Calculation of reproducibility rates (R0) by simplification of SIR model applied to Influenza A epidemic (H1N1) in Brazil occurred in 2009

• Autor(a) principal: Kock, Kelser de Souza
• Data de Publicação: 2017
• Outros Autores: Tavares, Estevan Grosch, Traebert, Jefferson Luiz, Maurici, Rosemeri
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista de Epidemiologia e Controle de Infecção
• Texto Completo: https://online.unisc.br/seer/index.php/epidemiologia/article/view/7685

Background and Objectives: The influenza A (H1N1) pandemic in 2009 reached more than 200 countries in different degrees of morbidity and mortality, and promoted several searches in this area, in order to help future epidemiological strategies. The use of mathematical models of infections may propitiate better comprehension of this phenomenon, and provide subsidies for intervention in public health. This study had as aim describe the reproducibility rate (R0) through simplification of mathematical model of epidemiology, estimate the value of R0 in influenza pandemic occurred in 2009 in Brazil and in Brazilian states, and compare R0 with infected population. Methods: It is an ecological study that uses a public domain data bank with notifications of influenza occurred in Brazil in 2009. A simplified analysis of compartmental model was proposed: Susceptible (S), Infected (I), and Recovered (R), in order to compare the viral reproducibility rate (R0) in Brazilian states. The value of R0 was also correlated with percentage of infected individuals. Results: An epidemic outbreak was configured in twelve states and in throughout Brazil, and more than one epidemic outbreak occurred in five states and in Distrito Federal. The correlation between R0 and the percentage of infected was strong and positive (r = 0.74), and demonstrated that a higher reproductive rate is associated with higher viral contagion. Conclusion: It is possible to conclude that the athematical simplification performed in this study points to another way to identify epidemic, because it is a basic analytical tool, and there is no complexity in computational implementations. KEYWORDS: Epidemiology. Epidemics. Computer Simulation. Influenza, Human. Communicable Diseases.