Auto-Regressive Integrated Moving Average Model (ARIMA): conceptual and methodological aspects and applicability in infant mortality

Abstract This reflective theoretical article, aims to discuss conceptual and methodological aspects about the applications of time series modeling, in particular, the Integrated Auto-regressive Moving Average model and its applicability in infant mortality. This modeling makes it possible to predict future values using past data, outlining and estimating possible scenarios of the health event, highlighting its magnitude. Due to the persistence of infant mortality as a public health problem, the applicability of this method is useful in the timely and systematic management of child health indicators, in addition to being a method with low operating cost, which in contexts of cost reduction in public healthcare services, becomes a potential management tool. However, there are still gaps in the use of statistical methods in the decision-making and policy-making process in public healthcare, such as the modeling in question. These are methodological (robust statistics), institutional (outdated information systems) and cultural obstacles (devaluation of the data produced, mainly at the local level).

Bibliographic Details

Main Authors:	Silva,Aline Beatriz dos Santos, Araújo,Ana Catarina de Melo, Frias,Paulo Germano de, Vilela,Mirella Bezerra Rodrigues, Bonfim,Cristine Vieira do
Format:	Digital revista
Language:	English
Published:	Instituto de Medicina Integral Prof. Fernando Figueira 2021
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-38292021000400647
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