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HIV and hepatitis C mortality in Massachusetts, 2002-2011: spatial cluster and trend analysis of HIV and HCV using multiple cause of death.

Meyers DJ, Hood ME, Stopka TJ - PLoS ONE (2014)

Bottom Line: The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state.Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups.We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, United States of America; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, United States of America.

ABSTRACT

Background: Infectious diseases, while associated with a much smaller proportion of deaths than they were 50 years ago, still play a significant role in mortality across the state of Massachusetts. Most analysis of infectious disease mortality in the state only take into account the underlying cause of death, rather than contributing causes of death, which may not capture the full extent of mortality trends for infectious diseases such as HIV and the Hepatitis C virus (HCV).

Methods: In this study we sought to evaluate current trends in infectious disease mortality across the state using a multiple cause of death methodology. We performed a mortality trend analysis, identified spatial clusters of disease using a 5-step geoprocessing approach and examined spatial-temporal clustering trends in infectious disease mortality in Massachusetts from 2002-2011, with a focus on HIV/AIDS and HCV.

Results: Significant clusters of high infectious disease mortality in space and time throughout the state were detected through both spatial and space time cluster analysis. The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state. Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups.

Conclusions: We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone. Our results may be used to inform public health resource allocation for infectious disease prevention and treatment programs, provide novel insight into the current state of infectious disease mortality throughout the state, and benefited from approaches that may more accurately document mortality trends.

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Related in: MedlinePlus

Statistically Significant Space-time and Spatial Trend Clusters in HCV.SatScan was used to test for spatial variation in temporal trends and for significant space-time clusters. Yellow boxes detail significant space-time clusters. Green boxes detail significant spatial variations in temporal trending. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.
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pone-0114822-g010: Statistically Significant Space-time and Spatial Trend Clusters in HCV.SatScan was used to test for spatial variation in temporal trends and for significant space-time clusters. Yellow boxes detail significant space-time clusters. Green boxes detail significant spatial variations in temporal trending. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.

Mentions: Fig. 10 portrays a map of the results of the space-time cluster analysis and the trends in spatio-temporal trends analysis. There were 11 significant space-time clusters and 2 significantly different temporal trend clusters. Within the space-time clusters, the relative risk of mortality due to HCV is given compared to locations outside of the cluster during that same time period. For example, the risk of mortality due to HCV in Cluster 1 is 2.7 times that of the state mean in that geographic area of Springfield from January 2007 to December 2011. For the spatial variation in temporal trend clusters, the percent change in mortality rates within that cluster is provided compared to the expected external trend during that time period. For example, in Trend 1, in southeastern Massachusetts (Hyannis, Cape Cod) HCV mortality increased by 403% from 2002 to 2011 while the rest of the state increased on average at a rate of 4.8% during that time period. Of note, many of these clusters aligned with the spatial hotspots conducted previously such as the cluster in Springfield and the Cluster in Worcester. This cluster in Hyannis did not appear using spatial data alone and was only present when incorporating the time element.


HIV and hepatitis C mortality in Massachusetts, 2002-2011: spatial cluster and trend analysis of HIV and HCV using multiple cause of death.

Meyers DJ, Hood ME, Stopka TJ - PLoS ONE (2014)

Statistically Significant Space-time and Spatial Trend Clusters in HCV.SatScan was used to test for spatial variation in temporal trends and for significant space-time clusters. Yellow boxes detail significant space-time clusters. Green boxes detail significant spatial variations in temporal trending. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263669&req=5

pone-0114822-g010: Statistically Significant Space-time and Spatial Trend Clusters in HCV.SatScan was used to test for spatial variation in temporal trends and for significant space-time clusters. Yellow boxes detail significant space-time clusters. Green boxes detail significant spatial variations in temporal trending. Shapefiles were provided by MassGIS, death data were provided by the Massachusetts Department of Public Health, and population estimates were provided by the US Census Bureau. NAD 1983 Massachusetts State Plain was used for projection. Maps created in ArcGIS 10.2.
Mentions: Fig. 10 portrays a map of the results of the space-time cluster analysis and the trends in spatio-temporal trends analysis. There were 11 significant space-time clusters and 2 significantly different temporal trend clusters. Within the space-time clusters, the relative risk of mortality due to HCV is given compared to locations outside of the cluster during that same time period. For example, the risk of mortality due to HCV in Cluster 1 is 2.7 times that of the state mean in that geographic area of Springfield from January 2007 to December 2011. For the spatial variation in temporal trend clusters, the percent change in mortality rates within that cluster is provided compared to the expected external trend during that time period. For example, in Trend 1, in southeastern Massachusetts (Hyannis, Cape Cod) HCV mortality increased by 403% from 2002 to 2011 while the rest of the state increased on average at a rate of 4.8% during that time period. Of note, many of these clusters aligned with the spatial hotspots conducted previously such as the cluster in Springfield and the Cluster in Worcester. This cluster in Hyannis did not appear using spatial data alone and was only present when incorporating the time element.

Bottom Line: The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state.Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups.We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, United States of America; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, United States of America.

ABSTRACT

Background: Infectious diseases, while associated with a much smaller proportion of deaths than they were 50 years ago, still play a significant role in mortality across the state of Massachusetts. Most analysis of infectious disease mortality in the state only take into account the underlying cause of death, rather than contributing causes of death, which may not capture the full extent of mortality trends for infectious diseases such as HIV and the Hepatitis C virus (HCV).

Methods: In this study we sought to evaluate current trends in infectious disease mortality across the state using a multiple cause of death methodology. We performed a mortality trend analysis, identified spatial clusters of disease using a 5-step geoprocessing approach and examined spatial-temporal clustering trends in infectious disease mortality in Massachusetts from 2002-2011, with a focus on HIV/AIDS and HCV.

Results: Significant clusters of high infectious disease mortality in space and time throughout the state were detected through both spatial and space time cluster analysis. The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state. Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups.

Conclusions: We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone. Our results may be used to inform public health resource allocation for infectious disease prevention and treatment programs, provide novel insight into the current state of infectious disease mortality throughout the state, and benefited from approaches that may more accurately document mortality trends.

Show MeSH
Related in: MedlinePlus