This study provides significant findings on the associations between COVID-19 mortality rates, long-term exposure to PM2.5, and temperature in the context of socio-spatial disparity across the ninety-six departments of France.
Spatial distribution of COVID-19 mortality rate and environmental factors
The geographic distribution of annual average PM2.5 concentration levels across France was uneven and reflected the distribution of emission sources and urbanisation rate of each department.
Our results showed an increasing trend in the distribution of COVID-19 mortality rates across the departments grouped into quartiles of the annual average level of PM2.5. Indeed, despite the gradual spread of the COVID-19 pandemic across the whole country, the mortality rate followed a gradient determined by the level of PM2.5, as shown in Fig. 1. They were all higher in the departments where the annual average of long-term PM2.5 concentrations was also high. Our results highlighted the existence of a strong correlation between the mortality rate due to COVID-19 and long-term exposure to PM2.5.
These results overlapped well with the COVID-19 incidence data published regularly by the Ministry of Health. Considered separately, some departments could present an epidemiological picture different from the group to which it was assigned based on its level of PM2.5 concentration. The spatial distribution of COVID-19 cases and deaths is not random and may be related to environmental factors [32].
These geographic disparities in COVID-19 mortality rates, depending on the level of long-term PM2.5, could be related to other parameters such as the pandemic's spatial dynamics, the intensity of social interactions, and aggregation of infected individuals [33]. These disparities could also be associated with the differential vulnerability between each sub-national level, such as the existence of medical conditions [2, 27] and socio-economic conditions. Environmental factors and various vulnerabilities could represent a favourable context for the spread of the COVID-19 pandemic and the increase in COVID-19 deaths [17]. The maps made it possible to observe the evolution (or trend) of the COVID-19 mortality rate across departments, given their levels of long-term exposure to PM2.5, expressed in quartiles.
Other studies have shown significant correlations between long-term exposure to PM2.5, and the incidence or mortality due to the COVID-19 pandemic [17, 34]. Pansini and Fornacca [34] concluded that higher mortality was also correlated with poor air quality, namely, high PM2.5. In this new study, significant positive correlations of the COVID-19 mortality rate were found with long-term exposure to PM2.5, urbanisation rate, population density, and standardised prevalence rate of diabetes. In contrast, negative correlations were found with long-term annual average temperature.
Association between COVID-19 mortality rate and long-term PM2.5 exposure
The existence of an association between the risk of death and hospitalisation for COVID-19 and long-term exposure to PM2.5 indicates the role of air pollution in the development of an increased vulnerability of specific populations to COVID -19, especially the elderly, men, and people living in large urban areas. We observed a positive gradient in the COVID-19 mortality rate linked to the annual average level of PM2.5, when defined by quartile.
Our study showed the stability of the impact of long-term exposure to PM2.5 on the COVID-19 mortality rate, varying from 1.244 (or 24.4%) to 1.258 (or 25.8%) on May 1 to October 1, respectively, before falling to 1.151 (or 15.1%) on 1 November then ceased to be statistically significant on December 1 and 31 2020. The beginning of the decrease in the intensity of the association between long-term exposure to PM2.5, and the COVID-19 mortality rate seemed to coincide with the pandemic's resurgence in September (see Supplementary Material Fig 1), also called the second wave. This second wave amplified the spread of SARS-CoV-2 through departments that were slightly affected and had lower PM2.5. This would have gradually reduced the specific effects of geographic disparities in pollution levels between departments.
