ABSTRACT
Background:
Telehealth has been widely used for new case detection and telemonitoring during the COVID-19 pandemic. However, the use of this approach for syndromic surveillance has been little explored. This data can provide qualified information to feed computational models to study the disease spread.
Objective:
Herein we report using a high-quality dataset obtained from a state-based telehealth service for forecasting the geographical spread of new cases of COVID-19 in Salvador (Bahia, Brazil).
Methods:
A wide-state toll-free telehealth service collected clinical-demographic structured data four months following the first notification of COVID-19 in the Bahia State, Brazil. Calls that reported COVID-19- like symptoms were selected for temporal-spatial analysis compared to notification of COVID-19 cases.
Autoria: Roberto Carreiro, Manoel Barral Netto, Thiago Cerqueira-Silva, Viviane Boaventura, Malu Grave.
Periódico: JMIR Publications
Ano de publicação: 2022