Influence of Detection Method and Study Area Scale on Syphilis Cluster Identification in North Carolina.

BACKGROUND: Identifying geographical clusters of sexually transmitted infections can aid in targeting prevention and control efforts. However, detectable clusters can vary between detection methods because of different underlying assumptions. Furthermore, because disease burden is not geographically homogenous, the reference population is sensitive to the study area scale, affecting cluster outcomes. We investigated the influence of cluster detection method and geographical scale on syphilis cluster detection in Mecklenburg County, North Carolina. METHODS: We analyzed primary and secondary syphilis cases reported in North Carolina (2003-2010). Primary and secondary syphilis incidence rates were estimated using census tract-level population estimates. We used 2 cluster detection methods: local Moran's I using an areal adjacency matrix and Kulldorff's spatial scan statistic using a variable size moving circular window. We evaluated 3 study area scales: North Carolina, Piedmont region, and Mecklenburg County. We focused our investigation on Mecklenburg, an urban county with historically high syphilis rates. RESULTS: Syphilis clusters detected using local Moran's I and Kulldorff's scan statistic overlapped but varied in size and composition. Because we reduced the scale to a high-incidence urban area, the reference syphilis rate increased, leading to the identification of smaller clusters with higher incidence. Cluster demographic characteristics differed when the study area was reduced to a high-incidence urban county. CONCLUSIONS: Our results underscore the importance of selecting the correct scale for analysis to more precisely identify areas with high disease burden. A more complete understanding of high-burden cluster location can inform resource allocation for geographically targeted sexually transmitted infection interventions.

Randomized Intervention of Self-Collected Sampling for Human Papillomavirus Testing in Under-Screened Rural Women: Uptake of Screening and Acceptability.

BACKGROUND: Our aim was to determine if cervical cancer screening uptake would increase among under-screened women living in rural Ontario, Canada, if at-home self-collected sampling for human papillomavirus (HPV) testing was offered as a primary cervical cancer screening modality, compared to invited papanicolaou (Pap) testing or routine opportunistic screening. METHODS: Women 30-70 years of age who were overdue for cervical cancer screening were randomized to receive (1) an at-home self-collected HPV kit, (2) a reminder invitation for Pap testing, or (3) standard of care opportunistic screening. The first two arms were also asked demographic and screening history questions. Women randomized to arm 1 were asked about acceptability. RESULTS: In total, 818 eligible women were identified in a small rural community in Southwestern Ontario: 335 received a self-collected HPV testing kit, 331 received a reminder letter, and 152 received standard of care. In the HPV self-collection arm, 21% (70/335) returned the sample and questionnaire and 11% (37/335) opted to undergo Pap testing. In total, 32% from the HPV self-collection arm, 15% (51/331) from the Pap invitation arm, and 8.5% (13/152) with standard of care were screened. Women receiving the self-collected HPV kit were 3.7 (95% confidence interval 2.2-6.4) times more likely to undergo screening compared to the standard of care arm. In the HPV self-sampling arm, 80% (56/70) said they would be very likely to choose self-collected sampling in the future. CONCLUSIONS: Providing self-collected sampling for HPV testing was more effective than sending reminder letters to increase screening coverage in under-screened women.

Barriers and Facilitators to Cervical Cancer Screening Among Women in Rural Ontario, Canada: The Role of Self-Collected HPV Testing.

PURPOSE: The addition of human papillomavirus (HPV) testing to primary cervical cancer screening provides an opportunity to employ less invasive cervical cancer screening modalities. The objective of this study was to explore the initial reaction and perception to HPV self-collected testing, in the context of current barriers and facilitators to cervical cancer screening, among women in an underscreened community in rural Ontario. METHODS: Age-stratified focus groups were conducted with women 18-70 years of age in rural Ontario to discuss cervical cancer screening. Women were recruited using purposive sampling of underscreened women and women in the general community. Qualitative thematic analysis of focus group transcripts identified the barriers, facilitators, and role of HPV self-collected testing for cervical cancer screening. RESULTS: Four focus groups were conducted with a total of 25 women. Overall, women were very positive toward self-collected HPV testing. HPV self-collected testing was felt to address many of the logistical (eg, inconvenient clinic hours, lack of time) and procedural barriers (embarrassment, lack of social distance in a small town) to current screening practices. However, self-collected HPV testing does not address barriers related to cervical cancer knowledge (eg, fear of cancer). Women identified issues related to test reliability, confidence in the ability to self-collect, and education around testing that would need to be addressed prior to implementation. Generational differences were noted in the acceptability of self-collected HPV testing between older and younger women. CONCLUSIONS: HPV self-collected testing was perceived as a facilitator for screening, and it was well accepted in this rural community.

