ABSTRACT
BACKGROUND: We aimed to visualize and classify the time series of COVID-19, tuberculosis (TB) notification, and TB outcomes (cure, treatment abandonment, and death), verify the impact of the new coronavirus pandemic on these indices in Brazil, and verify the presence of spatial autocorrelation between COVID-19 and TB. METHODS: This was an ecological time series study that considered TB and COVID-19 cases. Seasonal Trend Decomposition using Loess (STL) was used to trace the temporal trend, Prais-Winsten was used to classify the temporal trend, Interrupted Time Series (ITS) was used to verify the impact of COVID-19 on TB rates, and the Bivariate Moran Index (Global and Local) was used to verify the spatial autocorrelation of events. RESULTS: Brazil and its macro-regions showed an increasing temporal trend for the notification of TB in the pre-pandemic period. Only the Northeast Region showed a decreasing temporal trend for cured cases. For treatment abandonment, all regions except for the Northeast showed an increasing temporal trend, and regarding death, Brazil and the Northeast Region showed an increasing temporal trend. With the ITS, COVID-19 caused a decline in TB notification rates and TB outcome rates. With the global spatial analysis, it was possible to identify the existence of spatial autocorrelation between the notification rate of COVID-19 and the TB notification rate and deaths. With the local analysis, it was possible to map the Brazilian municipalities and classify them according to the relationship between the rates of both diseases and space. CONCLUSIONS: COVID-19 influenced the follow-up of and adherence to TB treatment and intensified social vulnerability and, consequently, affected the notification of TB since the relationship between the disease and social determinants of health is already known. The restoration and strengthening of essential services for the prevention and detection of cases and treatment of TB in endemic environments such as Brazil have been oriented as a priority in the global health agenda.
ABSTRACT
BACKGROUND: The aim of this study was to describe the temporal trend of tuberculosis cases according to sex and age group and evidence the level of disease before the Covid-19 pandemic in a TB high endemic city. METHODS: This was a time series study carried out in a city in northeast Brazil. The population was composed of cases of tuberculosis, excluding those with HIV-positive status, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to sex and age group, was performed. Subsequently, the progression of the trend and prediction of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average (ARIMA) model and the usual Box-Jenkins method were used to choose the most appropriate models. RESULTS: A total of 1620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both sexes, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend in the years 2002-2018, with a trend of stability. CONCLUSIONS: The study evidenced a decreasing trend in tuberculosis, even before the Covid-19 pandemic, for both sex and age; however, in a step really slow from that recommended by the World Health Organization. According to the results, the disease would have achieved a level of stability in the city next years, however it might have been aggravated by the pandemic. These findings are relevant to evidence the serious behavior and trends of TB in a high endemic scenario considering a context prior to the Covid-19 pandemic.