Title : Objective Regressive Regression as a function of infectious entities and natural disasters
Abstract:
The control of infectious entities with repercussions on human health, as in the rest of animals, is becoming more complex every day, and it is even more difficult to control disease vector organisms and their etiological agents, which is why the scientific community is increasingly committed to research related to control alternatives that are much more efficient, sustainable, economical and environmentally friendly. We have gone through different methods and control alternatives, from biological, physical, ecological, genetic manipulation, chemical, among others, but the problem of confrontation and control of zoonotic entities remains latent, both in re-emerging and emerging entities, and will continue as long as the human species exists; This is the reason why the human intellect cannot cease in this struggle, hence our incursion and linkage with other disciplines of scientific knowledge, with emphasis on geographical sciences and mathematics, and especially, mathematical modeling and its different forecasting models, in the short, medium and long term, with emphasis on the methodology of the Regressive Objective Regression (ROR). The modeling (ROR), based on a combination of Dummy variables with ARIMA modeling, where only two Dummy variables are created and the trend of the series is obtained, requires few cases to be used and also allows the use of exogenous variables that make it possible to model and forecast in the long term, depending on the exogenous variable, It has given better results than ARIMA modeling in some variables, such as HIV modeling, viral etiology/arbovirosis entities (Dengue, Zika and Leptospirosis), parasitic entities (Malaria, Fasciolosis and Angiostrongilosis) and even in the current COVID-19 pandemic, but its application has gone beyond, up to meteorological disturbances (cyclones and hurricanes) and earthquakes.
Key words: infectious entities, Objective Regressive Regression (ORR) methodology, mathematical modeling, earthquakes.