Estimating the Location and Spatial Extent of a Covert Anthrax Release

Rapidly identifying the features of a covert release of an agent such as anthrax could help to inform the planning of public health mitigation strategies. Previous studies have sought to estimate the time and size of a bioterror attack based on the symptomatic onset dates of early cases. We extend the scope of these methods by proposing a method for characterizing the time, strength, and also the location of an aerosolized pathogen release. A back-calculation method is developed allowing the characterization of the release based on the data on the first few observed cases of the subsequent outbreak, meteorological data, population densities, and data on population travel patterns. We evaluate this method on small simulated anthrax outbreaks (about 25–35 cases) and show that it could date and localize a release after a few cases have been observed, although misspecifications of the spore dispersion model, or the within-host dynamics model, on which the method relies can bias the estimates. Our method could also provide an estimate of the outbreak's geographical extent and, as a consequence, could help to identify populations at risk and, therefore, requiring prophylactic treatment. Our analysis demonstrates that while estimates based on the first ten or 15 observed cases were more accurate and less sensitive to model misspecifications than those based on five cases, overall mortality is minimized by targeting prophylactic treatment early on the basis of estimates made using data on the first five cases. The method we propose could provide early estimates of the time, strength, and location of an aerosolized anthrax release and the geographical extent of the subsequent outbreak. In addition, estimates of release features could be used to parameterize more detailed models allowing the simulation of control strategies and intervention logistics

Approaches to the evaluation of outbreak detection methods

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

Family Planning Decisions, Perceptions and Gender Dynamics among Couples in Mwanza, Tanzania: A Qualitative Study.

Contraceptive use is low in developing countries which are still largely driven by male dominated culture and patriarchal values. This study explored family planning (FP) decisions, perceptions and gender dynamics among couples in Mwanza region of Tanzania. Twelve focus group discussions and six in-depth interviews were used to collect information from married or cohabiting males and females aged 18-49. The participants were purposively selected. Qualitative methods were used to explore family planning decisions, perceptions and gender dynamics among couples. A guide with questions related to family planning perceptions, decisions and gender dynamics was used. The discussions and interviews were tape-recorded, transcribed verbatim and analyzed manually and subjected to content analysis. Four themes emerged during the study. First, "risks and costs" which refer to the side effects of FP methods and the treatment of side -effects as well as the costs inherit in being labeled as an unfaithful spouse. Second, "male involvement" as men showed little interest in participating in family planning issues. However, the same men were mentioned as key decision-makers even on the number of children a couple should have and the child spacing of these children. Third, "gender relations and communication" as participants indicated that few women participated in decision-making on family planning and the number of children to have. Fourth, "urban-rural differences", life in rural favoring having more children than urban areas therefore, the value of children depended on the place of residence. Family Planning programs should adapt the promotion of communication as well as joint decision-making on FP among couples as a strategy aimed at enhancing FP use

Web Queries as a Source for Syndromic Surveillance

In the field of syndromic surveillance, various sources are exploited for outbreak detection, monitoring and prediction. This paper describes a study on queries submitted to a medical web site, with influenza as a case study. The hypothesis of the work was that queries on influenza and influenza-like illness would provide a basis for the estimation of the timing of the peak and the intensity of the yearly influenza outbreaks that would be as good as the existing laboratory and sentinel surveillance. We calculated the occurrence of various queries related to influenza from search logs submitted to a Swedish medical web site for two influenza seasons. These figures were subsequently used to generate two models, one to estimate the number of laboratory verified influenza cases and one to estimate the proportion of patients with influenza-like illness reported by selected General Practitioners in Sweden. We applied an approach designed for highly correlated data, partial least squares regression. In our work, we found that certain web queries on influenza follow the same pattern as that obtained by the two other surveillance systems for influenza epidemics, and that they have equal power for the estimation of the influenza burden in society. Web queries give a unique access to ill individuals who are not (yet) seeking care. This paper shows the potential of web queries as an accurate, cheap and labour extensive source for syndromic surveillance

Definitions, Criteria and Global Classification of Mast Cell Disorders with Special Reference to Mast Cell Activation Syndromes: A Consensus Proposal

