**5. Conclusions**

Based on the data obtained, greater attention should be paid to private residences with a capacity of over 100 people, where the number of deaths is very high.

The data show that the physical agents studied, in addition to meteorological factors, have a clear connection with the number of deaths.

The autonomous communities of Extremadura and Castilla–La Mancha are the most affectedbyahighnumberofCOVID-19deathsinthemostvulnerablepopulationgroups.

Of the pollutants studied, formaldehyde has the least influence on air quality pollution (3–4%).

In addition to carbon dioxide, PM10 and PM2.5 have a strong influence in the southern regions of Spain, Melilla and the Canary and Balearic archipelagos due to dried dust emissions from Africa.

The population density has the weakest correlation with the other variables, so it may be possible to omit this variable in subsequent studies.

PM10 concentration is strongly related to relative humidity and precipitation, and relative humidity is strongly related to nitrogen oxide.

Indoor combustion processes are the main source of nitrogen oxide emissions. Increased humidity also leads to increased nitrogen dioxide concentrations.

Special care must be taken with the data on pollutant concentrations in indoor environments, which, unfortunately, are often below the actual levels.

It is advisable to increase the number of air changes in residences to improve air quality, even if this results in higher energy costs. Health should be prioritised over cost.

These issues should be addressed in the design of buildings, particularly those of nursing homes, where significant deficiencies have been shown in the design of heating, air-conditioning and ventilation systems.

Authors should discuss the results and how they can be interpreted from the perspective of previous studies and of the working hypotheses. The findings and their implications should be discussed in the broadest context possible. Future research directions may also be highlighted.

**Author Contributions:** Conceptualization, G.S.-C., E.J.L.-F. and R.A.G.-L.; methodology, G.S.-C., E.J.L.-F. and R.A.G.-L.; software, G.S.-C., E.J.L.-F. and R.A.G.-L.; validation, G.S.-C., E.J.L.-F. and R.A.G.-L.; formal analysis G.S.-C., E.J.L.-F. and R.A.G.-L.; investigation, G.S.-C., E.J.L.-F. and R.A.G.-L.; resources G.S.-C., E.J.L.-F. and R.A.G.-L.; data curation, G.S.-C., E.J.L.-F. and R.A.G.-L.; writing— original draft preparation, G.S.-C., E.J.L.-F. and R.A.G.-L.; writing—review and editing, G.S.-C., E.J.L.-F. and R.A.G.-L.; visualization, G.S.-C., E.J.L.-F. and R.A.G.-L.; supervision, G.S.-C. and R.A.G.- L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** None of the authors have conflict of interest associated with this study to report.
