Last data update: Jun 17, 2024. (Total: 47034 publications since 2009)
Records 1-20 (of 20 Records) |
Query Trace: Wilt G [original query] |
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County-level social vulnerability and nonfatal drug overdose emergency department visits and hospitalizations, January 2018-December 2020
Stokes EK , Pickens CM , Wilt G , Liu S , David F . Drug Alcohol Depend 2023 247 109889 BACKGROUND: Nonfatal drug overdoses (NFODs) are often attributed to individual behaviors and risk factors; however, identifying community-level social determinants of health (SDOH) associated with increased NFOD rates may allow public health and clinical providers to develop more targeted interventions to address substance use and overdose health disparities. CDC's Social Vulnerability Index (SVI), which aggregates social vulnerability data from the American Community Survey to produce ranked county-level vulnerability scores, can help identify community factors associated with NFOD rates. This study aims to describe associations between county-level social vulnerability, urbanicity, and NFOD rates. METHODS: We analyzed county-level 2018-2020 emergency department (ED) and hospitalization discharge data submitted to CDC's Drug Overdose Surveillance and Epidemiology system. Counties were ranked in vulnerability quartiles based on SVI data. We used crude and adjusted negative binomial regression models, by drug category, to calculate rate ratios and 95% confidence intervals comparing NFOD rates by vulnerability. RESULTS: Generally, as social vulnerability scores increased, ED and hospitalization NFOD rates increased; however, the magnitude of the association varied across drugs, visit type, and urbanicity. SVI-related theme and individual variable analyses highlighted specific community characteristics associated with NFOD rates. CONCLUSIONS: The SVI can help identify associations between social vulnerabilities and NFOD rates. Development of an overdose-specific validated index could improve translation of findings to public health action. The development and implementation of overdose prevention strategies should consider a socioecological perspective and address health inequities and structural barriers associated with increased risk of NFODs at all levels of the social ecology. |
Association between passively collected walking and bicycling data and purposefully collected active commuting survey data-United States, 2019
Soto GW , Webber BJ , Fletcher K , Chen TJ , Garber MD , Smith A , Wilt G , Conn M , Whitfield GP . Health Place 2023 81 103002 Commercially-available location-based services (LBS) data derived primarily from mobile devices may provide an alternative to surveys for monitoring physically-active transportation. Using Spearman correlation, we compared county-level metrics of walking and bicycling from StreetLight with metrics of physically-active commuting among U.S. workers from the American Community Survey. Our strongest pair of metrics ranked counties (n = 298) similarly for walking (rho = 0.53 [95% CI: 0.44-0.61]) and bicycling (rho = 0.61 [0.53-0.67]). Correlations were higher for denser and more urban counties. LBS data may offer public health and transportation professionals timely information on walking and bicycling behavior at finer geographic scales than some existing surveys. |
Social Vulnerability and County Stay-At-Home Behavior During COVID-19 Stay-At-Home Orders, United States, April 7-April 20, 2020.
Fletcher KM , Espey J , Grossman M , Sharpe JD , Curriero FC , Wilt GE , Sunshine G , Moreland A , Howard-Williams M , Ramos JG , Giuffrida D , García MC , Harnett WM , Foster S . Ann Epidemiol 2021 64 76-82 PURPOSE: Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. METHODS: Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7 to April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index. RESULTS: Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. CONCLUSIONS: Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and responses to future outbreaks. |
Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February-June 2020, Massachusetts.
