Sexually transmitted infections (STI) remain highly endemic in the southeast United States. Unlike most of the rest of the US, STIs in the southeast are prevalent in both urban and rural areas. Controlling STIs requires a combination of ongoing sustained efforts and rapid intervention during outbreaks. Previously, spatial representations of STI have provided useful information for surveillance and targeted intervention, while simultaneously providing important clues regarding STI epidemiology. For example, geographical core areas, a phenomenon described over 20 years ago, remains an important construct today. Despite these important contributions of spatial representations of STIs, most applications of spatial statistics in STI epidemiology have been relatively rudimentary and based solely in urban areas. We propose to use modern geostatistical methods to develop improved methods of STI surveillance and investigate core areas of transmission. Specifically, our aims are 1 )To develop and evaluate a spatiotemporal model to monitor reported STIs and identify outbreaks at an early stage, using syphilis and gonorrhea as examples;2) To characterize the spatial pattern of syphilis incidence rates and case densities during a known outbreak extending across two rural counties and to relate this pattern to a sexual network analysis;and 3) To evaluate the concept of geographical core, or risk space, for gonorrhea in rural and urban areas and at multiple spatial scales. To address these aims, we will use existing and routinely collected surveillance data for syphilis and gonorrhea. Our primary strategy will use Bayesian Maximum Entropy models, incorporating both spatial and temporal data. We will also assess other methods to determine the most efficient strategies for evaluating outbreaks and representing network structure spatially. We introduce and evaluate a new spatial measure, termed the """"""""transmission potential"""""""", which combines aspects of incidence rate and case density. Our development and application of these spatial methods will improve surveillance procedures and provide a modeling procedure generalizable throughout the U.S. Use of these procedures will facilitate targeted interventions to reduce the burden of these important diseases. Furthermore, we will obtain critical, new information regarding STI epidemiology in southeastern U.S., a region with disproportionate burden of these infections.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI067913-05
Application #
7844825
Study Section
Social Sciences and Population Studies Study Section (SSPS)
Program Officer
David, Hagit S
Project Start
2006-06-01
Project End
2012-07-31
Budget Start
2010-06-01
Budget End
2012-07-31
Support Year
5
Fiscal Year
2010
Total Cost
$341,950
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Escamilla, Veronica; Hampton, Kristen H; Gesink, Dionne C et al. (2016) Influence of Detection Method and Study Area Scale on Syphilis Cluster Identification in North Carolina. Sex Transm Dis 43:216-21
Gesink, Dionne C; Sullivan, Ashleigh B; Norwood, Todd A et al. (2013) Does core area theory apply to sexually transmitted diseases in rural environments? Sex Transm Dis 40:32-40
Doherty, Irene A; Serre, Marc L; Gesink, Dionne et al. (2012) Sexual networks, surveillance, and geographical space during syphilis outbreaks in rural North Carolina. Epidemiology 23:845-51
Miller, William C (2012) Commentary: Reference-test bias in diagnostic-test evaluation: a problem for epidemiologists, too. Epidemiology 23:83-5
Li, Ye; Brown, Patrick; Gesink, Dionne C et al. (2012) Log Gaussian Cox processes and spatially aggregated disease incidence data. Stat Methods Med Res 21:479-507
Hampton, Kristen H; Serre, Marc L; Gesink, Dionne C et al. (2011) Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping. Int J Health Geogr 10:54
Sullivan, Ashleigh B; Gesink, Dionne C; Brown, Patrick et al. (2011) Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina? Ann Epidemiol 21:245-52
Doherty, Irene A (2011) Sexual networks and sexually transmitted infections: innovations and findings. Curr Opin Infect Dis 24:70-7
Gesink, Dionne C; Sullivan, Ashleigh B; Miller, William C et al. (2011) Sexually transmitted disease core theory: roles of person, place, and time. Am J Epidemiol 174:81-9
Doherty, Irene A; Adimora, Adaora A; Muth, Stephen Q et al. (2011) Comparison of sexual mixing patterns for syphilis in endemic and outbreak settings. Sex Transm Dis 38:378-84

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