34 research outputs found

    Applying cusum-based methods for the detection of outbreaks of Ross River virus disease in Western Australia

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    <p>Abstract</p> <p>Background</p> <p>The automated monitoring of routinely collected disease surveillance data has the potential to ensure that important changes in disease incidence are promptly recognised. However, few studies have established whether the signals produced by automated monitoring methods correspond with events considered by epidemiologists to be of public health importance. This study investigates the correspondence between retrospective epidemiological evaluation of notifications of Ross River virus (RRv) disease in Western Australia, and the signals produced by two cumulative sum (cusum)-based automated monitoring methods.</p> <p>Methods</p> <p>RRv disease case notification data between 1991 and 2004 were assessed retrospectively by two experienced epidemiologists, and the timing of identified outbreaks was compared with signals generated from two different types of cusum-based automated monitoring algorithms; the three Early Aberration Reporting System (EARS) cusum algorithms (C1, C2 and C3), and a negative binomial cusum.</p> <p>Results</p> <p>We found the negative binomial cusum to have a significantly greater area under the receiver operator characteristic curve when compared with the EARS algorithms, suggesting that the negative binomial cusum has a greater level of agreement with epidemiological opinion than the EARS algorithms with respect to the existence of outbreaks of RRv disease, particularly at low false alarm rates. However, the performance of individual EARS and negative binomial cusum algorithms were not significantly different when timeliness was also incorporated into the area under the curve analyses.</p> <p>Conclusion</p> <p>Our retrospective analysis of historical data suggests that, compared with the EARS algorithms, the negative binomial cusum provides greater sensitivity for the detection of outbreaks of RRv disease at low false alarm levels, and decreased timeliness early in the outbreak period. Prospective studies are required to investigate the potential usefulness of these algorithms in practice.</p

    Lack of SARS Transmission among Public Hospital Workers, Vietnam

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    The severe acute respiratory syndrome (SARS) outbreak in Vietnam was amplified by nosocomial spread within hospital A, but no transmission was reported in hospital B, the second of two designated SARS hospitals. Our study documents lack of SARS-associated coronavirus transmission to hospital B workers, despite variable infection control measures and the use of personal protective equipment

    Clinical Description of a Completed Outbreak of SARS in Vietnam, February–May, 2003

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    We investigated the clinical manifestations and course of all probable severe acute respiratory syndrome (SARS) patients in the Vietnam outbreak. Probable SARS cases were defined by using the revised World Health Organization criteria. We systematically reviewed medical records and undertook descriptive statistical analyses. All 62 patients were hospitalized. On admission, the most prominent symptoms were malaise (82.3%) and fever (79.0%). Cough, chest pain, and shortness of breath were present in approximately one quarter of the patients; 79.0% had lymphopenia; 40.3% had thrombocytopenia; 19.4% had leukopenia; and 75.8% showed changes on chest radiograph. Fever developed on the first day of illness onset, and both respiratory symptoms and radiographic changes occurred on day 4. On average, maximal radiographic changes were observed on day 10, and fevers subsided by day 13. Symptoms on admission were nonspecific, although fever, malaise, and lymphopenia were common. The complications of SARS included invasive intubation and ventilation (11.3%) and death (9.7%)

    Approaches to the evaluation of outbreak detection methods

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    BACKGROUND: An increasing number of methods are being developed for the early detection of infectious disease outbreaks which could be naturally occurring or as a result of bioterrorism; however, no standardised framework for examining the usefulness of various outbreak detection methods exists. To promote comparability between studies, it is essential that standardised methods are developed for the evaluation of outbreak detection methods. METHODS: This analysis aims to review approaches used to evaluate outbreak detection methods and provide a conceptual framework upon which recommendations for standardised evaluation methods can be based. We reviewed the recently published literature for reports which evaluated methods for the detection of infectious disease outbreaks in public health surveillance data. Evaluation methods identified in the recent literature were categorised according to the presence of common features to provide a conceptual basis within which to understand current approaches to evaluation. RESULTS: There was considerable variation in the approaches used for the evaluation of methods for the detection of outbreaks in public health surveillance data, and appeared to be no single approach of choice. Four main approaches were used to evaluate performance, and these were labelled the Descriptive, Derived, Epidemiological and Simulation approaches. Based on the approaches identified, we propose a basic framework for evaluation and recommend the use of multiple approaches to evaluation to enable a comprehensive and contextualised description of outbreak detection performance. CONCLUSION: The varied nature of performance evaluation demonstrated in this review supports the need for further development of evaluation methods to improve comparability between studies. Our findings indicate that no single approach can fulfil all evaluation requirements. We propose that the cornerstone approaches to evaluation identified provide key contributions to support internal and external validity and comparability of study findings, and suggest these be incorporated into future recommendations for performance assessment