Activation of tissue mast cells (MCs) and their abnormal growth and accumulation in various organs are typically found in primary MC disorders also referred to as mastocytosis. However, increasing numbers of patients are now being informed that their clinical findings are due to MC activation (MCA) that is neither associated with mastocytosis nor with a defined allergic or inflammatory reaction. In other patients with MCA, MCs appear to be clonal cells, but criteria for diagnosing mastocytosis are not met. A working conference was organized in 2010 with the aim to define criteria for diagnosing MCA and related disorders, and to propose a global unifying classification of all MC disorders and pathologic MC reactions. This classification includes three types of `MCA syndromes' (MCASs), namely primary MCAS, secondary MCAS and idiopathic MCAS. MCA is now defined by robust and generally applicable criteria, including (1) typical clinical symptoms, (2) a substantial transient increase in serum total tryptase level or an increase in other MC-derived mediators, such as histamine or prostaglandin D 2, or their urinary metabolites, and (3) a response of clinical symptoms to agents that attenuate the production or activities of MC mediators. These criteria should assist in the identification and diagnosis of patients with MCAS, and in avoiding misdiagnoses or overinterpretation of clinical symptoms in daily practice. Moreover, the MCAS concept should stimulate research in order to identify and exploit new molecular mechanisms and therapeutic targets. Copyright (C) 2011 S. Karger AG, Base

Validity of registration of ICD codes and prescriptions in a research database in Swedish primary care: a cross-sectional study in Skaraborg primary care database

<p>Abstract</p> <p>Background</p> <p>In recent years, several primary care databases recording information from computerized medical records have been established and used for quality assessment of medical care and research. However, to be useful for research purposes, the data generated routinely from every day practice require registration of high quality. In this study we aimed to investigate (i) the frequency and validity of ICD code and drug prescription registration in the new Skaraborg primary care database (SPCD) and (ii) to investigate the sources of variation in this registration.</p> <p>Methods</p> <p>SPCD contains anonymous electronic medical records (ProfDoc III) automatically retrieved from all 24 public health care centres (HCC) in Skaraborg, Sweden. The frequencies of ICD code registration for the selected diagnoses diabetes mellitus, hypertension and chronic cardiovascular disease and the relevant drug prescriptions in the time period between May 2002 and October 2003 were analysed. The validity of data registration in the SPCD was assessed in a random sample of 50 medical records from each HCC (n = 1200 records) using the medical record text as gold standard. The variance of ICD code registration was studied with multi-level logistic regression analysis and expressed as median odds ratio (MOR).</p> <p>Results</p> <p>For diabetes mellitus and hypertension ICD codes were registered in 80-90% of cases, while for congestive heart failure and ischemic heart disease ICD codes were registered more seldom (60-70%). Drug prescription registration was overall high (88%). A correlation between the frequency of ICD coded visits and the sensitivity of the ICD code registration was found for hypertension and congestive heart failure but not for diabetes or ischemic heart disease.</p> <p>The frequency of ICD code registration varied from 42 to 90% between HCCs, and the greatest variation was found at the physician level (MOR_PHYSICIAN= 4.2 and MOR_HCC= 2.3).</p> <p>Conclusions</p> <p>Since the frequency of ICD code registration varies between different diagnoses, each diagnosis must be separately validated. Improved frequency and quality of ICD code registration might be achieved by interventions directed towards the physicians where the greatest amount of variation was found.</p

The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic

Twitter is a free social networking and micro-blogging service that enables its millions of users to send and read each other's “tweets,” or short, 140-character messages. The service has more than 190 million registered users and processes about 55 million tweets per day. Useful information about news and geopolitical events lies embedded in the Twitter stream, which embodies, in the aggregate, Twitter users' perspectives and reactions to current events. By virtue of sheer volume, content embedded in the Twitter stream may be useful for tracking or even forecasting behavior if it can be extracted in an efficient manner. In this study, we examine the use of information embedded in the Twitter stream to (1) track rapidly-evolving public sentiment with respect to H1N1 or swine flu, and (2) track and measure actual disease activity. We also show that Twitter can be used as a measure of public interest or concern about health-related events. Our results show that estimates of influenza-like illness derived from Twitter chatter accurately track reported disease levels