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Dive into the research topics where Ram K. Raghavan is active.

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Featured researches published by Ram K. Raghavan.


PLOS ONE | 2015

Bayesian Geostatistical Analysis and Ecoclimatic Determinants of Corynebacterium pseudotuberculosis Infection among Horses

Courtney Boysen; Elizabeth G. Davis; L. A. Beard; Brian V. Lubbers; Ram K. Raghavan

Kansas witnessed an unprecedented outbreak in Corynebacterium pseudotuberculosis infection among horses, a disease commonly referred to as pigeon fever during fall 2012. Bayesian geostatistical models were developed to identify key environmental and climatic risk factors associated with C. pseudotuberculosis infection in horses. Positive infection status among horses (cases) was determined by positive test results for characteristic abscess formation, positive bacterial culture on purulent material obtained from a lanced abscess (n = 82), or positive serologic evidence of exposure to organism (≥1:512)(n = 11). Horses negative for these tests (n = 172)(controls) were considered free of infection. Information pertaining to horse demographics and stabled location were obtained through review of medical records and/or contact with horse owners via telephone. Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate). Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates. The best performing model indicated a protective effect for higher soil moisture content (OR = 0.53, 95% CrI = 0.25, 0.71), and detrimental effects for higher land surface temperature (≥35°C) (OR = 2.81, 95% CrI = 2.21, 3.85) and habitat fragmentation (OR = 1.31, 95% CrI = 1.27, 2.22) for C. pseudotuberculosis infection status in horses, while age, gender and breed had no effect. Preventative and ecoclimatic significance of these findings are discussed.


PLOS ONE | 2016

Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis

Gregg A. Hanzlicek; Ram K. Raghavan; Roman R. Ganta; Gary A. Anderson

The space-time pattern and environmental drivers (land cover, climate) of bovine anaplasmosis in the Midwestern state of Kansas was retrospectively evaluated using Bayesian hierarchical spatio-temporal models and publicly available, remotely-sensed environmental covariate information. Cases of bovine anaplasmosis positively diagnosed at Kansas State Veterinary Diagnostic Laboratory (n = 478) between years 2005–2013 were used to construct the models, which included random effects for space, time and space-time interaction effects with defined priors, and fixed-effect covariates selected a priori using an univariate screening procedure. The Bayesian posterior median and 95% credible intervals for the space-time interaction term in the best-fitting covariate model indicated a steady progression of bovine anaplasmosis over time and geographic area in the state. Posterior median estimates and 95% credible intervals derived for covariates in the final covariate model indicated land surface temperature (minimum), relative humidity and diurnal temperature range to be important risk factors for bovine anaplasmosis in the study. The model performance measured using the Area Under the Curve (AUC) value indicated a good performance for the covariate model (> 0.7). The relevance of climatological factors for bovine anaplasmosis is discussed.


Preventive Veterinary Medicine | 2012

Evaluations of hydrologic risk factors for canine leptospirosis: 94 cases (2002-2009).

Ram K. Raghavan; Karen Brenner; James J. Higgins; J. M. Shawn Hutchinson; Kenneth R. Harkin

Hydrologic and soil-hydrologic variables were evaluated retrospectively as potential risk factors for canine leptospirosis in Kansas and Nebraska using Geographic Information Systems (GIS). The sample included 94 positive and 185 negative dogs for leptospirosis predominantly based on PCR test for leptospires in urine. Hydrologic variables for the region were derived from National Hydrographic Dataset, National Flood Hazard Layer, National Wetlands Inventory; and soil-hydrologic variables from Soil Survey Geographic Database around geocoded addresses of case/control locations. Multivariable logistic models were used to determine association between hydrologic and soil-hydrologic variables and test status. Distance from water features (OR=0.82; 95% CI=0.79, 0.86), hydrologic density (OR=2.80; 95% CI=1.58, 4.96) and frequently flooded areas (OR=4.05; 95% CI=2.17, 7.55) within 2500 m surrounding case/control locations were significant risk factors for canine leptospirosis. Vaccination for dogs that live closer to water features, landscapes dominated by water features and frequent floods should be considered for leptospirosis prevention.


PLOS ONE | 2016

Hierarchical Bayesian Spatio–Temporal Analysis of Climatic and Socio–Economic Determinants of Rocky Mountain Spotted Fever

Ram K. Raghavan; Douglas G. Goodin; Daniel Neises; Gary A. Anderson; Roman R. Ganta

This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio–economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio–temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio–economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main–effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate–change impacts on tick–borne diseases are discussed.


