Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-6 (of 6 Records) |
Query Trace: Bonney W[original query] |
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New Lineage of Lassa Virus, Togo, 2016.
Whitmer SLM , Strecker T , Cadar D , Dienes HP , Faber K , Patel K , Brown SM , Davis WG , Klena JD , Rollin PE , Schmidt-Chanasit J , Fichet-Calvet E , Noack B , Emmerich P , Rieger T , Wolff S , Fehling SK , Eickmann M , Mengel JP , Schultze T , Hain T , Ampofo W , Bonney K , Aryeequaye JND , Ribner B , Varkey JB , Mehta AK , Lyon GM 3rd , Kann G , De Leuw P , Schuettfort G , Stephan C , Wieland U , Fries JWU , Kochanek M , Kraft CS , Wolf T , Nichol ST , Becker S , Ströher U , Günther S . Emerg Infect Dis 2018 24 (3) 599-602 We describe a strain of Lassa virus representing a putative new lineage that was isolated from a cluster of human infections with an epidemiologic link to Togo. This finding extends the known range of Lassa virus to Togo. |
Local health department engagement with workplaces during the COVID-19 pandemic-Examining barriers of and facilitators to outbreak investigation and mitigation
Bonney T , Grant MP . Front Public Health 2023 11 1116872 OBJECTIVES: To document local health department (LHD) COVID-19 prevention or mitigation activities at workplaces in the United States and identify facilitators for and barriers to these efforts. METHODS: We conducted a web-based, cross-sectional national probability survey of United States LHDs (n = 181 unweighted; n = 2,284 weighted) from January to March 2022, collecting information about worker complaints, surveillance, investigations, relationships and interactions with employers/businesses, and LHD capacity. RESULTS: Overall, 94% LHD respondents reported investigating workplace-linked COVID-19 cases; however, 47% reported insufficient capacity to effectively receive, investigate and respond to COVID-19-related workplace safety complaints. Prior relationships with jurisdiction employers and LHD personnel with formal occupational health and safety (OHS) training were predictors of proactive outreach to prevent COVID-19 spread in workplaces (p < 0.01 and p < 0.001). LHD size predicted OHS personnel and sufficient financial resources to support workplace investigation and mitigation activities (p < 0.001). CONCLUSIONS: Differences in LHD capacity to effectively respond to communicable disease spread in workplaces may exacerbate health disparities, especially between rural and urban settings. Improving LHD OHS capacity, especially in smaller jurisdictions, could facilitate effective prevention and mitigation of workplace communicable disease spread. |
Towards Unified Data Exchange Formats for Reporting Molecular Drug Susceptibility Testing.
Bonney W , Price SF , Abhyankar S , Merrick R , Hampole V , Halse TA , DiDonato C , Dalton T , Metchock B , Starks AM , Miramontes R . Online J Public Health Inform 2020 12 (2) e14 BACKGROUND: With the rapid development of new advanced molecular detection methods, identification of new genetic mutations conferring pathogen resistance to an ever-growing variety of antimicrobial substances will generate massive genomic datasets for public health and clinical laboratories. Keeping up with specialized standard coding for these immense datasets will be extremely challenging. This challenge prompted our effort to create a common molecular resistance Logical Observation Identifiers Names and Codes (LOINC) panel that can be used to report any identified antimicrobial resistance pattern. OBJECTIVE: To develop and utilize a common molecular resistance LOINC panel for molecular drug susceptibility testing (DST) data exchange in the U.S. National Tuberculosis Surveillance System using California Department of Public Health (CDPH) and New York State Department of Health as pilot sites. METHODS: We developed an interface and mapped incoming molecular DST data to the common molecular resistance LOINC panel using Health Level Seven (HL7) v2.5.1 Electronic Laboratory Reporting (ELR) message specifications through the Orion Health™ Rhapsody Integration Engine v6.3.1. RESULTS: Both pilot sites were able to process and upload/import the standardized HL7 v2.5.1 ELR messages into their respective systems; albeit CDPH identified areas for system improvements and has focused efforts to streamline the message importation process. Specifically, CDPH is enhancing their system to better capture parent-child elements and ensure that the data collected can be accessed seamlessly by the U.S. Centers for Disease Control and Prevention. DISCUSSION: The common molecular resistance LOINC panel is designed to be generalizable across other resistance genes and ideally also applicable to other disease domains. CONCLUSION: The study demonstrates that it is possible to exchange molecular DST data across the continuum of disparate healthcare information systems in integrated public health environments using the common molecular resistance LOINC panel. |
Design and Implementation of Data Exchange Formats for Molecular Detection of Drug-Resistant Tuberculosis.
Bonney W , Price SF , Miramontes R . AMIA Jt Summits Transl Sci Proc 2019 2019 686-695 Drug-resistant tuberculosis (TB) remains a public health threat to the United States and worldwide control of TB. Rapid and reliable drug susceptibility testing (DST) is essential for aiding clinicians in selecting an optimal treatment regimen for TB patients and to prevent ongoing transmission. Growth-based DST results for culture-confirmed cases are routinely reported to the U.S. Centers for Disease Control and Prevention through the National TB Surveillance System (NTSS). However, the NTSS currently lacks the capacity and functionality to accept laboratory results from advanced molecular methods that detect mutations associated with drug resistance. The objective of this study is to design and implement novel comprehensive data exchange formats that utilize the Health Level Seven (HL7) version 2.5.1 messaging hierarchy to capture, store, and monitor molecular DST data, thereby, improving the quality of data, specifications and exchange formats within the NTSS as well as ensuring full reporting of drug-resistant TB. |
Detection of dengue virus among children with suspected malaria, Accra, Ghana
Amoako N , Duodu S , Dennis FE , Bonney JHK , Asante KP , Ameh J , Mosi L , Hayashi T , Agbosu EE , Pratt D , Operario DJ , Fields B , Liu J , Houpt ER , Armah GE , Stoler J , Awandare GA . Emerg Infect Dis 2018 24 (8) 1544-1547 We report new molecular evidence of locally acquired dengue virus infections in Ghana. We detected dengue viral RNA among children with suspected malaria by using a multipathogen real-time PCR. Subsequent sequence analysis revealed a close relationship with dengue virus serotype 2, which was implicated in a 2016 outbreak in Burkina Faso. |
Interrelationship of cytokines, hypothalamic-pituitary-adrenal axis hormones, and psychosocial variables in the prediction of preterm birth
Pearce BD , Grove J , Bonney EA , Bliwise N , Dudley DJ , Schendel DE , Thorsen P . Gynecol Obstet Invest 2010 70 (1) 40-6 BACKGROUND/AIMS: To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. METHODS: In this prospective case-control study, maternal serum biomarkers were quantified at 9-23 weeks' gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. RESULTS: Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-alpha were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743-0.874). CONCLUSION: Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator. |
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