On the other hand, considering the distribution of long-term exposure to PM2.5, our results revealed a positive gradient in the impact of air pollution on the COVID-19 mortality rate from the third quartile. This gradient was observed until 1 November 2020. From December 1, only the departments belonging to the third quartile of the PM2.5 concentration level had higher COVID-19 mortality rates than those in the first quartile. This result is important as it suggests that the effect of long-term exposure to PM2.5 on the COVID-19 mortality rate was not significant in France until the end of 2020. In addition, this effect remained associated with the geographic disparities in mortality rates observed when less comprehensive analyses could be performed. It should also be noted that there was no statistically significant difference in the COVID-19 mortality rates between the departments located in the first and the second quartiles. Since the start of the SARS-CoV-2 pandemic, several studies have advanced various hypotheses that may help to understand the mechanisms by which exposure to PM2.5, and air pollution in general, would influence the spread of the coronavirus and would induce the severity of infected cases and deaths [35-38]. For example, Wang et al. [39] considered that PM2.5 could facilitate SARS-CoV-2 infection through the overregulation of ACE2. As the impact of air pollution on health is well documented, the association between long-term air pollution and the severity of infected cases and mortality is thought to be mediated by the various morbidity conditions caused by chronic exposure to poor air quality.
This association could be explained by the fact that short- and long-term exposure to air pollution in the population was linked to asthma attacks, exacerbation of COPD, acute respiratory inflammation, and cardiorespiratory disease linked to death. Prolonged exposure to air pollution leads to a chronic inflammatory stimulus, even in young and healthy subjects, and could induce persistent modifications of the immune system, for which short-term changes in air quality may not be sufficient to break the aforementioned vicious circle [24]. Of course, the latter authors have observed the persistence of a high fatality rate, despite the dramatic reduction in air pollution levels in Lombardy since the start of the outbreak. Our results showed certain stability of the effects of long-term exposure to PM2.5, on the COVID-19 mortality rates. These results are consistent with those obtained by other studies in the USA, Italy, China, Great Britain, the Netherlands, and Spain.
In the USA, Wu et al. [13] found that an increase of only 1 µg/m3 in long-term average PM2.5, is associated with a statistically significant increase of 15% in the COVID-19 mortality rate with data collected on 5 April 2020. Using data from 18 June 2020 the same authors found that the association led to an increase of 11% in the COVID-19 mortality rate [8].
In the Netherlands, Cole et al. [40] examined COVID-19 data between February and June 2020 and found a statistically significant positive relationship between long-term PM2.5 exposure and COVID-19 deaths. Their findings indicated that an increase in PM2.5 concentrations of 1 µg/m³ was associated with an increase in COVID-19 deaths of between 13.0% and 21.4%.
Coker et al. [15] found a 1 µg/m³ increase in PM2.5, leading to a 9% increase in COVID-19 related excess mortality at the municipality level.
In a study concerning the regional and global contributions of air pollution to the risk of death from COVID-19, Pozzer et al. [37] found that the COVID-19 mortality fraction attributed to air pollution was 11% for fossil fuel-related emissions in France, 17% in Germany, 12% in Italy, and 9% in the UK. These authors considered that long-term exposure to high levels of PM2.5 is a significant co-factor that influences the severity of COVID-19 outcomes and increases the risk of mortality from SARS-CoV-2 [37].
However, the scope of these significant associations should be moderated because the health outcome considered, whether the number of cases of COVID-19 or the number of deaths, was measured during the first 2–3 months of the onset pandemic. It is a short period, during which the spread of the pandemic was mainly limited to parts of the countries, particularly because of the adoption of containment and physical distancing measures. We assume that the magnitude of the association between long-term exposure to PM2.5, and the COVID-19 mortality rate would tend to decrease or even disappear as the spread of the pandemic progresses and affects multiple geographic areas across the entire country. Our study has shown how this association is sensitive to the spread of the pandemic over different periods. Indeed, in the case of France, with COVID-19 mortality data as of 1 November 2020 a 1 µg/m³ increase in PM2.5 corresponded to a 15% increase in COVID-19 mortality rate, while with the data from the month of December, this association was no longer significant with the same variables. This result suggests that the association was not sustainable in the long term, and it might only represent a snapshot of the spread of the pandemic in the country [41].