Troppy S , Wilt GE , Whiteman A , Hallisey E , Crockett M , Sharpe JD , Haney G , Cranston K , Klevens RM . Public Health Rep 2021 136 (6) 765-773 OBJECTIVES: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. METHODS: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. RESULTS: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. CONCLUSION: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels. |
Social Vulnerability and Access of Local Medical Care During Hurricane Harvey: A Spatial Analysis
Rickless DS , Wilt GE , Sharpe JD , Molinari N , Stephens W , LeBlanc TT . Disaster Med Public Health Prep 2021 17 1-9 OBJECTIVES: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. METHODS: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. RESULTS: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. CONCLUSIONS: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status. |
Screening for colorectal cancer in asymptomatic average-risk adults
Wilt TJ , Crandall CJ , Hicks LA , Mustafa RA , Qaseem A . Ann Intern Med 2020 172 (7) 508-509 American College of Physicians guidance statements are intended to provide critical review and appraisal of guidelines and evidence presented to support the recommendations when several conflicting guidelines exist on a clinical topic (1, 2). We acknowledge Dr. Kim's point that there are observational data on CTC; however, the U.S. Preventive Services Task Force notes that the evidence is limited to test characteristics studies with no data on clinical effectiveness and insufficient evidence on harms, including unnecessary testing and treatment due to incidental extracolonic findings that are common with this test (3). Positive findings on CTC require colonoscopy follow-up, thus reducing the advantage of this direct visualization test. |
Shigella sonnei Outbreak Investigation During a Municipal Water Crisis-Genesee and Saginaw Counties, Michigan, 2016.
McClung RP , Karwowski M , Castillo C , McFadden J , Collier S , Collins J , Soehnlen M , Dietrich S , Trees E , Wilt G , Harrington C , Miller A , Adam E , Reses H , Cope J , Fullerton K , Hill V , Yoder J . Am J Public Health 2020 110 (6) e1-e8 ![]() ![]() Objectives. To investigate a shigellosis outbreak in Genesee County, Michigan (including the City of Flint), and Saginaw County, Michigan, in 2016 and address community concerns about the role of the Flint water system.Methods. We met frequently with community members to understand concerns and develop the investigation. We surveyed households affected by the outbreak, analyzed Shigella isolate data, examined the geospatial distribution of cases, and reviewed available water quality data.Results. We surveyed 83 households containing 158 cases; median age was 10 years. Index case-patients from 55 of 83 households (66%) reported contact with a person outside their household who wore diapers or who had diarrhea in the week before becoming ill; results were similar regardless of household drinking water source. Genomic diversity was not consistent with a point source. In Flint, no space-time clustering was identified, and average free chlorine residual values remained above recommended levels throughout the outbreak period.Conclusions. The outbreak was most likely caused by person-to-person contact and not by the Flint water system. Consistent community engagement was essential to the design and implementation of the investigation. (Am J Public Health. Published online ahead of print April 16, 2020: e1-e8. doi:10.2105/AJPH.2020.305577). |
Spatial exploration of the CDC's Social Vulnerability Index and heat-related health outcomes in Georgia
Lehnert EA , Wilt G , Flanagan B , Hallisey E . Int J Disaster Risk Reduct 2020 46 Heat-related illness, an environmental exposure-related outcome commonly treated in U.S. hospital emergency departments (ED), is likely to rise with increased incidence of heat events related to climate change. Few studies demonstrate the spatial and statistical relationship of social vulnerability and heat-related health outcomes. We explore relationships of Georgia county-level heat-related ED visits and mortality rates (2002–2008), with CDC's Social Vulnerability Index (CDC SVI). Bivariate Moran's I analysis revealed significant clustering of high SVI rank and high heat-related ED visit rates (0.211, p < 0.001) and high smoothed mortality rates (0.210, p < 0.001). Regression revealed that for each 10% increase in SVI ranking, ED visit rates significantly increased by a factor of 1.18 (95% CI = 1.17–1.19), and mortality rates significantly increased by a factor of 1.31 (95% CI = 1.16–1.47). CDC SVI values are spatially linked and significantly associated with heat-related ED visit, and mortality rates in Georgia. |