PLOS ONE | 2014

Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

Ram K. Raghavan; Daniel Neises; Douglas G. Goodin; Daniel Andresen; Roman R. Ganta

Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005–2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005–2012, and identified poverty status, relative humidity, and an interactive factor, ‘diurnal temperature range x mixed forest area’ as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases.


Preventive Veterinary Medicine | 2012

Neighborhood-level socioeconomic and urban land use risk factors of canine leptospirosis: 94 cases (2002-2009).

Ram K. Raghavan; Karen Brenner; James J. Higgins; J. M. Shawn Hutchinson; Kenneth R. Harkin

Associations of housing, population, and agriculture census variables, and presence near public places were retrospectively evaluated as potential risk factors for canine leptospirosis using Geographic Information Systems (GIS). The sample population included 94 dogs positive for leptospirosis based on a positive polymerase chain reaction test for leptospires on urine, isolation of leptospires on urine culture, a single reciprocal serum titer of 12,800 or greater, or a four-fold rise in reciprocal serum titers over a 2-4 week period; and 185 dogs negative for leptospirosis based on a negative polymerase chain reaction test and reciprocal serum titers less than 400. Multivariable logistic regressions revealed different risk factors among different census units; however, houses lacking complete plumbing facilities [OR=2.80, 95% C.I.=1.82, 4.32 (census unit, block group); OR=1.36, 95% C.I.=1.28, 1.45 (census tract); OR=3.02, 95% C.I.=2.60, 3.52 (county)]; and poverty status by age (18-64) [OR=2.04, 95% C.I.=1.74, 2.39 (block group); OR=1.53, 95% C.I.=1.41, 1.67 (census tract); and OR=1.62, 95% C.I.=1.50, 1.76 (county)] were consistent risk factors for all census units. Living within 2500 m of a university/college and parks/forests were also significantly associated with leptospirosis status in dogs. Dogs that live under these circumstances are at higher risk for leptospirosis and pet owners should consider vaccination.


Vector-borne and Zoonotic Diseases | 2016

Maximum Entropy-Based Ecological Niche Model and Bio-Climatic Determinants of Lone Star Tick (Amblyomma americanum) Niche

Ram K. Raghavan; Douglas G. Goodin; Gregg A. Hanzlicek; Gregory Zolnerowich; Michael W. Dryden; Gary A. Anderson; Roman R. Ganta

The potential distribution of Amblyomma americanum ticks in Kansas was modeled using maximum entropy (MaxEnt) approaches based on museum and field-collected species occurrence data. Various bioclimatic variables were used in the model as potentially influential factors affecting the A. americanum niche. Following reduction of dimensionality among predictor variables using principal components analysis, which revealed that the first two principal axes explain over 87% of the variance, the model indicated that suitable conditions for this medically important tick species cover a larger area in Kansas than currently believed. Soil moisture, temperature, and precipitation were highly correlated with the first two principal components and were influential factors in the A. americanum ecological niche. Assuming that the niche estimated in this study covers the occupied distribution, which needs to be further confirmed by systematic surveys, human exposure to this known disease vector may be considerably under-appreciated in the state.


Vector-borne and Zoonotic Diseases | 2013

Environmental, climatic, and residential neighborhood determinants of feline tularemia.

Ram K. Raghavan; John A. Harrington; Gary A. Anderson; J. M. Shawn Hutchinson; Brad M. DeBey