    Factors associated with nosocomial SARS-CoV transmission among healthcare workers in Hanoi, Vietnam, 2003

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    BACKGROUND: In March of 2003, an outbreak of Severe Acute Respiratory Syndrome (SARS) occurred in Northern Vietnam. This outbreak began when a traveler arriving from Hong Kong sought medical care at a small hospital (Hospital A) in Hanoi, initiating a serious and substantial transmission event within the hospital, and subsequent limited spread within the community. METHODS: We surveyed Hospital A personnel for exposure to the index patient and for symptoms of disease during the outbreak. Additionally, serum specimens were collected and assayed for antibody to SARS-associated coronavirus (SARS-CoV) antibody and job-specific attack rates were calculated. A nested case-control analysis was performed to assess risk factors for acquiring SARS-CoV infection. RESULTS: One hundred and fifty-three of 193 (79.3%) clinical and non-clinical staff consented to participate. Excluding job categories with <3 workers, the highest SARS attack rates occurred among nurses who worked in the outpatient and inpatient general wards (57.1, 47.4%, respectively). Nurses assigned to the operating room/intensive care unit, experienced the lowest attack rates (7.1%) among all clinical staff. Serologic evidence of SARS-CoV infection was detected in 4 individuals, including 2 non-clinical workers, who had not previously been identified as SARS cases; none reported having had fever or cough. Entering the index patient's room and having seen (viewed) the patient were the behaviors associated with highest risk for infection by univariate analysis (odds ratios 20.0, 14.0; 95% confidence intervals 4.1–97.1, 3.6–55.3, respectively). CONCLUSION: This study highlights job categories and activities associated with increased risk for SARS-CoV infection and demonstrates that a broad diversity of hospital workers may be vulnerable during an outbreak. These findings may help guide recommendations for the protection of vulnerable occupational groups and may have implications for other respiratory infections such as influenza

    Using GIS to create synthetic disease outbreaks

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    BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

    Disease surveillance using a hidden Markov model

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    <p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

    Human Neural Stem Cells Differentiate and Promote Locomotor Recovery in an Early Chronic Spinal coRd Injury NOD-scid Mouse Model

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    Traumatic spinal cord injury (SCI) results in partial or complete paralysis and is characterized by a loss of neurons and oligodendrocytes, axonal injury, and demyelination/dysmyelination of spared axons. Approximately 1,250,000 individuals have chronic SCI in the U.S.; therefore treatment in the chronic stages is highly clinically relevant. Human neural stem cells (hCNS-SCns) were prospectively isolated based on fluorescence-activated cell sorting for a CD133(+) and CD24(-/lo) population from fetal brain, grown as neurospheres, and lineage restricted to generate neurons, oligodendrocytes and astrocytes. hCNS-SCns have recently been transplanted sub-acutely following spinal cord injury and found to promote improved locomotor recovery. We tested the ability of hCNS-SCns transplanted 30 days post SCI to survive, differentiate, migrate, and promote improved locomotor recovery.hCNS-SCns were transplanted into immunodeficient NOD-scid mice 30 days post spinal cord contusion injury. hCNS-SCns transplanted mice demonstrated significantly improved locomotor recovery compared to vehicle controls using open field locomotor testing and CatWalk gait analysis. Transplanted hCNS-SCns exhibited long-term engraftment, migration, limited proliferation, and differentiation predominantly to oligodendrocytes and neurons. Astrocytic differentiation was rare and mice did not exhibit mechanical allodynia. Furthermore, differentiated hCNS-SCns integrated with the host as demonstrated by co-localization of human cytoplasm with discrete staining for the paranodal marker contactin-associated protein.The results suggest that hCNS-SCns are capable of surviving, differentiating, and promoting improved locomotor recovery when transplanted into an early chronic injury microenvironment. These data suggest that hCNS-SCns transplantation has efficacy in an early chronic SCI setting and thus expands the "window of opportunity" for intervention

    Oral Abstracts 7: RA ClinicalO37. Long-Term Outcomes of Early RA Patients Initiated with Adalimumab Plus Methotrexate Compared with Methotrexate Alone Following a Targeted Treatment Approach

