Background:

At the end of January 2021, Portugal had over 700,000 confirmed COVID-19 cases. The burden of COVID-19 varies between and within countries due to differences in contextual and individual factors, transmission rates, and clinical and public health interventions.

Objectives:

To identify high-risk areas, between April and October, on a weekly basis and at the municipality level, and to assess the temporal evolution of COVID-19, considering municipalities classified by incidence levels.

Methods:

This is an ecological study following a 3-step approach, i.e., (1) calculation of the relative risk (RR) of the number of new confirmed COVID-19 cases, weekly, per municipality, using a spatial scan analysis; (2) classification of the municipalities according to the European Centre for Disease Control incidence categorization on November 19; and (3) characterization of RR temporal evolution by incidence groups.

Results:

Between April and October, the mean RR was 0.53, with a SD of 1.44, varying between 0 and 46.4. Globally, the north and Lisbon and Tagus Valley (LVT) area were the regions with the highest number of municipalities with a RR above 3.2. In April and beginning of May, most of the municipalities with an RR above 3.2 were from the north, while between May and August most municipalities with an RR above 3.2 were from LVT area. Comparing the incidence in November and retrospectively analyzing the RR showed the huge variation, with municipalities with an RR of 0 at a certain time classified as extremely high in November.

Conclusions:

Our results showed considerable variation in RR over time and space, with no consistent “better” or “worst” municipality. In addition to the several factors that influence COVID-19 transmission dynamics, there were some outbreaks over time and throughout the country and this may contribute to explaining the observed variation. Over time, on a weekly basis, it is important to identify critical areas allowing tailored and timely interventions in order to control outbreaks in early stages.

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