Method for Active Pandemic Curve Management (MAPCM)

Willem G Odendaal

• The method allows spreading out the cases evenly without asphyxiating the economy or sacrificing lives. • The success of the method can be improved upon the more accurate the model being used is, because control decisions are made based on predictions. • The method can be implemented even without a good model. • The accuracies of all appropriate models can be improved by eliminating unknown variables via a scientific process of testing that has been lacking thusfar. • The method can be improved by a feedback loop using test data. Feedback control can handle large time delays. The better test data is in accuracy, scale, and timeliness, the more responsive this method can be. • The case data for the examples are based on US national averages. It would be better to implement the method at the state level, than at the national level. • Partitioning is not limited to geography, but can be implemented based on demographics, and any number of methods. • The curve is programmable • The outbreak timing becomes programmable. It can be started earlier or later than suggested by the herd or mitigated curves. • The curve can be adjusted to accommodate changes in healthcare resources, for example a field hospital becoming operational. • If those that are at risk can be isolated, such as the elderly and those with underlying issues, while the rest of the population is gradually loosened back to normal life, then the death rate can be reduced furtner. • Small populations are infected faster than large populations.