Sociodemographic disparities in access to ovarian cancer treatment
Graham S , Hallisey E , Wilt G , Flanagan B , Rodriguez JL , Peipins L . Ann Cancer Epidemiol 2019 3 Background: Ovarian cancer is the fifth most common cause of cancer death among women in the United States. Failure to receive optimal treatment and poorer survival rates have been reported for older women, African-American women, women with low income, and women with public health insurance coverage or no coverage. Additionally, regional differences in geographic access influence the type of treatment women may seek. This paper explores geographic accessibility and sociodemographic vulnerability in Georgia, which influence receipt of optimal ovarian cancer treatment. Methods: An enhanced two-step floating catchment area (E2SFCA), defining physical access, was created for each census tract and gynecologic oncologist clinic. Secondly, sociodemographic variables reflecting potential social vulnerability were selected from U.S. Census and American Community Survey data at the tract level. These two measures were combined to create a measure of Geosocial Vulnerability. This framework was tested using Georgia ovarian cancer mortality records. Results: Geospatial access was higher in urban areas with less accessibility in suburban and rural areas. Sociodemographic vulnerability varied geospatially, with higher vulnerability in urban citers and rural areas. Sociodemographic measures were combined with geospatial access to create a Geosocial Vulnerability Indicator, which showed a significant positive association with ovarian cancer mortality. Conclusions: Spatial and sociodemographic measures pinpointed areas of healthcare access vulnerability not revealed by either spatial analysis or sociodemographic assessment alone. Whereas lower healthcare accessibility in rural areas has been well described, our analysis shows considerable heterogeneity in access to care in urban areas where the disadvantaged census tracts can be easily identified. |
A spatial and temporal investigation of medical surge in Dallas-Fort Worth during Hurricane Harvey, Texas 2017
Stephens W , Wilt GE , Lehnert EA , Molinari NM , LeBlanc TT . Disaster Med Public Health Prep 2020 14 (1) 1-8 OBJECTIVE: When 2017 Hurricane Harvey struck the coastline of Texas on August 25, 2017, it resulted in 88 fatalities and more than US $125 billion in damage to infrastructure. The floods associated with the storm created a toxic mix of chemicals, sewage and other biohazards, and over 6 million cubic meters of garbage in Houston alone. The level of biohazard exposure and injuries from trauma among persons residing in affected areas was widespread and likely contributed to increases in emergency department (ED) visits in Houston and cities receiving hurricane evacuees. We investigated medical surge resulting from these evacuations in Dallas-Fort Worth (DFW) metroplex EDs. METHODS: We used data sourced from the North Texas Syndromic Surveillance Region 2/3 in ESSENCE to investigate ED visit surge following the storm in DFW hospitals because this area received evacuees from the 60 counties with disaster declarations due to the storm. We used the interrupted time series (ITS) analysis to estimate the magnitude and duration of the ED surge. ITS was applied to all ED visits in DFW and visits made by patients residing in any of the 60 counties with disaster declarations due to the storm. The DFW metropolitan statistical area included 55 hospitals. Time series analyses examined data from March 1, 2017-January 6, 2018 with focus on the storm impact period, August 14-September 15, 2017. Data from before, during, and after the storm were visualized spatially and temporally to characterize magnitude, duration, and spatial variation of medical surge attributable to Hurricane Harvey. RESULTS: During the study period overall, ED visits in the DFW area rose immediately by about 11% (95% CI: 9%, 13%), amounting to ~16 500 excess total visits before returning to the baseline on September 21, 2017. Visits by patients identified as residing in disaster declaration counties to DFW hospitals rose immediately by 127% (95% CI: 125%, 129%), amounting to 654 excess visits by September 29, 2017, when visits returned to the baseline. A spatial analysis revealed that evacuated patients were strongly clustered (Moran's I = 0.35, P < 0.0001) among 5 of the counties with disaster declarations in the 11-day window during the storm surge. CONCLUSIONS: The observed increase in ED visits in DFW due to Hurricane Harvey and ensuing evacuation was significant. Anticipating medical surge following large-scale hurricanes is critical for community preparedness planning. Coordinated planning across stakeholders is necessary to safeguard the population and for a skillful response to medical surge needs. Plans that address hurricane response, in particular, should have contingencies for support beyond the expected disaster areas. |
