GET WELL: an automated surveillance system for gaining new epidemiological knowledge

<p>Abstract</p> <p>Background</p> <p>The assumption behind the presented work is that the information people search for on the internet reflects the disease status in society. By having access to this source of information, epidemiologists can get a valuable complement to the traditional surveillance and potentially get new and timely epidemiological insights. For this purpose, the Swedish Institute for Infectious Disease Control collaborates with a medical web site in Sweden.</p> <p>Methods</p> <p>We built an application consisting of two conceptual parts. One part allows for trends, based on user specified requests, to be extracted from anonymous web query data from a Swedish medical web site. The second conceptual part permits tailored analyses of particular diseases, where more complex statistical methods are applied to the data. To evaluate the epidemiological relevance of the output, we compared Google search data and search data from the medical web site.</p> <p>Results</p> <p>In the paper, we give concrete examples of the output from the web query-based system. We also present results from the comparison between data from the search engine Google and search data from the national medical web site.</p> <p>Conclusions</p> <p>The application is in regular use at the Swedish Institute for Infectious Disease Control. A system based on web queries is flexible in that it can be adapted to any disease; we get information on other individuals than those who seek medical care; and the data do not suffer from reporting delays. Although Google data are based on a substantially larger search volume, search patterns obtained from the medical web site may still convey more information from an epidemiological perspective. Furthermore we can see advantages with having full access to the raw data.</p

Temporal and spatial variation in Anaplasma phagocytophilum infection in Swedish moose (Alces alces)

The occurrence ofAnaplasma phagocytophilumwas investigated in spleen and serum samplesfrom Swedish moose (Alces alces) in southern Sweden (island and mainland). Samples wereanalysed for presence ofA. phagocytophilumDNA by real-time PCR (n=263), and forAnaplasmaantibodies with ELISA serology (n=234). All serum samples had antibodies againstA. phagocytophilum. The mean DNA-based prevalence was 26·3%, and significant (

Extraforaminal ligament attachments of the thoracic spinal nerves in humans

An anatomical study of the extraforaminal attachments of the thoracic spinal nerves was performed using human spinal columns. The objectives of the study are to identify and describe the existence of ligamentous structures at each thoracic level that attach spinal nerves to structures at the extraforaminal region. During the last 120 years, several mechanisms have been described to protect the spinal nerve against traction. All the described structures were located inside the spinal canal proximal to the intervertebral foramen. Ligaments with a comparable function just outside the intervertebral foramen are mentioned ephemerally. No studies are available about ligamentous attachments of thoracic spinal nerves to the spine. Five embalmed human thoracic spines (Th2–Th11) were dissected. Bilaterally, the extraforaminal region was dissected to describe and measure anatomical structures and their relationships with the thoracic spinal nerves. Histology was done at the sites of attachment of the ligaments to the nerves and along the ligaments. The thoracic spinal nerves are attached to the transverse process of the vertebrae cranial and caudal to the intervertebral foramen. The ligaments consist mainly of collagenous fibers. In conclusion, at the thoracic level, direct ligamentous connections exist between extraforaminal thoracic spinal nerves and nearby structures. They may serve as a protective mechanism against traction and compression of the nerves by positioning the nerve in the intervertebral foramen

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

Carpal tunnel syndrome and the "double crush" hypothesis: a review and implications for chiropractic

Upton and McComas claimed that most patients with carpal tunnel syndrome not only have compressive lesions at the wrist, but also show evidence of damage to cervical nerve roots. This "double crush" hypothesis has gained some popularity among chiropractors because it seems to provide a rationale for adjusting the cervical spine in treating carpal tunnel syndrome. Here I examine use of the concept by chiropractors, summarize findings from the literature, and critique several studies aimed at supporting or refuting the hypothesis. Although the hypothesis also has been applied to nerve compressions other than those leading to carpal tunnel syndrome, this discussion mainly examines the original application – "double crush" involving both cervical spinal nerve roots and the carpal tunnel. I consider several categories: experiments to create double crush syndrome in animals, case reports, literature reviews, and alternatives to the original hypothesis. A significant percentage of patients with carpal tunnel syndrome also have neck pain or cervical nerve root compression, but the relationship has not been definitively explained. The original hypothesis remains controversial and is probably not valid, at least for sensory disturbances, in carpal tunnel syndrome. However, even if the original hypothesis is importantly flawed, evaluation of multiple sites still may be valuable. The chiropractic profession should develop theoretical models to relate cervical dysfunction to carpal tunnel syndrome, and might incorporate some alternatives to the original hypothesis. I intend this review as a starting point for practitioners, educators, and students wishing to advance chiropractic concepts in this area

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time