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Background: On March 16, 2020, the first death from CO­VID-19 was recorded in Portugal. Since then, there has been a reorganization of health services, changing the normal approach for the different cases of public health. Excess deaths recorded without a COVID-19 diagnosis are called excess mortality without COVID-19 (EM non-COVID-19). This study aims to estimate the EM non-COVID in the 7-month period after the first registered Covid-19 death. Methods: The following 2 methods were used to estimate the excess mortality in this period: the daily historical average of reported deaths and an adapted auto regressive integrated moving average (ARIMA) model, considering the previous 5 years of records until October 16. For this model, after March 16, data was replaced with the daily historical average deaths from the previous 5 years, simulating the closest scenario possible as there was no pandemic. Only deaths from natural causes were selected for these estimations. For EM non-COVID-19 estimation, we subtracted the COVID-19 deaths from the overall excess mortality. Results: Between March 16, 2020, and October 16, 2020, there was an excess of 6,330 deaths from natural causes, i.e., nearly 12% more than expected. Both methods estimated an EM non-COVID-19 of around 66–67% in this period, with a greater relevance in mid-July and mid-September. Conclusions: Excess mortality was present almost every day during the study period. EM non-COVID-19 seemed to vary over time, showing some inadequacy of healthcare services in management of other patients free of COVID-19 in Portugal during periods with a greater patient volume. It is necessary to take care and monitor COVID-19 cases but also non-COVID-19 cases.

Background: The role of demographic and socio-economic determinants of COVID-19 transmission is still unclear and is expected to vary in different contexts and epidemic periods. Exploring such determinants may generate a hypothesis about transmission and aid the definition of prevention strategies. Objectives: To identify municipality-level demographic and socio-economic determinants of COVID-19 in Portugal. Methods: We assessed determinants of COVID-19 daily cases at 4 moments of the first COVID-19 epidemic wave in Portugal, related with lockdown and post-lockdown measures. We selected 60 potential determinants from 5 dimensions: population and settlement, disease, economy, social context, and mobility. We conducted a multiple linear regression (MLR) stepwise analysis (p < 0.05) and an artificial neural network (ANN) analysis with the variables to identify predictors of the number of daily cases. Results: For MLR, some of the identified variables were: resident population and population density, exports, overnight stays in touristic facilities, the location quotient of employment in accommodation, catering and similar activities, education, restaurants and lodging, some industries and building construction, the share of the population working outside the municipality, the net migration rate, income, and renting. In ANN, some of the identified variables were: population density and resident population, urbanization, students in higher education, income, exports, social housing buildings, production services employment, and the share of the population working outside the municipality of residence. Conclusions: Several factors were identified as possible determinants of COVID-19 transmission at the municipality level. Despite limitations to the study, we believe that this information should be considered to promote communication and prevention approaches. Further research should be conducted.