Screening for colorectal cancer in asymptomatic average-risk adults: A guidance statement from the American College of Physicians
Qaseem A , Crandall CJ , Mustafa RA , Hicks LA , Wilt TJ . Ann Intern Med 2019 171 (9) 643-654 Description: The purpose of this guidance statement is to guide clinicians on colorectal cancer screening in average-risk adults. Methods: This guidance statement is derived from a critical appraisal of guidelines on screening for colorectal cancer in average-risk adults and the evidence presented in these guidelines. National guidelines published in English between 1 June 2014 and 28 May 2018 in the National Guideline Clearinghouse or Guidelines International Network library were included. The authors also included 3 guidelines commonly used in clinical practice. Web sites were searched for guideline updates in December 2018. The AGREE II (Appraisal of Guidelines for Research and Evaluation II) instrument was used to evaluate the quality of guidelines. Target Audience and Patient Population: The target audience is all clinicians, and the target patient population is adults at average risk for colorectal cancer. Guidance Statement 1: Clinicians should screen for colorectal cancer in average-risk adults between the ages of 50 and 75 years. Guidance Statement 2: Clinicians should select the colorectal cancer screening test with the patient on the basis of a discussion of benefits, harms, costs, availability, frequency, and patient preferences. Suggested screening tests and intervals are fecal immunochemical testing or high-sensitivity guaiac-based fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus fecal immunochemical testing every 2 years. Guidance Statement 3: Clinicians should discontinue screening for colorectal cancer in average-risk adults older than 75 years or in adults with a life expectancy of 10 years or less. |
A spatial exploration of changes in drug overdose mortality in the United States, 2000-2016
Wilt GE , Lewis BE , Adams EE . Prev Chronic Dis 2019 16 E33 From 2000 to 2014, rates of drug overdose mortality increased by 137% in the United States. By 2014, 61% of these mortalities were due to opioid overdoses, which have tripled since 2000 (1). Within the last decade, increased amounts of fentanyl in drugs, as well as changes in prescription drug use, have drastically affected the geography of this epidemic. Additionally, the rise in heroin overdoses in recent years has shifted the epidemic into cities (2). The Pew Charitable Trusts reported that in 2015, 38% of all renter households were rent burdened (ie, spending 30% or more of pretax income on rent), a 19% increase since 2001, highlighting the increase of economic immobility in America (3). As overdose mortality rates increased, county-level economic distress worsened (2). Examining this shift in overdose mortalities and their potential drivers through a spatial lens can identify at-risk counties. |
The impact of Hurricane Sandy on HIV testing rates: An interrupted time series analysis, January 1, 2011 - December 31, 2013
Ekperi LI , Thomas E , LeBlanc TT , Adams EE , Wilt GE , Molinari NA , Carbone EG . PLoS Curr 2018 10 BACKGROUND: Hurricane Sandy made landfall on the eastern coast of the United States on October 29, 2012 resulting in 117 deaths and 71.4 billion dollars in damage. Persons with undiagnosed HIV infection might experience delays in diagnosis testing, status confirmation, or access to care due to service disruption in storm-affected areas. The objective of this study is to describe the impact of Hurricane Sandy on HIV testing rates in affected areas and estimate the magnitude and duration of disruption in HIV testing associated with storm damage intensity. METHODS: Using MarketScan data from January 2011December 2013, this study examined weekly time series of HIV testing rates among privately insured enrollees not previously diagnosed with HIV; 95 weeks pre- and 58 weeks post-storm. Interrupted time series (ITS) analyses were estimated by storm impact rank (using FEMA's Final Impact Rank mapped to Core Based Statistical Areas) to determine the extent that Hurricane Sandy affected weekly rates of HIV testing immediately and the duration of that effect after the storm. RESULTS: HIV testing rates declined significantly across storm impact rank areas. The mean decline in rates detected ranged between -5% (95% CI: -9.3, -1.5) in