Does core area theory apply to sexually transmitted diseases in rural environments?

BACKGROUND: Our objective was to determine the extent to which geographical core areas for gonorrhea and syphilis are located in rural areas as compared with urban areas. METHODS: Incident gonorrhea (January 1, 2005-December 31, 2010) and syphilis (January 1, 1999-December 31, 2010) rates were estimated and mapped by census tract and quarter. Rurality was measured using percent rural and rural-urban commuting area (rural, small town, micropolitan, or urban). SaTScan was used to identify spatiotemporal clusters of significantly elevated rates of infection. Clusters lasting 5 years or longer were considered core areas; clusters of shorter duration were considered outbreaks. Clusters were overlaid on maps of rurality and qualitatively assessed for correlation. RESULTS: Twenty gonorrhea core areas were identified: 65% were in urban centers, 25% were in micropolitan areas, and the remaining 10% were geographically large capturing combinations of urban, micropolitan, small town, and rural environments. Ten syphilis core areas were identified with 80% in urban centers and 20% capturing 2 or more rural-urban commuting areas. All 10 (100%) of the syphilis core areas overlapped with gonorrhea core areas. CONCLUSIONS: Gonorrhea and syphilis rates were high for rural parts of North Carolina; however, no core areas were identified exclusively for small towns or rural areas. The main pathway of rural sexually transmitted disease (STI) transmission may be through the interconnectedness of urban, micropolitan, small town, and rural areas. Directly addressing STIs in urban and micropolitan communities may also indirectly help address STI rates in rural and small town communities.

Mycoplasma genitalium presence, resistance and epidemiology in Greenland.

OBJECTIVES: Greenland reports the highest rates of chlamydial infection and gonorrhea in the Arctic. Our objective was to determine the presence, and describe the basic epidemiology, of Mycoplasma genitalium for Greenland. STUDY DESIGN: Cross-sectional study. METHODS: 314 residents from Nuuk and Sisimiut, between the ages of 15 and 65 years, participated in "Inuulluataarneq" (the Greenland Sexual Health Project) between July 2008 and November 2009. Participants provided self-collected samples for sexually transmitted infection (STI) testing and completed a sexual health survey. Descriptive statistics and logistic regression were used to summarize the basic characteristics of STI cases overall and M. genitalium and Chlamydia trachomatis specifically. Clinically relevant characteristics in each full model were gender (male or female), age (in years), age at sexual debut (in years), number of sexual partners in the past 3 months (continuous) and history of forced sex and community. RESULTS: The overall prevalence of STIs was 19.0%, specifically: 9.8% for M. genitalium and 9.4% for C. trachomatis; 100% of M. genitalium-positive cases carried macrolide resistance determinants. Being female [OR = 3.2; 95% confidence interval (CI): 1.1-9.8] and younger age (OR = 0.9; 95% CI: 0.9-1.0) were associated with M. genitalium positivity. Age was also associated with C. trachomatis (OR = 0.9; 95% CI: 0.8-0.9) and STI positivity overall (OR = 0.9; 95% CI: 0.9-0.9). CONCLUSIONS: We observed a high prevalence of M. genitalium and macrolide resistance in this study. A better understanding of M. genitalium sequelae is needed to inform policy around testing, treatment, control and antibiotic use.

Log Gaussian Cox processes and spatially aggregated disease incidence data.

