Prevalence of virological and serological markers of SARS-CoV-2 infection in the population of Ribeirão Preto, Southeast Brazil: an epidemiological survey.

INTRODUCTION: This epidemiological household survey aimed to estimate the prevalence of the current and past SARS-CoV-2 infections in Ribeirão Preto, a municipality of southeast Brazil. METHODS: The survey was conducted in two phases using a clustered sampling scheme. The first phase spanned May 1-3 and involved 709 participants. The second phase spanned June 11-14, 2020, and involved 646 participants. RESULTS: During the first phase, RT-PCR performed on nasopharyngeal swabs was positive at 0.14%. The serological tests were positive in 1.27% of the patients during the first phase and 2.79% during the second phase. People living in households with more than five members had a prevalence of 10.83% (95%CI: 1.58-74.27) higher than those living alone or with someone other. Considering the proportion of the positive serological test results with sex and age adjustments, approximately 2.37% (95%CI: 1.32-3.42) of the population had been cumulatively infected by mid-June 2020, which is equivalent to 16,670 people (95%CI: 9,267-24,074). Considering that 68 deaths from the disease in the residents of the city had been confirmed as at the date of the second phase of the survey, the infection fatality rate was estimated to be 0.41% (95%CI: 0.28-0.73). Our results suggest that approximately 88% of the cases of SARS-CoV-2 infection at the time of the survey were not reported to the local epidemiological surveillance service. CONCLUSIONS: The findings of this study provide in-depth knowledge of the COVID-19 pandemic in Brazil and are helpful for the preventive and decision-making policies of public managers.

Feasibility of very short-term forecast models for COVID-19 hospital-based surveillance.

INTRODUCTION: We evaluated the performance of Bayesian vector autoregressive (BVAR) and Holt's models to forecast the weekly COVID-19 reported cases in six units of a large hospital. METHODS: Cases reported from epidemiologic weeks (EW) 12-37 were selected as the training period, and from EW 38-41 as the test period. RESULTS: The models performed well in forecasting cases within one or two weeks following the end of the time-series, but forecasts for a more distant period were inaccurate. CONCLUSIONS: Both models offered reasonable performance in very short-term forecasts for confirmed cases of COVID-19.

Feasibility of very short-term forecast models for COVID-19 hospital-based surveillance

Abstract INTRODUCTION: We evaluated the performance of Bayesian vector autoregressive (BVAR) and Holt's models to forecast the weekly COVID-19 reported cases in six units of a large hospital. METHODS: Cases reported from epidemiologic weeks (EW) 12-37 were selected as the training period, and from EW 38-41 as the test period. RESULTS: The models performed well in forecasting cases within one or two weeks following the end of the time-series, but forecasts for a more distant period were inaccurate. CONCLUSIONS: Both models offered reasonable performance in very short-term forecasts for confirmed cases of COVID-19.