low impact areas and -24% (95% CI: -28.5, -18.9) in very high impact areas. We estimated at least 9,736 (95% CI: 7,540, 11,925) testing opportunities were missed among privately insured persons following Hurricane Sandy. Testing rates returned to baseline in low impact areas by 6 weeks post event (December 9, 2012); by 15 weeks post event (February 10, 2013) in moderate impact areas; and by 17 weeks after the event (February 24, 2013) in high and very high impact areas. CONCLUSIONS: Hurricane Sandy resulted in a detectable and immediate decline in HIV testing rates across storm-affected areas. Greater storm damage was associated with greater magnitude and duration of testing disruption. Disruption of basic health services, like HIV testing and treatment, following large natural and man-made disasters is a public health concern. Disruption in testing services availability for any length of time is detrimental to the efforts of the current HIV prevention model, where status confirmation is essential to control disease spread. |
Vulnerabilities associated with post-disaster declines in HIV-testing: Decomposing the impact of Hurricane Sandy
Thomas E , Ekperi L , LeBlanc TT , Adams EE , Wilt GE , Molinari NA , Carbone EG . PLoS Curr 2018 10 Introduction: Using Interrupted Time Series Analysis and generalized estimating equations, this study identifies factors that influence the size and significance of Hurricane Sandy's estimated impact on HIV testing in 90 core-based statistical areas from January 1, 2011 to December 31, 2013. Methods: Generalized estimating equations were used to examine the effects of sociodemographic and storm-related variables on relative change in HIV testing resulting from Interrupted Time Series analyses. Results: There is a significant negative relationship between HIV prevalence and the relative change in testing at all time periods. A one unit increase in HIV prevalence corresponds to a 35% decrease in relative testing the week of the storm and a 14% decrease in relative testing at week twelve. Building loss was also negatively associated with relative change for all time points. For example, a one unit increase in building loss at week 0 corresponds with an 8% decrease in the relative change in testing (p=0.0001) and a 2% at week twelve (p=0.001). Discussion: Our results demonstrate that HIV testing can be negatively affected during public health emergencies. Communities with high percentages of building loss and significant HIV disease burden should prioritize resumption of testing to support HIV prevention. |
A space time analysis evaluating the impact of Hurricane Sandy on HIV testing rates
Wilt GE , Adams EE , Thomas E , Ekperi L , LeBlanc TT , Dunn I , Molinari NA , Carbone EG . Int J Disaster Risk Reduct 2018 28 839-844 Spatial proximity to infrastructural damage from natural disasters may pose a threat to established HIV testing services and contribute to delays in knowledge of one's disease status. Physical vulnerabilities such as spatial proximity to a level 4 FEMA impact zone, are defined in this study as natural and infrastructural barriers that can impede access to care. We analyzed the storm effects and community characteristics that contributed to the changes in HIV testing rates post Hurricane Sandy. Univariate and bivariate Moran's I tests were conducted to test for spatial autocorrelation. Combined spatial lag and error models accounted for lagged effects and alternatives in error distribution. Bivariate local Moran's I identified many significant clusters of more extreme negative relative change in HIV testing rates in areas with high FEMA impact ranks. Spatial lag and error models highlighted a significant relationship between CBSAs closer to a level 4 FEMA impact zone and the increased effect of Hurricane Sandy on HIV testing. Additionally, as the number of habitable buildings increased, there was significantly less change in HIV testing rates. Physical vulnerability had a significant effect on HIV testing rates. However all findings became less significant over time, highlighting the recovery process. Factors including: increased communication concerning preventative measures prior to the disaster, a prompt response to mitigate infrastructural damage and resumption of HIV testing services, are essential at the government and community levels to mitigate infection risk. |
A spatial analysis of amyotrophic lateral sclerosis (ALS) cases in the United States and their proximity to multidisciplinary ALS clinics, 2013
