In the context of a novel influenza virus invading a naive population, estimates of the reproduction number will determine the potential and severity of an outbreak, and provide critical information for identifying the type of disease interventions and the intensity of mitigation measures required for achieving maximum protection of community health.
This approach suggests that evidence-based design of multi-target therapies may take advantage of hierarchical patterns of convergence to improve both efficacy and selectivity of disease-intervention.
Circumstances that might bring about clinical heterogeneity included differences in severity of disease, intervention dosage, measurements, and management.
The major difference between studies employing the COPCORD protocol and the other studies was that the former included additional information related to the burden of disease, intervention and aetiology of disease.
Public health case management consisted of completion of the MHD H1N1 surveillance form, identification of possible source and spread of disease, intervention to prevent additional spread as well as general health and hygiene education.
Moreover, data obtained from cost of illness studies are increasingly being incorporated into models used for assessing the cost-effectiveness of disease intervention, which assign incremental costs to specific subgroups of patients [ 22].
Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming.
To determine whether chronic infection plays a role in initiation or progression of disease, intervention studies in humans have been initiated, and animal models of C. pneumoniae infection have been developed.
From the standpoint of disease intervention, the up-regulation of IL-6 by SMF at first seems to be unwanted because IL-6 is generally maintained at low levels in healthy tissue [ 50].
The cut-off between a short and long follow-up depends on the type of disease, intervention and outcome and we list some examples that range from 30 days to 5 years (table 6).
