County-level Incidence Research Articles

Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009

Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.

Association between cutaneous melanoma incidence rates among white US residents and county-level estimates of solar ultraviolet exposure

Recent US studies have raised questions as to whether geographic differences in cutaneous melanoma incidence rates are associated with differences in solar ultraviolet (UV) exposure. We sought to assess the association of solar UV exposure with melanoma incidence rates among US non-Hispanic whites. We assessed the association between county-level estimates of average annual solar UV exposure for 1961 to 1990 and county-level melanoma incidence rates during 2004 to 2006. We used Poisson multilevel mixed models to calculate incidence density ratios by cancer stage at diagnosis while controlling for individuals' age and sex and for county-level estimates of solar UV exposure, socioeconomic status, and physician density. Age-adjusted rates of early- and late-stage melanoma were both significantly higher in high solar UV counties than in low solar UV counties. Rates of late-stage melanoma incidence were generally higher among men, but younger women had a higher rate of early-stage melanoma than their male counterparts. Adjusted rates of early-stage melanoma were significantly higher in high solar UV exposure counties among men aged 35 years or older and women aged 65 years or older. The relationship between individual-level UV exposure and risk for melanoma was not evaluated. County-level solar UV exposure was associated with the incidence of early-stage melanoma among older US adults but not among younger US adults. Additional studies are needed to determine whether exposure to artificial sources of UV exposure or other factors might be mitigating the relationship between solar UV exposure and risk for melanoma.

U.S. Geographic Distribution of Prevaccine Era Cervical Cancer Screening, Incidence, Stage, and Mortality

Cervical cancer prevention programs are being reconfigured to incorporate human papillomavirus (HPV) testing and vaccination. To define priority areas for prevention efforts, we examined the geographic distribution of cervical cancer screening, incidence, stage, and mortality in the United States, prior to the introduction of HPV-based prevention technologies. County-level cervical cancer incidence data from 37 central registries were obtained from Surveillance, Epidemiology, and End Results and North American Association of Central Cancer Registries. A spatial-temporal model that accounted for demographic and behavioral attributes was used to generate a complete view of county-level incidence from 1995 to 2004, including counties with missing data. Distribution of stage at diagnosis was examined by registry. Counties with high mortality and infrequent screening were identified using vital statistics and newly available county-level screening estimates. Compared with non-Hispanic whites and Asian and Pacific Islanders, incidence rates were higher among non-Hispanic black, American Indian and Alaska Native, and Hispanic women. Counties with infrequent screening often experienced elevated incidence and mortality rates and were located in states with suboptimal stage at diagnosis profiles. Affected areas included Appalachia, the southeastern Atlantic states, and the lower Mississippi Valley. Elevated death rates were experienced in central counties of large metropolitan areas. Geographic and racial/ethnic variability were evident in cervical cancer incidence and mortality. Women living in areas with endemic poverty would benefit from access to HPV-based prevention technologies. These findings provide a baseline for monitoring progress in cervical cancer control in the era of HPV-based prevention.

Higher Physician Density is Associated with Lower Incidence of Late-stage Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer in the United States and a leading cause of cancer related mortality. Routine screening decreases incidence and mortality; however rates of screening remain low. Physician recommendation is a key determinant of screening rates; thus, physician availability may also influence CRC incidence and mortality. Data on CRC incidence and stage at diagnosis was obtained for each county in Pennsylvania from the Pennsylvania cancer registry. Physician density (per 100,000 population) was calculated for each county using physician counts from the American Medical Association. Pearson correlation coefficients and linear regression models were used to examine the association between physician density and CRC incidence and outcomes. Primary care physician density (Pearson's correlation coefficient: -0.25, p=0.05) and gastroenterologist density (correlation coefficient -0.25, p=0.04) inversely correlated with county-level incidence of late-stage CRC. However, this association was seen only in non-metropolitan counties or those with low population density. On linear regression, non-metropolitan counties which had a high density of gastroenterologists had an incidence of late-stage CRC that was lower by 4/100,000 (reduction of 14%). Low population density counties had lower incidence of late-stage CRC by 5/100,000 (reduction of 17%) when they had at least 3.3 gastroenterologists/100,000 population compared to counties with a lower gastroenterologist-per-population ratio. Gastroenterologist density did not correlate with reduced late-stage CRC incidence prior to institution of Medicare coverage for colonoscopy for routine CRC screening. Higher gastroenterologist or PCP density is associated with 14-17% lower incidence of late-stage CRC in non-metropolitan counties or those with low population density. Efforts at increasing physician supply should target these underserved areas.

