Decision Making in Health Management during Crisis: A Case Study Based on Epidemiological Curves of China and Italy against COVID-19

• Main Authors: Salvador Ávila Filho, Júlia Spínola Ávila, Beata Mrugalska, Naiara Fonseca de Souza, Ana Paula Meira Gomes de Carvalho, Lhaís Rodrigues Gonçalves
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: COVID-19; China; Italy; parameters; health management; crisis management
• Online Access: https://www.mdpi.com/1660-4601/18/15/8078
• ISSN: 1661-7827; 1660-4601

In December 2019, a new infectious respiratory disease called COVID-19 was identified in Wuhan, Hubei province, in China and quickly reached pandemic status in March 2020, in uncertain and frightening situation. The objective of this study was to analyze the epidemiological curves from the fight against COVID-19 in China and Italy, establishing parameters that can assist with the decisions of health-planning managers. This study was conducted using the principles of the grounded theory methodology and a practical method of comparison between the real and ideal curves, based on the contamination and death data by SARS-CoV-2 in China and Italy. For this purpose, we built graphs, including parameters, such as, among others, amplitude, height, saturation point, acceleration, lethality, event, risk, and efficiency. The results of our study showed that China exhibited amplitude and height of the active contamination and death curve 2 times smaller than those of Italy which exhibited several saturations. It was investigated that Italy presented a qualitative risk of 5–6, whereas for China it was 4. According to the parameters, China and Italy presented health management that was able to reduce the impact caused by the virus. The implementation of adequate health management with these practical tools can guide perception of the crisis critical levels, avoiding major disasters. We intend to continue to validate the method in the analysis of data from Brazil and the USA.