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

Comparison of neuropathic pain and neuronal apoptosis following nerve root or spinal nerve compression

Altered dorsal root ganglion (DRG) function is associated with neuropathic pain following spinal nerve injury. However, compression of the cauda equina and dorsal rhizotomy proximal to the DRG do not induce significant pain, whereas in the spinal nerve and peripheral nerve, injury distal to the DRG does induce neuropathic pain. Caspase signaling induces apoptosis, and caspase inhibitors prevent pain-related behavior. The degree of DRG neuronal apoptosis is thought to play a role in pain behavior. We suggest that differences in pain behavior according to the injury sites within the DRG may be related to imbalances in apoptotic injuries. The aim of this study was to determine which compression injury was more painful and to compare behavior with expression of tumor necrosis factor (TNF)-alpha in DRG and apoptosis in the DRG following crush injury to the L5 nerve root or L5 spinal nerve. Sprague–Dawley rats received a crush injury to the L5 spinal nerve (distal to the DRG), crush injury to the L5 nerve root (proximal to the DRG), or no crush injury (sham). Mechanical allodynia was determined by the von Frey test. Expression of TNF-alpha was compared among three groups using immunoblot findings. Furthermore, we compared the percentage of neurons injured in the DRG using immunostaining for apoptotic cells and localization of activated caspase 3. Mechanical allodynia was observed in both crush injury groups. The duration of mechanical allodynia in the distal crush group was significantly longer than in the proximal crush group (P < 0.05). TNF-alpha expression was increased in DRG neurons following injury. DRG apoptosis in the distal crush group was significantly higher than in the proximal group at each time point (P < 0.05). This study suggests that spinal nerve crush injuries produce a greater degree of DRG apoptosis than do corresponding nerve root crush injuries, and that the former injuries are associated with longer lasting mechanical allodynia. Thus, differences in the time course of mechanical allodynia might be associated with an imbalance in DRG apoptosis

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