What Impact Will Worsening Air Pollution Have on the Burden of Covid-19?

Background: Evidence suggests association between long-term exposure to air pollutants and increased risk of becoming infected with SARS-CoV- 2, the causative agent of COVID-19, and increased severity of COVID-19. However, it remains unclear whether breathing more polluted air over many years affects susceptibility to infection or only affects disease severity, with uncertainty around the intensity of these associations. It has been estimated that anthropogenic emissions have contributed to over 10% of the over 660 million cases of SARS-CoV-2 and the over 7.5 million COVID-19 deaths reported worldwide over the course of the pandemic. Furthermore, as the world continues to warm and if air pollution levels increase, then so might the burden of respiratory infectious disease, including COVID-19. Method(s): Here we explore the potential impact of long-term exposure to increasing levels of particulate matter 2.5 microns or less in diameter (PM2.5) (+1 to +5 mug/m3) assuming an association on either (1) SARS-CoV-2 susceptibility or (2) COVID-19 disease severity by projecting SARS-CoV-2 infections and COVID-19-related hospital admissions over a two-year period. Simulations were conducted using a SARS-CoV-2 transmission model in a global setting capturing age and comorbidity risk, considering seasonality, emerging variants, and vaccination and treatment options. We model linear, log, and log10 relationships between these associations. Result(s): We show that if long-term exposure to higher levels of air pollution only affects COVID-19 severity, then as expected, the projected number of COVID-19-related hospitalisations would proportionally increase. However, if exposure directly affects the susceptibility of becoming infected, then while infections would be higher, hospitalizations would also be even higher due to the potential for onward transmission. This aligns with associations between air pollution and other respiratory infections and their associated health outcomes. Conclusion(s): The anticipated additional impact air pollution is having on the public health burden of respiratory infectious disease, like COVID-19, should be considered in strategic action plans to mitigate and adapt to changing levels of air pollution. It is important to better understand at which point air pollution affects SARS-CoV-2 infection acquisition through to disease progression, to enable improved protection and to better support those most vulnerable. Modelled impact of air pollution on COVID-19. The projected cumulative impact of long-term exposure to incrementally higher PM2.5 levels (+1 to +5 mug/m3) affecting either SARS-CoV-2 susceptibility or COVID-19 disease severity on cumulative SARS-CoV-2 infections and COVID-19-related hospital admissions over a two-year period in a global setting of 100,000 people. Age and comorbidity risk are captured, seasonality considered, and it is assumed SARS-CoV-2 variants of concern (with 10% more infectious and 20% more immune-evading than the previous variant, and Omicron-level severity) emerge every six months, and COVID-19 vaccination and treatment (monoclonalantibody PrEP and antivirals) are implemented for all those eligible. While the associations between PM2.5 exposure and either SARS-CoV-2 susceptibility or COVID-19 disease severity remains unclear and there is much uncertainty around estimated assumptions, here we show a modelled log10 relationship between these two potential associations. COVID-19: coronavirus disease 2019. PM2.5: particulate matter 2.5 microns or less in diameter. PrEP: pre-exposure prophylaxis. SARS-CoV-2: severe acute respiratory syndrome coronavirus 2.

Depression trajectories during the COVID-19 pandemic in the high-quality health care setting of Switzerland: the COVCO-Basel cohort.

OBJECTIVES: During the pandemic, Switzerland avoided stringent lockdowns and provided funds to stabilize the economy. To assess whether and in what subgroups the pandemic impacted on depressive symptoms in this specific Swiss context, we derived depression trajectories over an extended pandemic period in a Swiss cohort and related them to individuals' sociodemographic characteristics. STUDY DESIGN: This was a population-based cohort study. METHODS: The population-based COVCO-Basel cohort in North-Western Switzerland invited 112,848 adult residents of whom 12,724 participated at baseline. Between July 2020 and December 2021, 6396 participants answered to additional 18 monthly online questionnaires. Depression symptoms were repeatedly measured by the DASS-21 scale. Group-based Trajectory Models methods were applied to identify clusters of similar depression trajectories. Trajectory clusters were characterized descriptively and with a Multinomial response model. RESULTS: Three distinct trajectories were identified. The 'Highly affected' trajectory (13%) had a larger presence of younger and female participants with lower average income, higher levels of past depression, and living alone. A majority of individuals in the 'Unaffected' trajectory (52%) were of medium or high average income, older average age, without previous depression symptoms, and not living alone. The 'Moderately affected' trajectory (35%) had a composition intermediate between the two opposite 'extreme' trajectories. CONCLUSIONS: This study is among few studies investigating depression trajectories up to the time when COVID-19 vaccination was readily available to the entire population. During these 18 months of the pandemic, depressive symptoms increased in a substantial percentage of participants. Economic support, high-quality health care system, and moderate containment measures did not sufficiently protect all population subgroups from adverse, potentially long-term psychological pandemic impacts.