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In particular the way in which the effect of intervention measures are represented in (mathematical) models needs to be considered carefully.
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Many of these scientists are finding that research in the dry world of silicon has not prepared them for the uncertainties of a "wet" laboratory, where their mathematical models need to come alive.
Thus, mathematical models need to be used in order, not only to predict the behavior of the designed synthetic devices; but to help on the selection of the biological parts, i.e., guidelines for the experimental implementation.
Significantly complex mathematical models need to be constructed in this case, which rely on the development of special mathematical techniques to build them.
In literature, several mathematical models need the data of water flow, while the velocity and elevation of water flow are provided by the hydrodynamic model.
Mathematical models need to be informed with accurate data on contacts among individuals.
Protocols for acceptable mathematical models need to be developed [49] to analyze past and present trends, and predict future trends.
For theoretical analyses, mathematical models need to be in hand.
40 However, mathematical models need to be calibrated to the epidemiology of a specific time and place, and their results are difficult to generalize to other scenarios.
Also, mathematical models need to be developed that reflect the performance of treatment programmes in terms of efficiency and equity - these models could include measures of feasibility (as e.g. health workers availability) as health system capacity constraints.
To do this, mathematical models need to be developed that not only incorporate the population phenomenon of disease transmission, but also integrate viral evolution and disease dynamics at the individual level.
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