ON THE USE OF NON-EUCLIDEAN ISOTROPY IN GEOSTATISTICS

This paper investigates the use of non-Euclidean distances to characterize isotropic spatial dependence for geostatistical related applications. A simple example is provided to demonstrate there are no guarantees that existing covariogram and variogram functions remain valid (i.e.\ positive definite or conditionally negative definite) when used with a non-Euclidean distance measure. Furthermore, satisfying the conditions of a metric is not sufficient to ensure the distance measure can be used with existing functions. Current literature is not clear on these topics. There are certain distance measures that when used with existing covariogram and variogram functions remain valid, an issue that is explored. No new theorems are provided, rather links between existing theorems and definitions related to the concepts of isometric embedding, conditionally negative definiteness, and positive definiteness are used to demonstrate classes of valid norm dependent isotropic covariogram and variogram functions, results most of which have yet to appear in mainstream geostatistical literature or application. These classes of functions extend the well known classes by adding a parameter to define the distance norm. In practice, this distance parameter can be set a priori to represent, for example, the Euclidean distance, or kept as a parameter to allow the data to choose the distance norm. Applications of the latter are provided for demonstration

Using Imputation to Provide Location Information for Nongeocoded Addresses

Background: The importance of geography as a source of variation in health research continues to receive sustained attention in the literature. The inclusion of geographic information in such research often begins by adding data to a map which is predicated by some knowledge of location. A precise level of spatial information is conventionally achieved through geocoding, the geographic information system (GIS) process of translating mailing address information to coordinates on a map. The geocoding process is not without its limitations, though, since there is always a percentage of addresses which cannot be converted successfully (nongeocodable). This raises concerns regarding bias since traditionally the practice has been to exclude nongeocoded data records from analysis. Methodology/Principal: Findings In this manuscript we develop and evaluate a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses. The strategies are developed assuming a known zip code with increasing use of collateral information, namely the spatial distribution of the population at risk. Strategies are evaluated using prostate cancer data obtained from the Maryland Cancer Registry. We consider total case enumerations at the Census county, tract, and block group level as the outcome of interest when applying and evaluating the methods. Multiple imputation is used to provide estimated total case counts based on complete data (geocodes plus imputed nongeocodes) with a measure of uncertainty. Results indicate that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels. Conclusions/Significance: The procedure allows for the potentially biased and likely under reported outcome, case enumerations based on only the geocoded records, to be presented with a statistically adjusted count (imputed count) with a measure of uncertainty that are based on all the case data, the geocodes and imputed nongeocodes. Similar strategies can be applied in other analysis settings

Evaluation of Methicillin-Resistant Staphylococcus aureus Carriage and High Livestock Production Areas in North Carolina through Active Case Finding at a Tertiary Care Hospital

: Recent reports from the Netherlands document the emergence of novel multilocus sequence typing (MLST) types (e.g., ST-398) of methicillin-resistant Staphylococcus aureus (MRSA) in livestock, particularly swine. In Eastern North Carolina (NC), one of the densest pig farming areas in the United States, as many as 14% of MRSA isolates from active case finding in our medical center have no matches in a repetitive sequence-based polymerase chain reaction (rep-PCR) library. The current study was designed to determine if these non-matched MRSA (NM-MRSA) were geographically associated with exposure to pig farming in Eastern NC. While residential proximity to farm waste lagoons lacked association with NM-MRSA in a logistic regression model, a spatial cluster was identified in the county with highest pig density. Using MLST, we found a heterogeneous distribution of strain types comprising the NM-MRSA isolates from the most pig dense regions, including ST-5 and ST-398. Our study raises the warning that patients in Eastern NC harbor livestock associated MRSA strains are not easily identifiable by rep-PCR. Future MRSA studies in livestock dense areas in the U.S. should investigate further the role of pig–human interactions

Humidity and gravimetric equivalency adjustments for nephelometer-based particulate matter measurements of emissions from solid biomass fuel in cookstoves

Great uncertainty exists around indoor biomass burning exposure-disease relationships due to lack of detailed exposure data in large health outcome studies. Passive nephelometers can be used to estimate high particulate matter (PM) concentrations during cooking in low resource environments. Since passive nephelometers do not have a collection filter they are not subject to sampler overload. Nephelometric concentration readings can be biased due to particle growth in high humid environments and differences in compositional and size dependent aerosol characteristics. This paper explores relative humidity (RH) and gravimetric equivalency adjustment approaches to be used for the pDR-1000 used to assess indoor PM concentrations for a cookstove intervention trial in Nepal. Three approaches to humidity adjustment performed equivalently (similar root mean squared error). For gravimetric conversion, the new linear regression equation with log-transformed variables performed better than the traditional linear equation. In addition, gravimetric conversion equations utilizing a spline or quadratic term were examined. We propose a humidity adjustment equation encompassing the entire RH range instead of adjusting for RH above an arbitrary 60% threshold. Furthermore, we propose new integrated RH and gravimetric conversion methods because they have one response variable (gravimetric PM2.5 concentration), do not contain an RH threshold, and is straightforward