Quantification of Temporal and Spatial Dynamics of Bean pod mottle virus at Different Spatial Scales

Bean pod mottle virus (BPMV) is the most prevalent virus infecting soybean (Glycine max) in the United States; however, the temporal and spatial dynamics in BPMV at varying spatial scales has not been elucidated. To quantify the temporal and spatial dynamics of BPMV at a field scale, a quadrat-based method was developed in which six soybean rows, each consisting of 30-cm-long quadrats, were established within soybean cv. NE3001 field plots (i.e., 150 quadrats per plot) in BPMV-inoculated and non-inoculated plots. Quadrats were sampled by selecting the youngest fully expanded leaflet from each of four plants within each quadrat beginning 25 days after planting, and continued at 8- to 11-day intervals until crop senescence. Leaf sap was extracted from each 4-leaflet (bulked) sample (from each quadrat), and tested for presence of the BPMV by ELISA. Quadrat position (plot, row, and quadrat number) and the date of sampling that each quadrat first tested positive for BPMV was recorded and mapped. The rate of BPMV incidence in 2006 ranged from 0.09 to 0.12 logits/day, indicating that BPMV incidence was doubling every 5.3 to 7.7 days in 2006. Doubling times for BPMV incidence in 2007 were slower, ranging from 17.3 to 34.7 days. Analysis of spatial patterns using ordinary runs revealed that BPMV-infected quadrats were predominantly clustered within both BPMV-inoculated and non-inoculated plots throughout both growing seasons. In addition to within field plot studies, a threeyear statewide disease survey (2005-2007) was conducted in Iowa to quantify county and field scale BPMV prevalence and incidence by systematically selecting 30 plants/soybean field (8 to 16 soybean fields per county). Leaf samples were then tested for BPMV by ELISA and county-level BPMV incidence maps were generated using ArcGIS software. End-of-season BPMV prevalence was 39/96 counties in 2005 (40%), 90/99 counties in 2006 (90.1%), and 74/99 counties in 2007 (74.7%). The incidence of BPMV within Iowa counties ranged from 0 to 100% and BPMV incidence significantly increased statewide from north to south. Spatial autocorrelation (dependence) analysis using Moran's I revealed clustering for BPMV incidence among Iowa counties, indicating that BPMV incidence among counties was not random. The elucidation of the within-field temporal and spatial dynamics of BPMV and the statewide geographic distribution of BPMV in Iowa has important implications with regards to sampling, plant disease forensics, BPMV management, and risk prediction of BPMV. Accepted for publication 28 January 2010. Published 26 May 2010.

Space-time variation of malaria incidence in Yunnan province, China.

BackgroundUnderstanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring.MethodsMonthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June–September and the preceding January–February.ResultsModels revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June–September and the preceding January–February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties.ConclusionDependence between incidence in summer and the preceding January–February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January–February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province.

The Incidence Risk, Clustering, and Clinical Presentation of La Crosse Virus Infections in the Eastern United States, 2003–2007

