As our climate continues to change, pollen seasons are becoming stronger and longer, impacting allergy sufferers more than ever. Luckily, advancements in pollen monitoring, powered by new methods of sophisticated modeling and big data, have enabled major breakthroughs in pollen tracking.
Let’s explore how new forms of pollen data can be used by allergy companies and service providers to enhance and personalize offerings in ways never before possible.
Let’s Define Pollen Data
Before we talk about the data, let’s first ask the question, what is pollen?
Plants release pollen grains, which look like a tiny, yellowish powder, as part of their reproductive mechanism. Pollen particles are then carried by the wind or spread via insects. Unfortunately, because they’re so small, pollen grains can enter human airways and impact our health; some seasonal allergy sufferers can even experience irritated skin reactions.
How is Pollen Traditionally Measured?
Traditional pollen monitoring involves manual pollen traps – mechanisms with hot air blowing on sticky film strips that capture pollen grains floating in the air. Strips are later removed and examined under a microscope to count the grains and provide a report.
What Do Free Pollen Databases Offer?
Free pollen databases exist in some capacity online, such as the European Pollen Records. Here you can find databases of fossil and modern pollen records for biogeography and ecosystem conservation studies. While useful, these free pollen databases do not provide reliable, granular, or live information, limiting their value when it comes to proactive decision-making.
Traditional Pollen Monitoring VS. Big Data Pollen Reporting
Due to the highly manual nature of traditional pollen tracking, many sources of pollen data are limited: there are often delays in reporting and a massive gap exists in terms of coverage, as pollen trap stations can only report according to the trap’s physical location. It’s also difficult to forecast changes with traditional pollen monitoring methods as they only report on the past. (Learn more about the limitations of traditional pollen tracking methods here)
BreezoMeter applies a more modern approach to pollen measurement which moves beyond manual-only measurements. To deliver accurate and timely pollen information, we move beyond monitoring station information and regional models by incorporating more types of data sources and applying sophisticated modeling: In addition to traditional pollen stations, we layer this information with information about pollen emission schedules, vegetation land covers, and climate and weather conditions – all of which serve to inform the accuracy of our pollen forecasting models.
Using a health-focused global pollen index, BreezoMeter provides daily pollen forecast information alongside location-based insights which can be personalized to individual sensitivity groups (read our pollen monitoring technology guide to learn more).
Amazing Use Cases for Timely Pollen Data
Accurate pollen forecast information can be used to help allergy sufferers limit allergic reactions by enabling them to optimize medication use, choose ideal times and the cleanest routes for outdoor activities, and keep indoor spaces as pollen-free as possible. For companies providing allergy services, personalized pollen data enables improved supply management and demand planning, can be used to inform market analysis, identify consumer trends, and ensure targeted marketing campaign messaging and ads are as effective as possible.
1. Location-based Insights: Accurate Pollen Count Reports for Every 1 KM
Newly available pollen data offers more granular forecasts than ever. Companies can leverage this dynamic and highly-localized pollen information to drive their personalization strategies, delivering actionable pollen insights based on a specific geolocation.
Organizations and businesses delivering these alerts can choose to notify only those they’ve identified to be sensitive to specific plant pollen in their vicinity. This improved targeting helps build trust by demonstrating specific value and not disturbing an individual needlessly.
2. What’s the Poison: Tree, Weed, or Grass?
The seasonality of different plant pollen types is not the same and neither are the local environments and terrains in which different plant types grow.
Breaking down local pollen data into 3 main plant-type categories ensures continuous coverage across the different weed, tree, and grass pollen seasons and their impacted regions all year round.
3. Mapping Sensitivities to Specific Plant Species
Pollen is not a one-size-fits-all allergen. The same pollen grains can affect different allergy sufferers in diverse ways; reactions can change according to plant type and species.
BreezoMeter categorizes pollen data from 15 different plant species, including Oak, Hazel, Elm, Ragweed, and Graminales. Detailing specific pollen species in the air enables allergy companies to map out personal triggers and personalize insights based on individual sensitivities in the most affected regions at the most relevant times.