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    Background: This analysis assessed, on a group level, whether there is a long-term advantage for early RA patients treated with adalimumab (ADA) + MTX vs those initially treated with placebo (PBO) + MTX who either responded to therapy or added ADA following inadequate response (IR). Methods: OPTIMA was a 78- week, randomized, controlled trial of ADA + MTX vs PBO + MTX in MTX-naïve early (<1 year) RA patients. Therapy was adjusted at week 26: ADA + MTX-responders (R) who achieved DAS28 (CRP) <3.2 at weeks 22 and 26 (Period 1, P1) were re-randomized to withdraw or continue ADA and PBO + MTX-R continued randomized therapy for 52 weeks (P2); IR-patients received open-label (OL) ADA + MTX during P2. This post hoc analysis evaluated the proportion of patients at week 78 with DAS28 (CRP) <3.2, HAQ-DI <0.5, and/or ΔmTSS ≤0.5 by initial treatment. To account for patients who withdrew ADA during P2, an equivalent proportion of R was imputed from ADA + MTX-R patients. Results: At week 26, significantly more patients had low disease activity, normal function, and/or no radiographic progression with ADA + MTX vs PBO + MTX (Table 1). Differences in clinical and functional outcomes disappeared following additional treatment, when PBO + MTX-IR (n = 348/460) switched to OL ADA + MTX. Addition of OL ADA slowed radiographic progression, but more patients who received ADA + MTX from baseline had no radiographic progression at week 78 than patients who received initial PBO + MTX. Conclusions: Early RA patients treated with PBO + MTX achieved comparable long-term clinical and functional outcomes on a group level as those who began ADA + MTX, but only when therapy was optimized by the addition of ADA in PBO + MTX-IR. Still, ADA + MTX therapy conferred a radiographic benefit although the difference did not appear to translate to an additional functional benefit. Disclosures: P.E., AbbVie, Merck, Pfizer, UCB, Roche, BMS—Provided Expert Advice, Undertaken Trials, AbbVie—AbbVie sponsored the study, contributed to its design, and participated in the collection, analysis, and interpretation of the data, and in the writing, reviewing, and approval of the final version. R.F., AbbVie, Pfizer, Merck, Roche, UCB, Celgene, Amgen, AstraZeneca, BMS, Janssen, Lilly, Novartis—Research Grants, Consultation Fees. S.F., AbbVie—Employee, Stocks. A.K., AbbVie, Amgen, AstraZeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, UCB—Research Grants, Consultation Fees. H.K., AbbVie—Employee, Stocks. S.R., AbbVie—Employee, Stocks. J.S., AbbVie, Amgen, AstraZeneca, BMS, Celgene, Centocor-Janssen, GlaxoSmithKline, Lilly, Pfizer (Wyeth), MSD (Schering-Plough), Novo-Nordisk, Roche, Sandoz, UCB—Research Grants, Consultation Fees. R.V., AbbVie, BMS, GlaxoSmithKline, Human Genome Sciences, Merck, Pfizer, Roche, UCB Pharma—Consultation Fees, Research Support. Table 1.Week 78 clinical, functional, and radiographic outcomes in patients who received continued ADA + MTX vs those who continued PBO + MTX or added open-label ADA following an inadequate response ADA + MTX, n/N (%)a PBO + MTX, n/N (%)b Outcome Week 26 Week 52 Week 78 Week 26 Week 52 Week 78 DAS28 (CRP) <3.2 246/466 (53) 304/465 (65) 303/465 (65) 139/460 (30)*** 284/460 (62) 300/460 (65) HAQ-DI <0.5 211/466 (45) 220/466 (47) 224/466 (48) 150/460 (33)*** 203/460 (44) 208/460 (45) ΔmTSS ≤0.5 402/462 (87) 379/445 (86) 382/443 (86) 330/459 (72)*** 318/440 (72)*** 318/440 (72)*** DAS28 (CRP) <3.2 + ΔmTSS ≤0.5 216/462 (47) 260/443 (59) 266/443 (60) 112/459 (24)*** 196/440 (45) 211/440 (48)*** DAS28 (CRP) <3.2 + HAQ-DI <0.5 + ΔmTSS ≤0.5 146/462 (32) 168/443 (38) 174/443 (39) 82/459 (18)*** 120/440 (27)*** 135/440 (31)** aIncludes patients from the ADA Continuation (n = 105) and OL ADA Carry On (n = 259) arms, as well as the proportional equivalent number of responders from the ADA Withdrawal arm (n = 102). bIncludes patients from the MTX Continuation (n = 112) and Rescue ADA (n = 348) arms. Last observation carried forward: DAS28 (CRP) and HAQ-DI; Multiple imputations: ΔmTSS. ***P < 0.001 and **iP < 0.01, respectively, for differences between initial treatments from chi-squar

    Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

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    Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes
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