Assessing land use and land cover change in coastal urban wetlands of international importance in Ghana using Intensity Analysis

Wetlands Ecology and Management - In the era of global environmental change, land transformation is acknowledged as a critical subject that needs to be addressed. Even though some studies have been...     

Persistence of extended-spectrum β-lactamase plasmids among Enterobacteriaceae in commercial broiler farms

To clarify the persistence of extended-spectrum β-lactamase (ESBL) producers, 13 plasmids from two broiler farms were analyzed. On the farm not using antimicrobials, one plasmid from Klebsiella pneumoniae isolated from a day-old chick was similar to that from Escherichia coli isolated a year later, with the deletion of two transposons. On the farm using antimicrobials, most circulating plasmids (eight out of nine) in a flock of 40-days-old chicks were identical, although one from K. pneumoniae had a deletion of a transposon carrying a class 1 integron containing aadA2 and dfrA12. Thus, ESBL plasmids persisted in the farms with or without antimicrobial agent use.     

Does Place of Residence or Time of Year Affect the Risk of Stroke Hospitalization and Death? A Descriptive Spatial and Temporal Epidemiologic Study

Background

Identifying geographic areas with significantly high risks of stroke is important for informing public health prevention and control efforts. The objective of this study was to investigate geographic and temporal patterns of stroke hospitalization and mortality risks so as to identify areas and seasons with significantly high burden of the disease in Florida. The information obtained will be useful for resource allocation for disease prevention and control.

Methods

Stroke hospitalization and mortality data from 1992 to 2012 were obtained from the Florida Agency for Health Care Administration. Age-adjusted stroke hospitalization and mortality risks for time periods 1992–94, 1995–97, 1998–2000, 2001–03, 2004–06, 2007–09 and 2010–12 were computed at the county spatial scale. Global Moran’s I statistics were computed for each of the time periods to test for evidence of global spatial clustering. Local Moran indicators of spatial association (LISA) were also computed to identify local areas with significantly high risks.

Results

There were approximately 1.5 million stroke hospitalizations and over 196,000 stroke deaths during the study period. Based on global Moran’s I tests, there was evidence of significant (p<0.05) global spatial clustering of stroke mortality risks but no evidence (p>0.05) of significant global clustering of stroke hospitalization risks. However, LISA showed evidence of local spatial clusters of both hospitalization and mortality risks with significantly high risks being observed in the north while the south had significantly low risks of stroke deaths. There were decreasing temporal trends and seasonal patterns of both hospitalization and mortality risks with peaks in the winter.

Conclusions

Although stroke hospitalization and mortality risks have declined in the past two decades, disparities continue to exist across Florida and it is evident from the results of this study that north Florida may, in fact, be part of the stroke belt despite not being in any of the traditional stroke belt states. These findings are useful for guiding public health efforts to reduce/eliminate inequities in stroke outcomes and inform policy decisions. There is need to continually identify populations with significantly high risks of stroke to better guide the targeting of limited resources to the highest risk populations.     

Identifying unique neighborhood characteristics to guide health planning for stroke and heart attack: fuzzy cluster and discriminant analyses approaches

Background

Socioeconomic, demographic, and geographic factors are known determinants of stroke and myocardial infarction (MI) risk. Clustering of these factors in neighborhoods needs to be taken into consideration during planning, prioritization and implementation of health programs intended to reduce disparities. Given the complex and multidimensional nature of these factors, multivariate methods are needed to identify neighborhood clusters of these determinants so as to better understand the unique neighborhood profiles. This information is critical for evidence-based health planning and service provision. Therefore, this study used a robust multivariate approach to classify neighborhoods and identify their socio-demographic characteristics so as to provide information for evidence-based neighborhood health planning for stroke and MI.

Methods and Findings

The study was performed in East Tennessee Appalachia, an area with one of the highest stroke and MI risks in USA. Robust principal component analysis was performed on neighborhood (census tract) socioeconomic and demographic characteristics, obtained from the US Census, to reduce the dimensionality and influence of outliers in the data. Fuzzy cluster analysis was used to classify neighborhoods into Peer Neighborhoods (PNs) based on their socioeconomic and demographic characteristics. Nearest neighbor discriminant analysis and decision trees were used to validate PNs and determine the characteristics important for discrimination. Stroke and MI mortality risks were compared across PNs. Four distinct PNs were identified and their unique characteristics and potential health needs described. The highest risk of stroke and MI mortality tended to occur in less affluent PNs located in urban areas, while the suburban most affluent PNs had the lowest risk.

Conclusions

Implementation of this multivariate strategy provides health planners useful information to better understand and effectively plan for the unique neighborhood health needs and is important in guiding resource allocation, service provision, and policy decisions to address neighborhood health disparities and improve population health.     

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

Background

Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.

Methods

A spatial statistical analysis using Kulldorff''s spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.

Results

The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001).

Conclusions

This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky.     

Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States

Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas.     

Risk factors of gastrointestinal nematode parasite infections in small ruminants kept in smallholder mixed farms in Kenya

Background

We have evaluated a sensitive screening assay for Mycobacterium tuberculosis (MTB) complex organisms and a specific assay for detecting Mycobacterium bovis DNA in lymph nodes taken from cattle with evidence of bovine tuberculosis. Underlying these series of experiments was the need for a versatile DNA extraction protocol which could handle tissue samples and with the potential for automation. The target for the screening assay was the multi-copy insertion element IS1081, present in 6 copies in the MTB complex. For confirmation of M. bovis we used primers flanking a specific deletion in the genome of M. bovis known as region of difference 4 (RD4). The sensitivity and specificity of these PCRs has been tested on genomic DNA from MTB complex reference strains, mycobacteria other than tuberculosis (MOTT), spiked samples and on clinical material.

