Allergic respiratory diseases resembling allergic rhinitis and asthma are considered adversarial effects of climate change on human health. The underlying mechanism liable for this association is the rise in atmospheric carbon dioxide (CO₂) and air temperature, which affects airborne allergens resembling fungal spores and pollen.

A recent eBioMedicine review explores three translational mitigation approaches to help in improved health outcomes.

Study: Climate change, airborne allergens, and three translational mitigation approaches. Image Credit: 24Novembers / Shutterstock.com

Background

The warming of the Earth’s atmosphere is going on at an unprecedented rate and is basically being driven by greenhouse gas emissions from human activities. The worldwide CO₂ concentration increased to 414.71 parts per million (ppm) in 2021 as in comparison with pre-industrial levels of about 280 ppm. These changes are impacting biological, physical, and human systems. 

Climate change affects airborne allergens and subsequently impacts allergic respiratory diseases, resembling allergic rhinitis and allergic asthma. In lots of countries and regions, these diseases already pose serious public health challenges, with asthma affecting at the least 30 million children and young adults in Europe and greater than 350 million people worldwide.

About this study

This current review discusses the impacts of climate change on airborne allergens and respiratory diseases.

To this end, three translational mitigation approaches that might improve health outcomes were assessed. These approaches included automated real-time airborne allergen monitoring, smartphone apps for reducing the adversarial impacts of airborne allergens, and airborne allergen forecasting and modeling.

Searches were conducted on MEDLINE, Web of Science, Current Contents, PubMed, and references from relevant articles to acquire data. Various search terms were used, resembling “fungal spore,” “mold spore,” “mold spore,” “climate change,” “allergy,” and “pollen.” Reports from meetings and abstracts were excluded, and only articles published in English between 2000 and 2022 were included. 

Key insights

Automatic and stand-alone instruments providing aeroallergen concentrations at high temporal resolution are currently available and aid in the gathering of data for all users and improve aeroallergen forecast accuracy. In comparison with previously available manual technologies, automatic data are more robust and essential to detect signal changes and evaluate future trends.

As a result of these recent developments, research on aeroallergens has rapidly progressed. Modern technology could change the understanding of aerobiological processes and make high-quality information available for the good thing about specialists.

Modeling and forecasting approaches for aeroallergens are also rapidly developing, particularly due to recent advances in machine learning. These models are the most-comprehensive tools available to research and forecast pollen concentrations at continental-to-regional scales. Nonetheless, extension to fungal spores is yet to realize maturity.

Maintaining their skills inside a changing environment stays a substantial challenge facing bioaerosol models concerning climate change. Statistical models quickly grow to be obsolete, and trajectory models don’t include vegetation-related modules.

The transition from classical Hirst-trap-based pollen observations to recent real-time monitoring technology is the brand new frontier in model development. This is predicted to extend the role of models as the first source of aerobiological information.

For respiratory conditions that require day by day self-management, cell phone apps are considered effective tools for symptom tracking, supporting health education, and ensuring adherence to treatment. A brand new generation of app-based services combining clinical, educational, and each real-time and forecast information is emerging.

Apps are promising avenues for sustained improvement within the diagnosis of specific sensitivities and personalized management options. A major advance that may be supported by mobile app data is the generation and sharing of knowledge on short-term forecasts of pollen and allergy risk.

Mobile app-supported healthcare can reduce the social burden of illness and improve quality of life. Nonetheless, this requires further refinement of high-quality personalized information, including timely detection of airborne allergens.

Conclusions

Climate change continues to affect airborne allergens significantly. While further research on this association is required, it’s crucial that these diseases be higher managed to avoid harmful exposures and improve health outcomes.

The present technological revolution can greatly assist in achieving this goal. Some novel approaches which will support this endeavor include automated real-time allergen monitoring, smartphone apps to cut back the health impacts of airborne allergens, and airborne allergen forecasting and modeling.