Analysis and Forecasting of Two Time Series Models for Respiratory Infectious Diseases

DOI

10.2991/978-2-38476-295-8_14How to use a DOI?

Keywords

COVID-19; respiratory diseases; healthcare systems; Japan; Brazil; time series analysis; ETS model; WHO data

Abstract

The global impact of the COVID-19 pandemic has heightened attention on respiratory diseases and medical infrastructure across the globe. This study focuses on the comparison of healthcare systems in Japan, a developed country, and Brazil, a developing nation, to explore how differences in medical systems affect the distribution of healthcare resources and outcomes in respiratory disease management. Given the more extensive medical coverage in Japan compared to Brazil, this research investigates whether Japan demonstrates better outcomes in terms of lower mortality rates for respiratory diseases. Utilizing data from the World Health Organization (WHO), this study conducts a time series analysis for upper and lower respiratory tract infections, applying and comparing various predictive models. The Exponential Triple Smoothing (ETS) model showed superior fit and forecasting accuracy. The results indicate that Japan consistently maintains lower mortality rates compared to Brazil, suggesting that disparities in healthcare systems significantly influence disease outcomes. These findings underscore the importance of robust healthcare infrastructure in managing respiratory diseases, particularly in the context of a global pandemic.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xin Jin
PY  - 2024
DA  - 2024/10/21
TI  - Analysis and Forecasting of Two Time Series Models for Respiratory Infectious Diseases
BT  - Proceedings of the 4th International Conference on Public Administration, Health and Humanity Development (PAHHD 2024)
PB  - Atlantis Press
SP  - 110
EP  - 118
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-295-8_14
DO  - 10.2991/978-2-38476-295-8_14
ID  - Jin2024
ER  -