Horton DK , Graham S , Punjani R , Wilt G , Kaye W , Maginnis K , Webb L , Richman J , Bedlack R , Tessaro E , Mehta P . Amyotroph Lateral Scler Frontotemporal Degener 2017 19 1-8 BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease that typically results in death within 2-5 years of initial symptom onset. Multidisciplinary ALS clinics (MDCs) have been established to provide specialty care to people living with the disease. OBJECTIVE: To estimate the proximity of ALS prevalence cases to the nearest MDC in the US to help evaluate one aspect of access to care. METHODS: Using 2013 prevalence data from the National ALS Registry, cases were geocoded by city using geographic information system (GIS) software, along with the locations of all MDCs in operation during 2013. Case-to-MDC proximity was calculated and analyzed by sex, race, and age group. RESULTS: During 2013, there were 72 MDCs in operation in 30 different states. A total of 15,633 ALS cases were geocoded and were distributed throughout all 50 states. Of these, 62.6% were male, 77.9% were white, and 76.2% were 50-79 years old. For overall case-to-MDC proximity, nearly half (44.9%) of all geocoded cases in the US lived >50 miles from an MDC, including approximately a quarter who lived >100 miles from an MDC. There was a statistically significant difference between distance to MDC by race and age group. CONCLUSIONS: The high percentage of those living more than 50 miles from the nearest specialized clinic underscores one of the many challenges of ALS. Having better access to care, whether at MDCs or through other modalities, is likely key to increasing survivability and obtaining appropriate end-of-life treatment and support for people with ALS. |
Geographic access to cancer care and mortality among adolescents
Tai E , Hallisey E , Peipins LA , Flanagan B , Buchanan Lunsford N , Wilt G , Graham S . J Adolesc Young Adult Oncol 2017 7 (1) 22-29 PURPOSE: Adolescents with cancer have had less improvement in survival than other populations in the United States. This may be due, in part, to adolescents not receiving treatment at Children's Oncology Group (COG) institutions, which have been shown to increase survival for some cancers. The objective of this ecologic study was to examine geographic distance to COG institutions and adolescent cancer mortality. METHODS: We calculated cancer mortality among adolescents and sociodemographic and healthcare access factors in four geographic zones at selected distances surrounding COG facilities: Zone A (area within 10 miles of any COG institution), Zones B and C (concentric rings with distances from a COG institution of >10-25 miles and >25-50 miles, respectively), and Zone D (area outside of 50 miles). RESULTS: The adolescent cancer death rate was highest in Zone A at 3.21 deaths/100,000, followed by Zone B at 3.05 deaths/100,000, Zone C at 2.94 deaths/100,000, and Zone D at 2.88 deaths/100,000. The United States-wide death rate for whites without Hispanic ethnicity, blacks without Hispanic ethnicity, and persons with Hispanic ethnicity was 2.96 deaths/100,000, 3.10 deaths/100,000, and 3.26 deaths/100,000, respectively. Zone A had high levels of poverty (15%), no health insurance coverage (16%), and no vehicle access (16%). CONCLUSIONS: Geographic access to COG institutions, as measured by distance alone, played no evident role in death rate differences across zones. Among adolescents, socioeconomic factors, such as poverty and health insurance coverage, may have a greater impact on cancer mortality than geographic distance to COG institution. |
Geospatial analysis of household spread of Ebola virus in a quarantined village - Sierra Leone, 2014
Gleason BL , Foster S , Wilt GE , Miles B , Lewis B , Cauthen K , King M , Bayor F , Conteh S , Sesay T , Kamara SI , Lambert G , Finley P , Beyeler W , Moore T , Gaudioso J , Kilmarx PH , Redd JT . Epidemiol Infect 2017 145 (14) 1-9 We performed a spatial-temporal analysis to assess household risk factors for Ebola virus disease (Ebola) in a remote, severely-affected village. We defined a household as a family's shared living space and a case-household as a household with at least one resident who became a suspect, probable, or confirmed Ebola case from 1 August 2014 to 10 October 2014. We used Geographic Information System (GIS) software to calculate inter-household distances, performed space-time cluster analyses, and developed Generalized Estimating Equations (GEE). Village X consisted of 64 households; 42% of households became case-households over the observation period. Two significant space-time clusters occurred among households in the village; temporal effects outweighed spatial effects. GEE demonstrated that the odds of becoming a case-household increased by 4.0% for each additional person per household (P < 0.02) and 2.6% per day (P < 0.07). An increasing number of persons per household, and to a lesser extent, the passage of time after onset of the outbreak were risk factors for household Ebola acquisition, emphasizing the importance of prompt public health interventions that prioritize the most populated households. Using GIS with GEE can reveal complex spatial-temporal risk factors, which can inform prioritization of response activities in future outbreaks. |