This article presents a methodology for modeling aggregated disease incidence data with the spatially continuous log-Gaussian Cox process. Statistical models for spatially aggregated disease incidence data usually assign the same relative risk to all individuals in the same reporting region (census areas or postal regions). A further assumption that the relative risks in two regions are independent given their neighbor's risks (the Markov assumption) makes the commonly used Besag-York-Mollié model computationally simple. The continuous model proposed here uses a data augmentation step to sample from the posterior distribution of the exact locations at each step of an Markov chain Monte Carlo algorithm, and models the exact locations with an log-Gaussian Cox process. A simulation study shows the log-Gaussian Cox process model consistently outperforming the Besag-York-Mollié model. The method is illustrated by making inference on the spatial distribution of syphilis risk in North Carolina. The effect of several known social risk factors are estimated, and areas with risk well in excess of that expected given these risk factors are identified.

Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping.

BACKGROUND: Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME) and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. RESULTS: In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. CONCLUSIONS: Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.

Sexually transmitted disease core theory: roles of person, place, and time.

The authors' purpose was to expand sexually transmitted disease core theory by examining the roles of person, place, and time in differentiating geographic core areas from outbreak areas. The authors mapped yearly census-tract-level syphilis rates for San Francisco, California, based on new primary and secondary syphilis cases reported to the San Francisco City sexually transmitted disease surveillance program between January 1, 1985, and December 31, 2007. SaTScan software (Information Management Services, Inc., Silver Spring, Maryland) was used to identify geographic clusters of significantly elevated syphilis rates over space and time. The authors graphed epidemic curves for 1) core areas, 2) outbreak areas, 3) neither core nor outbreak areas, and 4) noncore areas, where noncore areas included outbreaks, and stratified these curves according to demographic characteristics. Five clusters of significantly elevated primary and secondary syphilis rates were identified. A 5-year threshold was useful for differentiating core clusters from outbreak clusters. Epidemic curves for core areas, outbreak areas, neither core nor outbreak areas, and noncore areas were perfectly synchronized in phase trends and wavelength over time, even when broken down by demographic characteristics. Between epidemics, the occurrence of syphilis affected all demographic groups equally. During an epidemic, a temporary disparity in syphilis occurrence arose and a homogeneous core group of cases could be defined.

Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina?

PURPOSE: To determine if the spatial pattern of gonorrhea observed for North Carolina was influenced by neighborhood-level sociocultural determinants of health, including race/ethnicity. METHODS: A generalized linear mixed model with spatially correlated random effects was fit to measure the influence of socio-cultural factors on the spatial pattern of gonorrhea reported to the North Carolina State Health Department (January 1, 2005 to March 31, 2008). RESULTS: Neighborhood gonorrhea rates increased as the percent single mothers increased (25th to 75th neighborhood percentile Relative Rate 1.18, 95% CI 1.12, 1.25), and decreased as socioeconomic status increased (Relative Rate 0.89, 95% CI 0.84, 0.95). Increasing numbers of men in neighborhoods with more women than men did not change the gonorrhea rate, but was associated with decreased rates in neighborhoods with more men than women. Living in the mountains was protective for all race/ethnicities. Rurality was associated with decreased rates for Blacks and increased rates for Native Americans outside the mountains. PURPOSE: Neighborhood-level sociocultural factors, primarily those indicative of neighborhood deprivation, explained a significant proportion of the spatial pattern of gonorrhea in both urban and rural communities. Race/ethnicity was an important proxy for social and cultural factors not captured by measures of socioeconomic status.

Geomasking sensitive health data and privacy protection: an evaluation using an E911 database.

Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of individuals when this condition is not met. Using household data from 2007, we evaluated the performance of donut geomasking in Orange County, North Carolina. We calculated the estimated k-anonymity for every household based on the assumption of uniform household distribution. We then determined the actual k-anonymity by revealing household locations contained in the county E911 database. Census block groups in mixed-use areas with high population distribution heterogeneity were the most likely to have privacy protection below selected criteria. For heterogeneous populations, we suggest tripling the minimum displacement area in the donut to protect privacy with a less than 1% error rate.

Mapping health data: improved privacy protection with donut method geomasking.

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.