Exploration tool for trends and detection of epidemiological patterns in Argentina

Abstract

This work presents the first stage of the development of an informatics tool that analyzes data from the systematized registry of deaths and their causes (coded according to ICD-9 and ICD-10) between the years 1991 and 2017 (Ministry of Health of the Argentina), combining it with demographic information from the National Institute of Statistics and Census (INDEC). The objective of the confection of this tool was to analyze various sets of cause-of-death codes, defined according to the research interest, and to quickly obtain epidemiological reports for the indicated time period. The cross-referencing of the information on deaths with demographic information and its geographic referencing (departmental, provincial and regional) allows us to calculate, for each year, the rates, incidence and mortality, and to visualize them in the reports, differentiating by sex, age group or geographic area. By using Python data analysis tools (Pandas, Geopandas, Seaborn, Ploomber), a data process with a high capacity for maintenance, flexibility and evolution was created. Considering the variability of possible epidemiological studies in Argentina (study of rare, respiratory, congenital diseases, etc.), it is expected that a tool of this type could accelerate and enrich the exploration and analysis of patterns.