Results

The minimum detection limits of the IS1081 method was < I genome copy and for the RD4 PCR was 5 genome copies. Both methods can be readily adapted for quantitative PCR with the use of SYBR Green intercalating dye on the RotorGene 3000 platform (Corbett Research). Initial testing of field samples of bovine lymph nodes with visible lesions (VL, n = 109) highlighted two shortfalls of the molecular approach. Firstly, comparison of IS1081 PCR with the "gold standard" of culture showed a sensitivity of approximately 70%. The sensitivity of the RD4 PCR method was 50%. Secondly, the success rate of spoligotyping applied directly to clinical material was 51% compared with cultures. A series of further experiments indicated that the discrepancy between sensitivity of detection found with purified mycobacterial DNA and direct testing of field samples was due to limited mycobacterial DNA recovery from tissue homogenates rather than PCR inhibition. The resilient mycobacterial cell wall, the presence of tissue debris and the paucibacillary nature of some cattle VL tissue may all contribute to this observation. Any of these factors may restrict application of other more discriminant typing methods. A simple means of increasing the efficiency of mycobacterial DNA recovery was assessed using a further pool of 95 cattle VL. Following modification of the extraction protocol, detection rate with the IS1081 and RD4 methods increased to 91% and 59% respectively.

Conclusion

The IS1081 PCR is a realistic screening method for rapid identification of positive cases but the sensitivity of single copy methods, like RD4 and also of spoligotyping will need to be improved to make these applicable for direct testing of tissue extracts.     

The importance of climatic factors and outliers in predicting regional monthly campylobacteriosis risk in Georgia,USA

Incidence of Campylobacter infection exhibits a strong seasonal component and regional variations in temperate climate zones. Forecasting the risk of infection regionally may provide clues to identify sources of transmission affected by temperature and precipitation. The objectives of this study were to (1) assess temporal patterns and differences in campylobacteriosis risk among nine climatic divisions of Georgia, USA, (2) compare univariate forecasting models that analyze campylobacteriosis risk over time with those that incorporate temperature and/or precipitation, and (3) investigate alternatives to supposedly random walk series and non-random occurrences that could be outliers. Temporal patterns of campylobacteriosis risk in Georgia were visually and statistically assessed. Univariate and multivariable forecasting models were used to predict the risk of campylobacteriosis and the coefficient of determination (R ²) was used for evaluating training (1999–2007) and holdout (2008) samples. Statistical control charting and rolling holdout periods were investigated to better understand the effect of outliers and improve forecasts. State and division level campylobacteriosis risk exhibited seasonal patterns with peaks occurring between June and August, and there were significant associations between campylobacteriosis risk, precipitation, and temperature. State and combined division forecasts were better than divisions alone, and models that included climate variables were comparable to univariate models. While rolling holdout techniques did not improve predictive ability, control charting identified high-risk time periods that require further investigation. These findings are important in (1) determining how climatic factors affect environmental sources and reservoirs of Campylobacter spp. and (2) identifying regional spikes in the risk of human Campylobacter infection and their underlying causes.     

The mosquitoes of eastern Tennessee: studies on abundance,habitat preferences,and host‐seeking behaviors

A significant increase in the number of reported cases of La Crosse virus (LACV) infections in eastern Tennessee has occurred in the last ten years. The objective of this study was to determine the abundance and habitat preferences of the potential vectors of LACV in this region. Adult host‐seeking mosquitoes were collected using CO₂‐baited CDC light traps and a series of human‐landing catches in eastern Tennessee from 2004 to 2006. A total of 4,200 female mosquitoes of 23 species was collected by CO₂‐baited CDC trapping at ten sites during the study period. Aedes albopictus (Skuse) was the most abundant mosquito collected at all sites and vegetation types, with the ratios of total Ae. albopictus to Ae. triseriatus (Say) females collected being 2.1:1 in 2004, 3.8:1 in 2005, and 4.9:1 in 2006. Ten species were collected during a series of human‐landing catches made at four different sites; one probable and three confirmed case sites of LACV infections, totaling 528 female mosquitoes. Aedes albopictus was the most abundant species collected, with a 4:1 ratio of Ae. albopictus to Ae. triseriatus females. Aedes albopictus exhibited two clear peaks of “landing” activity, one in the early morning and one in the late afternoon or early evening. Simple and multiple regression analyses of the predictors of the number of mosquitoes collected showed that populations of Ae. albopictus were three times more likely to be collected overall than Ae. triseriatus. Species (Ae. albopictus), vegetation (residential), and the previous cumulative precipitation for the four weeks prior to collection were significantly (P < 0.05) associated with the number of mosquitoes collected by CO₂‐baited CDC trapping. Aedes albopictus was also more likely to be collected than Ae. triseriatus at confirmed cases of LACV infections.     

Cemeteries Are Effective Sites For Monitoring La Crosse Virus (LACv) and these Environments May Play a Role in LACv Infection

La Crosse encephalitis (LAC) is the leading arboviral disease among children, and was previously limited to the upper Midwest. In 2012 nine pediatric cases of LAC occurred in eastern Tennessee, including one fatal case. In an attempt to identify sites near an active LACv infection and describe the abundance and distribution of potential LACv vectors near a fatal LAC case in the Appalachian region, we initiated an end of season study using a combination of questing and oviposition mosquito traps placed at forty-nine sites consisting of cemeteries and houses within 16 radial kilometers of two pediatric infections. LACv was isolated from three Aedes triseriatus pools collected from cemeteries and spatial clustering analysis identified clusters of Ae. triseriatus and Ae. albopictus populations that overlapped in the same area as the 2012 LACv cases. Results indicate cemeteries are effective sites for monitoring LACv. The role of cemeteries and specific environmental features will be the focus of future investigations.