Dataset Information

Spatial clustering of myelodysplastic syndromes (MDS) in the Seattle-Puget Sound region of Washington State.

ABSTRACT: Incidence of myelodysplastic syndromes (MDS) has been described in the United States since its inclusion in the Surveillance, Epidemiology, and End Results program in 2001, and the Seattle-Puget Sound region of Washington State has among the highest rates of the registries. In this investigation, we described small-scale incidence patterns of MDS within the Seattle-Puget Sound region from 2002 to 2006 and identified potential spatial clusters to inform planning of future studies of MDS etiology.We used a spatial disease mapping model to estimate smoothed relative risks for each census tract and to describe the spatial component of variability in the incidence rates. We also used two methods to describe the location of potential MDS clusters: the approach of Besag and Newell and the Kulldorff spatial scan statistic.Our findings from all three approaches indicated the most likely areas of increased MDS incidence were located on Whidbey Island in Island County.Interpretation is limited because our data are based on the residential location of the MDS case only at the time of diagnosis. Nevertheless, inclusion of identified cluster regions in future population-based research and investigation of individual-level exposures could shed light on environmental risk factors for MDS.

SUBMITTER: Ross ME

PROVIDER: S-EPMC3196606 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Spatial clustering of myelodysplastic syndromes (MDS) in the Seattle-Puget Sound region of Washington State.

Ross Michelle E ME Wakefield Jon J Davis Scott S De Roos Anneclaire J AJ

Cancer causes & control : CCC 20100126 6

<h4>Objectives</h4>Incidence of myelodysplastic syndromes (MDS) has been described in the United States since its inclusion in the Surveillance, Epidemiology, and End Results program in 2001, and the Seattle-Puget Sound region of Washington State has among the highest rates of the registries. In this investigation, we described small-scale incidence patterns of MDS within the Seattle-Puget Sound region from 2002 to 2006 and identified potential spatial clusters to inform planning of future studi ...[more]

PMID: 20101455

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Project description:BackgroundRural U.S. communities are at risk from COVID-19 due to advanced age and limited access to acute care. Recognizing this, the Vashon Medical Reserve Corps (VMRC) in King County, Washington, implemented an all-volunteer, community-based COVID-19 response program. This program integrated public engagement, SARS-CoV-2 testing, contact tracing, vaccination, and material community support, and was associated with the lowest cumulative COVID-19 case rate in King County. This study aimed to investigate the contributions of demographics, geography and public health interventions to Vashon's low COVID-19 rates.MethodsThis observational cross-sectional study compares cumulative COVID-19 rates and success of public health interventions from February 2020 through November 2021 for Vashon Island with King County (including metropolitan Seattle) and Whidbey Island, located ~50 km north of Vashon. To evaluate the role of demography, we developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across 77 King County zip codes. To investigate the role of remote geography we expanded the regression models to include North, Central and South Whidbey, similarly remote island communities with varying demographic features. To evaluate the effectiveness of VMRC's community-based public health measures, we directly compared Vashon's success of vaccination and contact tracing with that of King County and South Whidbey, the Whidbey community most similar to Vashon.ResultsVashon's cumulative COVID-19 case rate was 29% that of King County overall (22.2 vs 76.8 cases/K). A multiple linear regression model based on King County demographics found educational attainment to be a major correlate of COVID-19 rates, and Vashon's cumulative case rate was just 38% of predicted (p < .05), so demographics alone do not explain Vashon's low COVID-19 case rate. Inclusion of Whidbey communities in the model identified a major effect of remote geography (-49 cases/K, p < .001), such that observed COVID-19 rates for all remote communities fell within the model's 95% prediction interval. VMRC's vaccination effort was highly effective, reaching a vaccination rate of 1500 doses/K four months before South Whidbey and King County and maintaining a cumulative vaccination rate 200 doses/K higher throughout the latter half of 2021 (p < .001). Including vaccination rates in the model reduced the effect of remote geography to -41 cases/K (p < .001). VMRC case investigation was also highly effective, interviewing 96% of referred cases in an average of 1.7 days compared with 69% in 3.7 days for Washington Department of Health investigating South Whidbey cases and 80% in 3.4 days for Public Health-Seattle & King County (both p<0.001). VMRC's public health interventions were associated with a 30% lower case rate (p<0.001) and 55% lower hospitalization rate (p = 0.056) than South Whidbey.ConclusionsWhile the overall magnitude of the pre-Omicron COVID-19 pandemic in rural and urban U.S. communities was similar, we show that island communities in the Puget Sound region were substantially protected from COVID-19 by their geography. We further show that a volunteer community-based COVID-19 response program was highly effective in the Vashon community, augmenting the protective effect of geography. We suggest that Medical Reserve Corps should be an important element of future pandemic planning.

Dataset Information

Spatial clustering of myelodysplastic syndromes (MDS) in the Seattle-Puget Sound region of Washington State.

Publications

Spatial clustering of myelodysplastic syndromes (MDS) in the Seattle-Puget Sound region of Washington State.

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