Transforming geographic scale: A comparison of combined population and areal weighting to other interpolation methods
Hallisey E , Tai E , Berens A , Wilt G , Peipins L , Lewis B , Graham S , Flanagan B , Lunsford NB . Int J Health Geogr 2017 16 (1) 29 BACKGROUND: Transforming spatial data from one scale to another is a challenge in geographic analysis. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the United States, we examined methods to estimate mortality within zones at varying distances from these facilities: (1) geographic centroid assignment, (2) population-weighted centroid assignment, (3) simple areal weighting, (4) combined population and areal weighting, and (5) geostatistical areal interpolation. For the primary study, we used county mortality counts from the National Center for Health Statistics (NCHS) and population data by census tract for the United States to estimate zone mortality. In this paper, to evaluate the five mortality estimation methods, we employed address-level mortality data from the state of Georgia in conjunction with census data. Our objective here is to identify the simplest method that returns accurate mortality estimates. RESULTS: The distribution of Georgia county adolescent cancer mortality counts mirrors the Poisson distribution of the NCHS counts for the U.S. Likewise, zone value patterns, along with the error measures of hierarchy and fit, are similar for the state and the nation. Therefore, Georgia data are suitable for methods testing. The mean absolute value arithmetic differences between the observed counts for Georgia and the five methods were 5.50, 5.00, 4.17, 2.74, and 3.43, respectively. Comparing the methods through paired t-tests of absolute value arithmetic differences showed no statistical difference among the methods. However, we found a strong positive correlation (r = 0.63) between estimated Georgia mortality rates and combined weighting rates at zone level. Most importantly, Bland-Altman plots indicated acceptable agreement between paired arithmetic differences of Georgia rates and combined population and areal weighting rates. CONCLUSIONS: This research contributes to the literature on areal interpolation, demonstrating that combined population and areal weighting, compared to other tested methods, returns the most accurate estimates of mortality in transforming small counts by county to aggregated counts for large, non-standard study zones. This conceptually simple cartographic method should be of interest to public health practitioners and researchers limited to analysis of data for relatively large enumeration units. |
Impact of a participatory analysis of a campus sustainability social network: A case study of Emory University
Chuvileva IM , Reef L , Wilt GE , Shriber J , Aleman M , Smith B . Sustainability 2017 10 (3) 193-203 Social network analysis makes visible the invisible connections and flows that underlie complex social relationships. Applied organizational researchers have used social network analysis to assess and improve organizational and leadership effectiveness by helping organizations design interventions to overcome siloing, enhance collaboration and productivity, and implement strategic innovations. Some analysts of sustainability in higher education have explicitly called for a similar use of social network analysis to enhance sustainability progress on campuses. Addressing this call and literature gap, this article details the purpose, process, and results of the Mapping Emory's Sustainability Social Network project at Emory University (Atlanta, Georgia). The project had three major components: 1.) researching and creating visual maps of the university's sustainability collaboration networks, 2.) engaging key stakeholders and the wider campus sustainability community in participatory analysis of the results, and 3.) evaluating the effectiveness of this information for community members in deepening their own sustainability thinking and practice. The project demonstrates the power of social network analysis as a critical tool to engage and mobilize staff, faculty, and students in sustainability on campus by supporting evidence-based, strategic decision making among community leaders. |
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