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This project is trying of improving quality and order of COVID-19 of Peru. First, I managed to order and clean conflict and bug due to fail type and others issues.
This part, I show that how to do in R script. my assumption is beginning date is 4th March, 2020 and last update is 3rd April, 2023, click here.
Here, I merged four groups of variables, namely COVID-19 infected people, COVID-19 deaths, available beds of intensive care unit (ICU), and COVID-19 vaccinated people. This data was used as input for Factorial multivariate analysis, which is a special kind of multivariate analysis, click here.
Generalized additive model(GAM) is one best way to discover non-linear relationship between many variables. So that, I relate Covid mortality normalized how dependence variable and Time(days),COVID-19 positivy(%), available beds of ICU(%), COVID-19 vaccinated people(%) how independence variables, click here.
Epidemiological forecasting using machine learning (ML)involves using computational models to predict the spread of diseases or other health-related events. In this section, we employ ML to infer the COVID-19 mortality and excess mortality, essentially creating a COVID-19 mortality index. Our approach relies on key independent variables such as Time (days), COVID-19 Positivity (%), ICU Bed Availability (%), and COVID-19 Vaccinated Population (%),click here.