Competing Bioaerosols May Influence the Seasonality of Influenza-Like Illnesses, including COVID-19. The Chicago Experience

Editorial for the Topical Collection "SARS-CoV-2 Infection and COVID-19 Disease"

A previously unknown coronavirus, named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in the city of Wuhan, China, in December 2019 [...].

Common Pollen Modulate Immune Responses against Viral-Like Challenges in Airway Coculture Model

Recent research indicates that exposure to pollen increases the risk and severity of respiratory infections, while studies also suggest that it may possess a protective function. Our aim was to investigate how exposure to common pollen modifies airway cells' responses to viral- or bacterial-like challenges and vice versa. Cocultured A549 and THP-1 cells were exposed to three doses of four different pollens (Alnus glutinosa, Betula pendula, Phleum pratense, or Ambrosia artemisiifolia) and subsequently to Toll-like receptor (TLR) ligands mimicking bacterial and viral challenges (TLR3, TLR4, TLR7/8). The stimulation experiment was replicated in reverse order. Toxicological and immunological end points were analyzed. When cells were primed with pollen, especially with grass (P. pratense) or weed (A. artemisiifolia), the ability of cells to secrete cytokines in response to bacterial- and viral-like exposure was decreased. In contrast, cells primed with viral ligand TLR7/8 showed greater cytokine responses against pollen than cells exposed to ligands or pollen alone. Our results suggest that pollen exposure potentially weakens immune reactions to bacterial- or viral-like challenges by modulating cytokine production. They also indicate that TLR7/8-mediated viral challenges could elicit exaggerated immune responses against pollen. Both mechanisms could contribute to the acceleration and complication of infections during the pollen season.

Exploring the interplay between climate, population immunity and SARS-CoV-2 transmission dynamics in Mediterranean countries

The relationship between SARS-CoV-2 transmission and environmental factors has been analyzed in numerous studies since the outbreak of the pandemic, resulting in heterogeneous results and conclusions. This may be due to differences in methodology, considered variables, confounding factors, studied periods and/or lack of adequate data. Furthermore, previous works have reported that the lack of population immunity is the fundamental driver in transmission dynamics and can mask the potential impact of environmental variables. In this study, we aimed to investigate the association between climate variables and COVID-19 transmission considering the influence of population immunity. We analyzed two different periods characterized by the absence of vaccination (low population immunity) and a high degree of vaccination (high level of population immunity), respectively. Although this study has some limitations, such us the restriction to a specific climatic zone and the omission of other environmental factors, our results indicate that transmission of SARS-CoV-2 may increase independently of temperature and specific humidity in periods with low levels of population immunity while a negative association is found under conditions with higher levels of population immunity in the analyzed regions.

A Review of the Role of Pollen in COVID-19 Infection

There is current interest in the role of ambient pollen in the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19) infection risk. The aim of this review is to summarise studies published up until January 2023 investigating the relationship between airborne pollen and the risk of COVID-19 infection. We found conflicting evidence, with some studies showing that pollen may increase the risk of COVID-19 infection by acting as a carrier, while others showed that pollen may reduce the risk by acting as an inhibiting factor. A few studies reported no evidence of an association between pollen and the risk of infection. A major limiting factor of this research is not being able to determine whether pollen contributed to the susceptibility to infection or just the expression of symptoms. Hence, more research is needed to better understand this highly complex relationship. Future investigations should consider individual and sociodemographic factors as potential effect modifiers when investigating these associations. This knowledge will help to identify targeted interventions.

Pollen, respiratory viruses, and climate change: Synergistic effects on human health

In recent years, evidence of the synergistic effects of pollen and viruses on respiratory health has begun to accumulate. Pollen exposure is a known risk factor for the incidence and severity of respiratory viral infections. However, recent evidence suggests that pollen exposure may also inhibit or weaken viral infections. A comprehensive summary has not been made and a consensus on the synergistic health effects has not been reached. It is highly possible that climate change will increase the significance of pollen exposure as a cause of respiratory problems and, at the same time, affect the risk of infectious disease outbreaks. It is important to accurately assess how these two factors affect human health separately and concurrently. In this review article, for the first time, the data from previous studies are combined and reviewed and potential research gaps concerning the synergistic effects of pollen and viral exposure are identified.

Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China

This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM_2.5 ), particulate matter 10 (PM₁₀ ), sulphur dioxide (SO₂ ), nitrogen dioxide (NO₂ ), and carbon monoxide (CO), and a low concentration of ozone (O₃ ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM₁₀ , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China

Existing studies reported higher altitudes reduce the COVID-19 infection rate in the United States, Colombia, and Peru. However, the underlying reasons for this phenomenon remain unclear. In this study, regression analysis and mediating effect model were used in a combination to explore the altitudes relation with the pattern of transmission under their correlation factors. The preliminary linear regression analysis indicated a negative correlation between altitudes and COVID-19 infection in China. In contrast to environmental factors from low-altitude regions (<1500 m), high-altitude regions (>1500 m) exhibited lower PM2.5, average temperature (AT), and mobility, accompanied by high SO2 and absolute humidity (AH). Non-linear regression analysis further revealed that COVID-19 confirmed cases had a positive correlation with mobility, AH, and AT, whereas negatively correlated with SO2, CO, and DTR. Subsequent mediating effect model with altitude-correlated factors, such as mobility, AT, AH, DTR and SO2, suffice to discriminate the COVID-19 infection rate between low- and high-altitude regions. The mentioned evidence advance our understanding of the altitude-mediated COVID-19 transmission mechanism.

Environmental factors and mobility predict COVID-19 seasonality in the Netherlands

BACKGROUND

We recently showed that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands. We hypothesize that in The Netherlands the same environmental factors and mobility trends that are associated with the seasonality of flu-like illnesses are predictors of COVID-19 seasonality as well.

METHODS

We used meteorological, pollen/hay fever and mobility data from the Netherlands. For the reproduction number of COVID-19 (R_t), we used daily estimates from the Dutch State Institute for Public Health. For all datasets, we selected the overlapping period of COVID-19 and the first allergy season: from February 17, 2020 till September 21, 2020 (n = 218). Backward stepwise multiple linear regression was used to develop an environmental prediction model of the R_t of COVID-19. Next, we studied whether adding mobility trends to an environmental model improved the predictive power.

RESULTS

Through stepwise backward multiple linear regression four highly significant (p < 0.01) predictive factors are selected in our combined model: temperature, solar radiation, hay fever incidence, and mobility to indoor recreation locations. Our combined model explains 87.5% of the variance of R_t of COVID-19 and has a good and highly significant fit: F(4, 213) = 374.2, p < 0.00001. This model had a better overall predictive performance than a solely environmental model, which explains 77.3% of the variance of R_t (F(4, 213) = 181.3, p < 0.00001).

CONCLUSIONS

We conclude that the combined mobility and environmental model can adequately predict the seasonality of COVID-19 in a country with a temperate climate like the Netherlands. In this model higher solar radiation, higher temperature and hay fever are related to lower COVID-19 reproduction, and higher mobility to indoor recreation locations is related to an increased COVID-19 spread.