Association between COVID-19 mortality rate and temperature
Several recent studies have analysed the influence of air quality on the spread of the COVID-19 pandemic and the resulting deaths [14, 18, 19, 20, 42-44]. Most of the results of these studies suggest that temperature could play an important role in the spread of the COVID-19 pandemic, as in the case of the influenza epidemic. On the contrary, other studies have not found statistically significant associations between the incidence and/or mortality due to COVID-19 and temperature [43].
Our results highlight the existence of these two seemingly contradictory situations during the analysis period. In fact, until 1 October 2020 the COVID-19 mortality rate was not statistically associated with temperature. However, from 1 November, the association became significant.
Over the study period, the multiplication coefficient of the association between mortality rate and temperature was less than 1, suggesting an inverse relationship between the two. However, this inverse relationship was statistically significant only with regards to the readings on 1 November, 1 December, and 31 December.
Thus, a degree of increase in the average temperature was associated with a 9.6% decrease in the COVID-19 mortality rate on 1 November, 13.0% a month later on 1 December, and then 14.1% as of 31 December 2020. These results could be explained by the fact that the COVID-19 mortality rate increased more sharply in the departments where low temperatures were more frequent than in the departments of the West and South-West of France.
Qi et al. [42] showed that both temperature and humidity are negatively associated with COVID-19.
In France, the emergence of the second wave coincided with the gradual drop in temperatures, notwithstanding the supposed relaxation of certain social distancing gestures, and tends to reinforce the hypothesis of a significant effect of temperature on the incidence and death rate of COVID-19. Our results are consistent with those found in China [18] and Spain in the Barcelona region [19]. Tobias and Molina [19] found that a 1°C increase in maximum temperature reduced the incidence rate by 7.5% on the same day. Holtman et al. [20] found that ambient temperature plays a significant role in the spread of COVID-19 by promoting the survival of the virus in the environment when temperatures are low. Wang et al. [14] reported that low temperature and low humidity significantly contributed to the transmission and survival of coronaviruses. For these authors, ‘strict public health strategies should be continued when temperature drops in most parts of the country so as to prevent reversal of the epidemic’. Coker et al. [15] found a negative association between temperature and COVID-19 mortality. In contrast, Sobral et al. [43] found no significant correlation between the COVID-19 mortality rates and temperature.
Finally, our study confirms and extends the results of previous studies concerning the impact of environmental factors on the COVID-19 mortality rate.
The long observation period of cumulative deaths due to the COVID-19, from March to December 2020, has indeed made it possible to highlight the influence of the duration and extent of the spread of the COVID-19 on most of the results of previous studies. Typically, the significant positive association between the COVID-19 mortality rate and long-term exposure to PM2.5 did not cease until 1 December 2020, while the relationship between the mean annual temperature and COVID-19 mortality rate did not appear until 1 November 2020. This last period coincided with what many specialists called the second wave of the pandemic, which was observed in several European countries (such as the UK, Germany, Spain, Belgium, Portugal, and Italy). This second wave gained momentum as the temperature gradually dropped, resulting in more deaths than the first wave. Future research with data from other countries is needed to evaluate the consistency of the relationships observed in France between COVID-19 mortality and environmental factors. Likewise, the results of our study encourage us to pursue investigations with individual data when they are available and publicly accessible.
Limitations
This study presents some inherent limitations to the ecological analysis, and our findings should be interpreted with caution due to some biases related to ecological data. First, within departments, long-term exposure to PM2.5 and COVID-19 deaths could vary from place to place, masking the heterogeneity within them. Second, the lack of individual data on COVID-19 deaths did not allow investigation of the precise long-term impact. In addition, the cross-sectional design of this study and the constraint of available data could also constitute limitations, as it is difficult to predict the evolution of the associations observed with time and the duration of the coronavirus pandemic itself. Furthermore, the COVID-19 pandemic is ongoing; hence, the study findings could change. Hence, the study results these should be considered intermediate results.