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It also allows for constant reappraisal of shifting or changing crime patterns in response to altered opportunity structures in order to address the dynamic nature of crime epidemics over time.
DOI: http://dx.doi.org/10.7554/eLife.09015.008 The mean CFR overall was 79%9595% CI = 76.4 81.6), but there were significant differences between epidemics and within epidemics over time.
In 2008, Google launched its Flu Trends, which used the search terms typed into Google to track the progression of influenza epidemics over time.
The reliance, exclusively until recently, on the consistency in prevalence data in concentrated epidemics, over time and of the veracity of empirically derived, but nevertheless uncertain, estimates of sizes of key populations [ 30] could also lead to biased results.
In this study, we explored the connectedness of the two cross-border epidemics over time and found, similar to our previous work (Mehta et al., 2010), which used a much smaller dataset and less detailed methods, that the two epidemics were mostly separate.
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Phylogenies reconstructed from randomly sampled viral gene sequences contain valuable and unique information about population-level processes such as change in population size and growth rate, and can be used to understand the course of a viral epidemic over time [16], [17].
Trends in this epidemic over time have not been examined.
More comprehensive approaches to resource allocation include simulation models used to project the epidemic over time and compare the outcome of alternative allocation scenarios [ 8, 9].
This analysis could not provide evidence of a causal association between non-consensual sex and HIV infection and this may be due to a changing effect of the HIV epidemic over time (as discussed above), or the following design limitations.
The Joint United Nations Programme on HIV/AIDS (UNAIDS)/World Health Organization (WHO) has defined second generation surveillance (SGS) [ 28, 29] as the «regular, systematic collection, analysis and interpretation of information for use in tracking and describing changes in the HIV/AIDS epidemic over time».
BED-EIA HIV-1 Incidence Test (BED-CEIA) has been described as a tool to discriminate recent (RS) from long-term (LTS) seroconversion of HIV-1 infection, contributing to a better understanding of the dynamics of the HIV/AIDS epidemic over time.
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