BackgroundAlthough La Crosse virus (LACV) is one of the most common causes of pediatric arboviral infections in the United States, little has been done to assess its geographic distribution, identify areas of higher risk of disease, and to provide a national picture of its clinical presentation. Therefore, the objective of this study was to investigate the geographic distribution of LACV infections reported in the United States, to identify hot-spots of infection, and to present its clinical picture.Methods and FindingsDescriptive and cluster analyses were performed on probable and confirmed cases of LACV infections reported to the Centers for Disease Control and Prevention from 2003–2007. A total of 282 patients had reported confirmed LACV infections during the study period. Of these cases the majority (81 percent) presented during the summer, occurred in children 15 years and younger (83.3 percent), and were found in male children (64.9 percent). Clinically, the infections presented as meningioencephalitis (56.3 percent), encephalitis (20.7 percent), meningitis (17.2 percent), or uncomplicated fever (5 percent). Deaths occurred in 1.9 percent of confirmed cases, and in 8.6 percent of patients suffering from encephalitis. The majority of these deaths were in patients 15 years and younger. The county-level incidence risk among counties (n = 136) reporting both probable and confirmed cases for children 15 years and younger (n = 355) ranged from 0.2 to 228.7 per 100,000 persons. The southern United States experienced a significantly higher (p<0.05) incidence risk during the months of June, July, August, and October then the northern United States. There was significant (p<0.05) clustering of high risk in several geographic regions with three deaths attributed to complications from LAC encephalitis occurring in two of these hot-spots of infections.ConclusionsBoth the incidence risk and case fatality rates were found to be higher than previously reported. We detected clustering in four geographic regions, a shift from the prior geographic distributions, and developed maps identifying high-risk areas. These findings are useful for raising awareness among health care providers regarding areas at a high risk of infections and for guiding targeted multifaceted interventions by public health officials.

Hierarchical Bayesian statistics: merging experimental and modeling approaches in ecology

covariance estimation. Journal of Agricultural, Biological and Environmental Statistics 12(4)450-469. Latimer, A. M., S. Wu, A. E. Gelfand, and J. A. Silander, Jr. 2006. Building statistical models to analyze species distribu tions. Ecological Applications 16:33-50. Ritter, K., and M. Leecaster. 2007. Multi-lag cluster designs for estimating the semivariogram for sediments affected by effluent discharges offshore in San Diego. Environmental and Ecological Statistics 14:41-53. Schabenberger, O., and C. A. Gotway. 2005. Statistical methods for spatial data analysis. Chapman and Hall/CRC, Boca Raton, Florida, USA. Waller, L. A., B. J. Goodwin, M. L. Wilson, R. S. Ostfeld, S. Marshall, and E. B. Hayes. 2007. Spatio-temporal patterns in county-level incidence and reporting of Lyme disease in the northeastern United States, 1990-2000. Environmental and Ecological Statistics 14:83-100. Waller, L, and C. Gotway. 2004. Applied spatial statistics for public health data. Wiley, New York, New York, USA. Wikle, C. K. 2003. Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 84:1382-1394. Wikle, C. K., L. M. Berliner, and N. Cressie. 1998. Hierarchical Bayesian space-time models. Environmental and Ecological Statistics 5:117-154. Xia, G, M. L. Miranda, and A. E. Gelfand. 2006. Approx imately optimal spatial design approaches for environmental health data. Environmetrics 17:363-385. Zimmerman, D. L. 2006. Optimal network design for spatial prediction, covariance parameter estimation and empirical prediction. Environmetrics 17:635-652.

Monitoring county-level chlamydia incidence in Texas, 2004 - 2005: application of empirical Bayesian smoothing and Exploratory Spatial Data Analysis (ESDA) methods.

BackgroundChlamydia continues to be the most prevalent disease in the United States. Effective spatial monitoring of chlamydia incidence is important for successful implementation of control and prevention programs. The objective of this study is to apply Bayesian smoothing and exploratory spatial data analysis (ESDA) methods to monitor Texas county-level chlamydia incidence rates by examining spatiotemporal patterns. We used county-level data on chlamydia incidence (for all ages, gender and races) from the National Electronic Telecommunications System for Surveillance (NETSS) for 2004 and 2005.ResultsBayesian-smoothed chlamydia incidence rates were spatially dependent both in levels and in relative changes. Erath county had significantly (p < 0.05) higher smoothed rates (> 300 cases per 100,000 residents) than its contiguous neighbors (195 or less) in both years. Gaines county experienced the highest relative increase in smoothed rates (173% – 139 to 379). The relative change in smoothed chlamydia rates in Newton county was significantly (p < 0.05) higher than its contiguous neighbors.ConclusionBayesian smoothing and ESDA methods can assist programs in using chlamydia surveillance data to identify outliers, as well as relevant changes in chlamydia incidence in specific geographic units. Secondly, it may also indirectly help in assessing existing differences and changes in chlamydia surveillance systems over time.

Social exclusion modifies climate and deforestation impacts on a vector-borne disease.