FINE PARTICULATE AIR POLLUTION AND MORTALITY IN 20 U.S. CITIES, 1987â 1994

BACKGROUND: Air pollution in cities has been linked to increased rates of mortality and morbidity in developed and developing countries. Although these findings have helped lead to a tightening of air-quality standards, their validity with respect to public health has been questioned. METHODS: We assessed the effects of five major outdoor-air pollutants on daily mortality rates in 20 of the largest cities and metropolitan areas in the United States from 1987 to 1994. The pollutants were particulate matter that is less than 10 microm in aerodynamic diameter (PM10), ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide. We used a two-stage analytic approach that pooled data from multiple locations. RESULTS: After taking into account potential confounding by other pollutants, we found consistent evidence that the level of PM10 is associated with the rate of death from all causes and from cardiovascular and respiratory illnesses. The estimated increase in the relative rate of death from all causes was 0.51 percent (95 percent posterior interval, 0.07 to 0.93 percent) for each increase in the PM10 level of 10 microg per cubic meter. The estimated increase in the relative rate of death from cardiovascular and respiratory causes was 0.68 percent (95 percent posterior interval, 0.20 to 1.16 percent) for each increase in the PM10 level of 10 microg per cubic meter. There was weaker evidence that increases in ozone levels increased the relative rates of death during the summer, when ozone levels are highest, but not during the winter. Levels of the other pollutants were not significantly related to the mortality rate. CONCLUSIONS: There is consistent evidence that the levels of fine particulate matter in the air are associated with the risk of death from all causes and from cardiovascular and respiratory illnesses. These findings strengthen the rationale for controlling the levels of respirable particles in outdoor air

Livestock density as risk factor for livestock-associated methicillin-resistant Staphylococcus aureus, the Netherlands

To determine whether persons living in areas of high animal density are at increased risk for carrying livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA), we used an existing dataset of persons in the Netherlands with LA-MRSA carriage and controls who carried other types of MRSA. Results of running univariate and multivariate logistic regression models indicated that living in livestock-dense areas increases the odds of nasal carriage of LA-MRSA. We found that doubling pig, cattle, and veal calf densities per municipality increased the odds of LA-MRSA carriage over carriage of other types of MRSA by 24.7% (95% CI 0.9%–54.2%), 76.9% (95% CI 11.3%–81.3%), and 24.1% (95% CI 5.5%–45.9%), respectively, after adjusting for direct animal contact, living in a rural area, and the probable source of MRSA carriage. Controlling the spread of LA-MRSA thus requires giving attention to community members in animal-dense regions who are unaffiliated with livestock farming

Geographic Variations in Retention in Care among HIV-Infected Adults in the United States

ObjectiveTo understand geographic variations in clinical retention, a central component of the HIV care continuum and key to improving individual- and population-level HIV outcomes.DesignWe evaluated retention by US region in a retrospective observational study.MethodsAdults receiving care from 2000–2010 in 12 clinical cohorts of the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) contributed data. Individuals were assigned to Centers for Disease Control and Prevention (CDC)-defined regions by residential data (10 cohorts) and clinic location as proxy (2 cohorts). Retention was ≥2 primary HIV outpatient visits within a calendar year, >90 days apart. Trends and regional differences were analyzed using modified Poisson regression with clustering, adjusting for time in care, age, sex, race/ethnicity, and HIV risk, and stratified by baseline CD4+ count.ResultsAmong 78,993 adults with 444,212 person-years of follow-up, median time in care was 7 years (Interquartile Range: 4–9). Retention increased from 2000 to 2010: from 73% (5,000/6,875) to 85% (7,189/8,462) in the Northeast, 75% (1,778/2,356) to 87% (1,630/1,880) in the Midwest, 68% (8,451/12,417) to 80% (9,892/12,304) in the South, and 68% (5,147/7,520) to 72% (6,401/8,895) in the West. In adjusted analyses, retention improved over time in all regions (p<0.01, trend), although the average percent retained lagged in the West and South vs. the Northeast (p<0.01).ConclusionsIn our population, retention improved, though regional differences persisted even after adjusting for demographic and HIV risk factors. These data demonstrate regional differences in the US which may affect patient care, despite national care recommendations

Combining Free Text and Structured Electronic Medical Record Entries to Detect Acute Respiratory Infections

The electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).A manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis.An adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.Structured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties