In an attempt to predict Rift Valley fever epidemics, Anyamba and his colleagues compared outbreak data from the past 40 years to weather and water temperature records, some dating as far back as 1951.
We studied a nosocomial outbreak of C. parapsilosis (20 ) and compared outbreak isolates with ones obtained from sporadic infections at our facility.
However, the model could be a valuable tool for evaluating and comparing outbreaks between years in the same area.
When comparing outbreaks, there was a decrease in the percentage of bathhouse users (from 47%to19%9%, p = 0.0001) and sex workers (from 6.5% to 0%) while the percentage of HIV infected individuals did not change significantly (range: 21%-28%, p = 0.36).
A degree of spatial overlap was observed when comparing outbreaks in 2010 to 2011; however, in 2011, human infections were primarily observed in areas that were not previously affected.
Following an information theoretic approach (AIC) to compare outbreak and non-outbreak (random) locations under two sets of a priori defined logistic regression models [38], we hypothesized that poultry outbreaks would be explained by anthropogenic factors (poultry density, etc).
We chose dengue in Brazil as a case study for comparing outbreak definitions for a number of reasons.
The present study aims to compare outbreak reporting by formal and informal sources given such changes in the field.
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.
Comparing outbreak surveillance data with those from published reports demonstrates a bias that favors the publication of novel findings and exceptional events (11).
