservoir of Lyme Disease in a Region of Endemicity in Southern Maryland

“…This is the first extensive report of the population structure of B. burgdorferi sensu stricto in the mid-Atlantic region of North America, as well as one of few extensive genetic surveys of spirochetes found in rodent reservoir populations over a large geographic region. Maryland reports moderate levels of LD transmission (12) and is at the geographic juxtaposition between regions with high and low LD transmission rates. Examining the genetic polymorphisms of B. burgdorferi found in the reservoir population in this region may help to elucidate the disparate LD transmission patterns observed along the eastern United States.…”

Spatio-temporal patterns in county-level incidence and reporting of Lyme disease in the northeastern United States, 1990–2000

“…Each map requires different data and reveals different elements of the interacting processes determining Lyme transmission. The literature contains examples of risk maps for Lyme disease for particular communities (Glass et al 1995;Dister et al 1997), for particular states (Kitron and Kazmierczak 1997;Frank et al 2002), and for the entire nation (Dennis et al 1998;Estrada-Pena 1998;US CDC 2001). Risk maps for Lyme disease have been constructed from incidence data (Kitron and Kazmierczak 1997;Frank et al 2002), tick distributions (Dennis et al 1998, and environmental risk factors (Glass et al 1995;Dister et al 1997;Estrada-Pena 1998;US CDC 2001).…”

“…The literature contains examples of risk maps for Lyme disease for particular communities (Glass et al 1995;Dister et al 1997), for particular states (Kitron and Kazmierczak 1997;Frank et al 2002), and for the entire nation (Dennis et al 1998;Estrada-Pena 1998;US CDC 2001). Risk maps for Lyme disease have been constructed from incidence data (Kitron and Kazmierczak 1997;Frank et al 2002), tick distributions (Dennis et al 1998, and environmental risk factors (Glass et al 1995;Dister et al 1997;Estrada-Pena 1998;US CDC 2001). Risk maps tend to be constructed either from a snapshot of the disease at a particular point in time (Glass et al 1995;Dister et al 1997), or by pooling or averaging disease incidence across the entire period of surveillance (Kitron and Kazmierczak 1997;Estrada-Pena 1998;US CDC 2001;Frank et al 2002).…”

“…Risk maps for Lyme disease have been constructed from incidence data (Kitron and Kazmierczak 1997;Frank et al 2002), tick distributions (Dennis et al 1998, and environmental risk factors (Glass et al 1995;Dister et al 1997;Estrada-Pena 1998;US CDC 2001). Risk maps tend to be constructed either from a snapshot of the disease at a particular point in time (Glass et al 1995;Dister et al 1997), or by pooling or averaging disease incidence across the entire period of surveillance (Kitron and Kazmierczak 1997;Estrada-Pena 1998;US CDC 2001;Frank et al 2002).…”