Amazonas suffered greatly during the COVID-19 pandemic. The mortality and fatality rates soared and scarcity of oxygen and healthcare supplies led the health system and funerary services to collapse. Thus, we analyzed the trends of incidence, mortality, and lethality indicators of COVID-19 and the dynamics of their main determinants in the state of Amazonas from March 2020 to June 2021. This is a time-series ecological study. We calculated the lethality, mortality, and incidence rates with official and public data from the Health Department. We used the Prais–Winsten regression and trends were classified as stationary, increasing, or decreasing. The effective reproduction number (Rt) was also estimated. Differences were considered significant when p < 0.05. We extracted 396,772 cases of and 13,420 deaths from COVID-19; 66% of deaths were in people aged over 60; 57% were men. Cardiovascular diseases were the most common comorbidity (28.84%), followed by diabetes (25.35%). Rural areas reported 53% of the total cases and 31% of the total deaths. The impact of COVID-19 in the Amazon is not limited to the direct effects of the pandemic itself; it may present characteristics of a syndemic due to the interaction of COVID-19 with pre-existing illnesses, endemic diseases, and social vulnerabilities.

Pernambuco, a northeastern Brazilian state, suffered significantly during the COVID-19 pandemic. The incidence, mortality, and fatality rates were incredibly high; these outcomes were a direct failure of the public health system to manage the COVID-19 pandemic. We developed an efficient method to analyze the trends in incidence, mortality, and lethality indicators of COVID-19 and the dynamics of their main determinants in the state of Pernambuco from March 2020 to March 2022. This was a time series ecological study. We calculated the lethality, mortality, and incidence rates with official and public data from the Health Department of this state. The effective reproduction number (Rt) was estimated, and then the periods were delimited, thus creating the efficiency model. Differences were considered significant when p < 0.05. We found 585,551 cases and 18,233 deaths from COVID-19. January 2022 was the month with the highest number of cases (6312) and, in May 2020, we recorded the highest number of deaths (149). Our method was efficient in analyzing periods of COVID-19, noting a contrast between the early and most recent periods, with the latter showing a stable number of new cases and patient deaths.