For example, allergy sufferers around parts of Arizona and New Mexico are in the middle of peak tree pollen season at the time of writing, and Juniper can be clearly identified as the biggest local allergen:
Pollen heatmap, Arizona-New Mexico Region, 03.28.22
4. Personalized Pollen Insights & Recommendations
By leveraging geolocation and personal sensitivity records in conjunction with pollen data, companies can deliver health-focused alerts and recommendations based on the specific needs and environment of an individual allergy sufferer: from alerts to take medication before increases in specific pollen species to informing allergy sufferers when allergy risk is low so they can enjoy outdoor activities.
The global pharmaceutical brand ALK does exactly this with BreezoMeter’s pollen data, considerably enhancing engagement with their allergy companion app. After improving user engagement with timely pollen insights and an in-app education center, they managed to reduce app churn rate by 50%. (Read the full case study here)
5. Historical Pollen Data for Correlation Studies
Historical pollen data trends enable market analysts to correlate changes in pollen counts at specific regions and times with consumer trends such as buying patterns and medication-demand. Allergy companies can capitalize on these discovered patterns in different ways, such as informing demand planning strategies and focusing targeted their products and messaging at the most relevant, affected individuals.
Historical pollen data can also be correlated with patient data to identify which pollen types and climate conditions produce the most symptoms and hospitalization/patient care. Healthcare providers can then reduce costs by informing vulnerable patients in impacted areas of their personal risks at the right times, thus lowering the rates of doctor visits.
Allergy therapeutic companies can also use personalized historical pollen data to reveal insights into individual sensitivities of consumers and tailor new treatments and health recommendations to their specific needs. (Check out our History Plus product to learn more).
6. Pollen Data Daily Forecasts for Informed Travel
Accurate multiple-day pollen forecasts can be used to enhance the offerings of allergy companion apps, providing more long-term value to the user and enabling them to adopt healthier lifestyle habits and improve daily and weekly travel planning for holidays, trips, or even work purposes. BreezoMeter currently provides 5-day pollen forecasts in over 65 countries worldwide.
The fitness and travel pioneer All Trails has made hiking more accessible by integrating BreezoMeter’s pollen data with their app, creating a new feature that provides subscribers with daily pollen forecasts as a map overlay for US and European regions.
Air quality overlay in the AllTrails app (Image originally featured on alltrails.com)
7. Pollen Data As a Climate Proxy
Pollen production depends greatly on climate, which impacts annual growing seasons. In this sense, granular and timely pollen data over time can be used to study climate change impact. By studying the relationship between climate and pollen trends over time, researchers can extrapolate insights and better inform prediction models.
8. Mapping Personal Symptoms & Local Sources
Companies can correlate pollen data with experienced symptoms to create personal risk metrics, adding value to their products and educating allergy sufferers on which pollen types trigger worse reactions for them. Pollen data also enables in-depth research into hospitalization peaks to identify health trends in correlation with local surroundings.
Digital health and therapeutics leader Propeller Health transforms the lives of asthma and COPD patients, by reducing hospitalization by 57% and inhaler use by 84% while increasing symptom-free days. Partly they do this by integrating pollen data (in addition to air quality) with their connected inhaler app, so users can gain insights into personal triggers. (Read the full case study here)
Thinking About Pollen Data? You Should Be…
The CDC warns that the growing impact of climate change may cause more people to suffer the health impact of pollen: In North America alone, climate change has made pollen seasons roughly 20 days longer and 21% stronger than a few decades ago.
New research predicts warmer temperatures will make US spring allergy seasons start even earlier, while rising CO2 levels may increase pollen emissions by up to 200% this century.
Pollen data and insights have become crucial for the allergy treatment and management industries and can be used by companies in this space to meet the demand for personalization in health, remain competitive in an ever-changing market, and pinpoint their messaging and targeting.
