COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave

Abstract

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.

Economic Strategy for the Impact of the COVID-19 Pandemic on Construction Project Implementation

“…Before the epidemic, several initiatives were underway in Ambon, but some were delayed, some were halted, and others were unable to proceed due to the funds being transferred to combat the COVID-19 Pandemic (Sousa, 2021). When planning for 2020 began, the total Bandung City Public Works project run was approximately 416 packages of planning, construction, and maintenance projects (Kaihuang, 2020).…”

Determinants of Physical Activity Practices in Metropolitan Context: The Case of Lisbon Metropolitan Area, Portugal

“…The COVID-19 pandemic radically changed the daily lives of families, including physical activity practices [74][75][76]. For example, in Portugal, gyms and swimming pools were closed for long periods and, when open, were subject to major constraints [77].…”

Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies

“…Given the need to uncover explanatory variables for COVID-19 spatiotemporal patterns, we supported the analysis using regression. Linear, generalized, mixed multi-level, non-linear and geographically based methods have been used for regression analysis to understand COVID-19 spatial dynamics and establish relationships with factors [5,6,8,9,46,56,57]. The choice of linear regression over more tuned methods is essentially due to two reasons.…”

“…The distribution of confirmed cases of COVID-19 had an uneven spread because the incidence of new infections was characterized by spatiotemporal heterogeneity at multiple scales [3]. The spatial patterns can be explained by multiple factors [4][5][6][7][8][9][10] that justify spatial variations in contagion exposure, vulnerability and susceptibility [11][12][13][14][15][16][17][18]. Different NPI management strategies, ranging from case isolation to comprehensive measures, are also explanatory of COVID-19 spatiotemporal variability [10,19,20].…”

“…In the case of Portugal, evidence-based knowledge about the existence of geographical contexts that are more favourable to transmission and outbreaks has been shown and highlighted by several authors [14,[43][44][45]. The spread of COVID-19 in the country has been associated with settlement patterns, transport networks, mobility behaviours, employment and other economic and social characteristics [8,[46][47][48]. However, indicators regarding the causes of the spread of the disease have not been properly integrated to serve as policy guidance in assisting public health decisionmakers.…”