Covariates used in the study: hypothesised association with COVID-19, definitions, sources and summary statistics before transformation (when required*)
| Covariate | Abbreviation | Assoc. with | Operationalisation and measurement | Period | Mean | Min | Max | SD |
| Demographic structure | ||||||||
| 1 .Percentage 0–15 | P0–15 | +a | % of the population aged 0–15 (ln) | 2019 | 16.2 | 8.3 | 22.8 | 3.1 |
| 2 .Percentage 70+ | P70+ | +b | % of the population aged 70+ | 2019 | 12.7 | 7.6 | 18.8 | 2.1 |
| 3. Old age–sex ratio | OLDSEXR | Men+c | % of the 70+ population who is male | 2019 | 38.8 | 33.5 | 45.7 | 2.3 |
| Socioeconomic status | ||||||||
| 4. Income | INCOME | –d | Mean income (€) per person (ln) | 2016 | 15 199.0 | 7790.0 | 29 144.0 | 4633.0 |
| 5. Post-secondary education | UNI | +/–d | Age-standardised ratio of post-secondary-educated population† | 2019 | 1.0 | 0.2 | 1.8 | 0.4 |
| 6. HDI high migrants | MIGRHI | +/–d | % of the population born in foreign countries with a high HDI (ln) | 2018 | 6.7 | 1.3 | 22.8 | 4.5 |
| 7. HDI low migrants | MIGRLOW | –/+d | % of the population born in foreign countries with a low HDI (ln) | 2018 | 17.5 | 6.5 | 46.7 | 7.9 |
| Density (urban and household) | ||||||||
| 8. Population density (urban) | URBDENSITY | +e | Inhabitants (in hundreds) per hectare, excl. forest parks | 2019 | 2.9 | 0.2 | 5.9 | 1.4 |
| 9. Persons per dwelling | HHSIZE1 | +e | Average number of persons per dwelling | 2019 | 2.5 | 2.1 | 3.0 | 0.2 |
| 10. One person households | 1PHH | –e | Age-standardised relative ratio of persons living in one person households | 2019 | 1.3 | 0.9 | 2.1 | 0.2 |
| Mobility | ||||||||
| 11. Vehicles per inhabitant | VEHICLES | –f | Number of registered vehicles per 100 persons aged 20+ years | 2019 | 47.6 | 18.9 | 89.1 | 12.5 |
| 12. Mobility during lockdown | MOBILE | +g | Percentage of people who left the area of residence during lockdown. Daily average, 9 March–3 May 2020 (ln) | 2020 | 10.7 | 5.5 | 19.6 | 2.8 |
| 13. Population deregistration | PADRON | –h | Automatic deregistrations from the municipal population register (expiration of the register)/1000 (ln) | 2017–2018 | 27.3 | 7.6 | 81.9 | 14.1 |
| Health | ||||||||
| 14. Nursing homes (LTCFs) | NURSHOME | +i | Number of nursing and retirement homes (measured in beds) per 1000 people (square root) | 2020 | 9.0 | 0.0 | 81.5 | 12.3 |
| 15. Health workers | EMPLHEALTH | +j | Percentage of economically active population in health sector | 2011 | 6.9 | 2.0 | 11.5 | 1.9 |
| 16. Life expectancy | LE0 | –k | Life expectancy at birth | 2006–2017 | 84.0 | 80.3 | 86.3 | 1.3 |
Expected or observed association between covariate and mortality at the neighbourhood level (main unit of analysis): (a) the role that children play in disease transmission is still unclear as studies have shown that they are rarely the index case.12 On the other hand, school closures are likely to have led to increased childcare by elders (who are a high-risk group)14; (b) 11; (c) although infection rates are similar, the severity of disease (hence COVID-19 reporting) and death is two times greater for men than for women41; (d) as an average for the studied period, a negative association with SES indicators is expected: higher income/educated/high-HDI neighbourhoods lead to lower infection rates, although the association may be positive early on the epidemic15; (e) denser neighbourhoods and overcrowding are associated with more social contact11 15 23; (f) more vehicles, less mobility in public transport, less exposure to infection24; (g) more mobility in the geographical unit of analysis implies greater exposure to infection; (h) infection rates may be lower in neighbourhoods where part of the population has left; (i) more nursing and retirement homes, more infections in the neighbourhood27; (j) more health personnel, the greater the infection rate. This is for two reasons: they are more exposed to the virus and have systematically been tested. Note that there are 25 geographical units with repeated values due to census aggregation; (k) LE0 as a proxy for health status (the severity of COVID-19 is positively associated with coexisting illnesses).42
Data sources: (1, 2, 3, 5, 6, 7, 9, 10, 12, 13) Population Register (National Statistics and Barcelona City Council); (4) Atlas de distribución de renta de los hogares (National Statistics); (8) urban indicators (Barcelona City Council); (11) economic indicators (Barcelona City Council); (12) Estudio de movilidad durante el estado de alarma por COVID-19 (National Statistics); (14) location list and characteristics of nursing homes (Consorci de Serveis Socials de Barcelona); (15) 2011 Population Census (National Statistics); (16) health indicators (Agència de Salut Pública de Barcelona).
*The type of transformation that was applied to make the variable values more normally distributed is mentioned in brackets. ln refers to natural logarithm. See also Data transformation subsection.
†Here we first applied the age-specific percentage of post-secondary-educated persons in the municipality to the residents of every neighbourhood by age group. We got, then, an estimated number of post-secondary-educated population for every unit of analysis, which we compared with the observed one. If the observed was greater than expected, the indicator is greater than 1; if lower, less than 1.
HDI, Human Development Index; LTCFs, long-term care facilities; SES, socioeconomic status.