Strategies for controlling non-transmissible infection outbreaks using a large human movement data set.

Prediction and control of the spread of infectious disease in human populations benefits greatly from our growing capacity to quantify human movement behavior. Here we develop a mathematical model for non-transmissible infections contracted from a localized environmental source, informed by a detailed description of movement patterns of the population of Great Britain. The model is applied to outbreaks of Legionnaires' disease, a potentially life-threatening form of pneumonia caused by the bacteria Legionella pneumophilia. We use case-report data from three recent outbreaks that have occurred in Great Britain where the source has already been identified by public health agencies. We first demonstrate that the amount of individual-level heterogeneity incorporated in the movement data greatly influences our ability to predict the source location. The most accurate predictions were obtained using reported travel histories to describe movements of infected individuals, but using detailed simulation models to estimate movement patterns offers an effective fast alternative. Secondly, once the source is identified, we show that our model can be used to accurately determine the population likely to have been exposed to the pathogen, and hence predict the residential locations of infected individuals. The results give rise to an effective control strategy that can be implemented rapidly in response to an outbreak.

Early diagnosis model for meningitis supports public health decision making.

OBJECTIVE: To develop a predictive model for rapid differential diagnosis of meningitis and meningococcal septicaemia to support public health decisions on chemoprophylaxis for contacts. METHODS: Prospective study of suspected cases of acute meningitis and meningococcal septicaemia admitted to hospitals in the South West, West Midlands and London Regions of England from July 2008 to June 2009. Epidemiological, clinical and laboratory variables on admission were recorded. Logistic regression was used to derive a predictive model. RESULTS: Of the 719 suspect cases reported, 385 confirmed cases were included in analysis. Peripheral blood polymorphonuclear count of >16 × 10(9)/l, serum C-reactive protein of >100 mg/l and haemorrhagic rash were strongly and independently associated with diagnosis of bacterial meningitis and meningococcal septicaemia. Using a simple scoring system, the presence of any one of these factors gave a probability of >95% in predicting the final diagnosis. CONCLUSION: We have developed a model using laboratory and clinical factors, but not dependent on availability of CSF, for differentiating acute bacterial from viral meningitis within a few hours of admission to hospital. This scoring system is recommended in public health management of suspected cases of meningitis and meningococcal septicaemia to inform decisions on chemoprophylaxis.

The frequency of heparin induced thrombocytopenia in patients undergoing elective cardiac bypass surgeries.

OBJECTIVE: To determine the frequency of Heparin Induced Thrombocytopenia (HIT) in patients undergoing elective cardiac bypass surgeries and to observe the platelets evolution post surgically in these patients. METHOD: A prospective study was designed and 100 unselected consecutive patients undergoing elective cardiac bypass surgery were enrolled and evaluated. The clinical and laboratory details were noted before and after surgery. Their platelet counts were observed from day 0 (prior to surgery) to day 5 post operatively. Particle gel immunoassay was used to demonstrate the presence of antibodies against heparin-platelet factor 4 complexes. RESULTS: There were 86 males and 14 females with median age of 59 and 53.5 years respectively. Marked platelet count variation was detected during post operative period in all patients (n=100) ranging from 23 +/- SD 186.73 to 389 +/- 84.12 X 109/L. However, 20 patients showed >50% drop on day 5 and seven of these also showed seroconversion. The clinical scoring for HIT was found to have a good negative predictive value. Thromboembolic complications were not observed in any of our patients. CONCLUSIONS: HIT is prevalent to a significant extent in patients after cardiac surgery in our clinical setting though it mostly remains undetected and is an under-diagnosed entity.