INTRODUCTION: Demonstrating the results of Social Distancing Strategies (SDS) became a relevant factor to obtain support by the population in São Paulo State and in Brazil. The delay in the processing of PCR tests and the small number of tests available limits the ability of sanitary authorities to make meaningful data available as to the number of cases or the number of deaths due to COVID-19. METHODOLOGY: We use a time series analysis of deaths due to COVID-19 referenced to the date of deaths (as opposed to the date in which the test results were obtained). RESULTS: We demonstrate that the SDS adopted in São Paulo City and State clearly brought meaningful results to delay the growth of COVID-19 cases. We also show that by using this type of time series it is possible to identify different trends for regions, allowing for targeted approaches. Additionally, by using a time series which is death-oriented makes it possible to identify, for São Paulo City, the effects of the SDS with the Social Isolation Index (SII) adopted in the state and to make a gross estimate for the SII, which prevents the growth of the disease. CONCLUSION: The use of a time series of deaths due to COVID-19 referenced to the date of the event allows a better understanding of the effects of the SDS on the progression of the COVID-19 epidemic in São Paulo State, Brazil.
INTRODUCTION: Demonstrating the results of Social Distancing Strategies (SDS) became a relevant factor to obtain support by the population in São Paulo State and in Brazil. The delay in the processing of PCR tests and the small number of tests available limits the ability of sanitary authorities to make meaningful data available as to the number of cases or the number of deaths due to COVID-19. METHODOLOGY: We use a time series analysis of deaths due to COVID-19 referenced to the date of deaths (as opposed to the date in which the test results were obtained). RESULTS: We demonstrate that the SDS adopted in São Paulo City and State clearly brought meaningful results to delay the growth of COVID-19 cases. We also show that by using this type of time series it is possible to identify different trends for regions, allowing for targeted approaches. Additionally, by using a time series which is death-oriented makes it possible to identify, for São Paulo City, the effects of the SDS with the Social Isolation Index (SII) adopted in the state and to make a gross estimate for the SII, which prevents the growth of the disease. CONCLUSION: The use of a time series of deaths due to COVID-19 referenced to the date of the event allows a better understanding of the effects of the SDS on the progression of the COVID-19 epidemic in São Paulo State, Brazil.
Authors: C L A Santana; C V Manfrinato; P R P Souza; A Marino; V F Condé; E Stedefeldt; L Y Tomita; M do Carmo Franco Journal: Public Health Date: 2021-08-27 Impact factor: 2.427
Authors: Ana Paula Helfer Schneider; Mari Ângela Gaedke; Janine Koepp; Éboni Marília Reuter; Camilo Darsie; Lia Gonçalves Possuelo; Andréia Rosane de Moura Valim; Marcelo Carneiro; Grupo Covid-Vrp Journal: Rev Panam Salud Publica Date: 2021-11-19
Authors: Kai Sing Sun; Terence See Man Lau; Eng Kiong Yeoh; Vincent Chi Ho Chung; Yin Shan Leung; Carrie Ho Kwan Yam; Chi Tim Hung Journal: BMJ Open Date: 2022-04-11 Impact factor: 2.692