BACKGROUND Tularemia, caused by a Gram-negative bacterium Francisella tularensis, is an occasional disease of cats in the midwestern United States and a public health concern due to its zoonotic potential. Different environmental, climatic, and pet-owners housing and socioeconomic conditions were evaluated as potential risk factors for feline tularemia using Geographic Information Systems (GIS) in a retrospective case-control study. METHODS The study included 46 cases identified as positive for tularemia based upon positive immunohistochemistry, isolation of F. tularensis using bacterial culture, and 4-fold or greater change in serum antibody titer for F. tularensis. Cats with a history of fever, malaise, icterus, and anorexia but no lesions characteristic of tularemia and/or negative immunohistochemistry, no isolation of bacteria in bacterial culture, and less than 4-fold raise in serum antibody titer for F. tularensis were treated as controls (n=93). Candidate geospatial variables from multiple thematic sources were analyzed for association with case status. Variables from National Land Cover Dataset, Soil Survey Geographic Database, US Census Bureau, and Daymet were extracted surrounding geocoded case-control household locations. Univariable screening of candidate variables followed by stepwise multivariable logistic modeling and odds ratios were used to identify strengths of variable associations and risk factors. RESULTS Living in a residence located in newly urbanized/suburban areas, residences surrounded by areas dominated by grassland vegetation, and mean vapor pressure conditions recorded during the 8(th) week prior to case arrival at the hospital are significant risk factors for feline tularemia. CONCLUSIONS Prevention strategies such as acaricide applications in residential backyards during spring and early summer periods and any behavior modifications suitable for cats that will prevent them from contracting infection from ticks or dead animals are necessary. Mean vapor pressure conditions recorded during the 8(th) week prior to case arrival at a diagnostic facility is a predictor for feline tularemia.


Journal of Medical Entomology | 2018

Surveillance for Tick-Borne Viruses Near the Location of a Fatal Human Case of Bourbon Virus (Family Orthomyxoviridae: Genus Thogotovirus) in Eastern Kansas, 2015

Harry M. Savage; Marvin S. Godsey; Nicholas A. Panella; Kristen L. Burkhalter; Justin Manford; Ingrid C Trevino-Garrison; Anne Straily; Savannah Wilson; Jaden Bowen; Ram K. Raghavan

Abstract Bourbon virus (Family Orthomyxoviridae: Genus Thogotovirus) was first isolated from a human case-patient residing in Bourbon County, Kansas, who subsequently died. Before becoming ill in late spring of 2014, the patient reported several tick bites. In response, we initiated tick surveillance in Bourbon County and adjacent southern Linn County during spring and summer of 2015. We collected 20,639 host-seeking ticks representing four species from 12 sites. Amblyomma americanum (L.) (Acari: Ixodidae) and Dermacentor variabilis (Say) (Acari: Ixodidae) accounted for nearly all ticks collected (99.99%). Three tick pools, all composed of adult A. americanum ticks collected in Bourbon County, were virus positive. Two pools were Heartland virus (Family Bunyaviridae: Genus Phlebovirus) positive, and one was Bourbon virus positive. The Bourbon virus positive tick pool was composed of five adult females collected on a private recreational property on June 5. Detection of Bourbon virus in the abundant and aggressive human-biting tick A. americanum in Bourbon County supports the contention that A. americanum is a vector of Bourbon virus to humans. The current data combined with virus detections in Missouri suggest that Bourbon virus is transmitted to humans by A. americanum ticks, including both the nymphal and adult stages, that ticks of this species become infected as either larvae, nymphs or both, perhaps by feeding on viremic vertebrate hosts, by cofeeding with infected ticks, or both, and that Bourbon virus is transstadially transmitted. Multiple detections of Heartland virus and Bourbon virus in A. americanum ticks suggest that these viruses share important components of their transmission cycles.


Journal of Medical Entomology | 2017

The Geographic Distribution of Ixodes scapularis (Acari: Ixodidae) Revisited: The Importance of Assumptions About Error Balance

A. Townsend Peterson; Ram K. Raghavan

Abstract The black-legged tick, Ixodes scapularis Say, is the primary vector of Borrelia burgdorferi, a spirochete that causes Lyme disease, in eastern North America. Lyme disease risk has generally been considered to be focused in the Northeast and the northern Midwest in the United States, yet the distribution of the vector extends considerably more broadly. A recent analysis of the distribution of the species using ecological niche modeling approaches painted an odd biogeographic picture, in which the species is distributed in a “rimming” distribution across the northern Midwest and Northeast, and along the Atlantic and Gulf coasts of the eastern United States, but not broadly in the interior of eastern North America. Here, we reanalyze the situation for this species, and demonstrate that the distribution estimated in the previous study was a consequence of assumptions about relative weights applied to different error types. A more appropriate error weighting scheme for niche modeling analyses, in which omission error is prioritized over commission error, shows a simpler distribution, in which the species ranges continuously across eastern North America; this distributional pattern is supported by independent occurrence data from the eastern Great Plains, in Kansas. We discuss implications for public health planning and intervention across the region, as well as for developing effective and predictive maps of vector distributions and pathogen transmission risk.

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Harry M. Savage

Centers for Disease Control and Prevention

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