BackgroundThe emergence of American Cutaneous Leishmaniasis (ACL) has been associated with changes in the relationship between people and forests, leading to the view that forest ecosystems increase infection risk and subsequent proposal that deforestation could reduce re-emergence of this disease.Methodology/Principal FindingsWe analyzed county-level incidence rates of ACL in Costa Rica (1996–2000) as a function of social and environmental variables relevant to transmission ecology with statistical models that incorporate breakpoints. Once social marginality was taken into account, the effect of living close to a forest on infection risk was small, and diminished exponentially above a breakpoint. Forest cover was associated with the modulation of temporal effects of El Niño Southern Oscillation (ENSO) at small spatial scales, revealing an additional complex interplay of environmental forces and disease patterns.Conclusions/SignificanceSocial factors, which previously have not been evaluated rigorously together with environmental and climatic factors, appear to play a critical role that may ultimately determine disease risk.

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

We present an exploratory analysis of reported county-specific incidence of Lyme disease in the northeastern United States for the years 1990–2000. We briefly review the disease ecology of Lyme disease and the use of risk maps to describe local incidence as estimates of local risk of disease. We place the relevant elements of local environmental and ecological variables, local disease incidence, and (importantly) local disease reporting in a conceptual context to frame our analysis. We then apply hierarchical linear models of increasing complexity to summarize observed patterns in reported incidence, borrowing information across counties to improve local precision. We find areas of increasing incidence in the central northeastern Atlantic coast counties, increasing incidence branching to the north and west, and an area of fairly stable and slightly decreasing reported incidence in western New York.

Use of Medicare claims data to measure county-level variation in breast carcinoma incidence and mammography rates

Background: National-level population-based data about breast carcinoma incidence and its association with screening mammography are currently not available. Methods: Inpatient, hospital outpatient and physician/supplier Medicare claims were used to identify incident cases of breast carcinoma in women ≥65 years from 1996 to 1997 and calculate county-level incidence rates. The 1994–1995 claims data were used to determine county-level rates of mammography, and determine the correlation with incidence. Results: The median 2-year incidence rate for women ≥65 was 979/100,000, and substantial variation in incidence between counties was observed. (i.e. 25th percentile 789/100,000, 75th percentile 1186/100,000). Two-year county-level mammography rates also varied among counties (i.e. 25th percentile 30.5%, 75th percentile 40.9%) and were higher in white women than in black women (median 36.8 and 26.3%, respectively). Counties with higher rates of mammography also had higher age-adjusted incidence rates. Conclusions: Medicare claims may provide an alternative source of population-based data, particularly for areas in which registry data are not readily available, or are of limited scope. The data highlight the geographic variation in incidence and screening rates that may be useful for targeted interventions, and also suggest that mammography remains in a growth phase.

Determination of county-level prostate carcinoma incidence and detection rates with Medicare claims data.

To the authors' knowledge, national-level population-based data regarding prostate carcinoma incidence and detection currently are not available. The availability of such data could identify those regions with a disproportionately high cancer incidence as well as the population-level association between prostate carcinoma detection and incidence. Inpatient, hospital outpatient, and physician/supplier Medicare claims from 1997 were used to identify incident cases of prostate carcinoma in men age > or = 65 years and to calculate state and county-level incidence rates. The 1991 and 1997 claims data were used to determine small area rates of prostate-specific antigen (PSA) testing and prostate biopsy and to determine their correlation with incidence. The calculated incidence rates for 1997 were 890 per 100,000 and 1196 per 100,000, respectively, in white males and African-American males and varied substantially between counties (i.e., 25--75th percentile, 676--1124 per 100,000). Rates of PSA and prostate biopsy increased markedly from 1991 to 1997 in both white men (1580 per 100,000 to 24,286 per 100,000) and African-American men (1277 per 100,000 to 15,190 per 100,000), and considerable variation in detection between counties was observed. Counties that had higher rates of prostate biopsy also had higher age-adjusted incidence rates, and county-level PSA testing was found to be associated with incidence in African-American patients, but not in white patients. Medicare claims may provide an alternative source of population-based data, particularly for areas in which registry data are not readily available or are of limited scope. In addition, claims provide otherwise unavailable national data concerning cancer detection.