The other day I got an emergency call from my friend who was on holiday with his family in Ooty his sister aged about 21 was moving into a beautiful garden full of flowers around 4 PM and suddenly fainted after a series of sneezing continuously for 6 to 7 minutes.
The face became so red and there was itching all over the body a runny nose, breathlessness, red eyes, and disturbed highly. He wanted me to get some treatment online. Immediately I told him to move her from that garden expecting there might be some pollen from the flowers or trees that might have caused an allergy to his sister. However, I also suggested anti-allergic medication. It is a surprise to note that the moment she left that garden and came away to their resort she became completely normal. This episode we call pollen allergy.
Pollen allergy sufferers: Impact of air pollution on Asthma and Rhinitis approach has been demonstrated by a project called Global Alliance against Chronic Respiratory Diseases – Prediction of interactions between air pollution and allergen exposure. Accordingly, this review analyzes the state and recent progress in the field of information support for pollen allergy sufferers.
For decades, information available for patients and allergologists consisted of pollen counts, which are vital but insufficient. New technology paves the way for a substantial increase in the amount and diversity of the data. Novel data came to light to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index.
This new index is available in an app (Mobile Airways Sentinel Network-air) that was developed in the frame of the European Union grant Impact of Air Pollution on Sleep, Asthma and Rhinitis (a project of the European Institute of Innovation and Technology-Health). The ongoing transformation of pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions.
The new information technology and artificial intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.
Depending on the quality of the recognition algorithm, the information on the flying particle could be derived almost immediately with uncertainty approaching 20% to 30% or less depending on the taxon. The pollen identification with all devices is based on manually collected and classified reference data sets and requires continuous manual correction and enrichment.
Debatably, the main problem of all devices with reasonable pollen recognition ability is their very high price. Other challenges include yet-to-mature quality control procedures, device comparability even within a single type or brand, and difficulties with identification of the “reference” pollen characteristics for every genus, and species.
The first operational multi-species pollen observational network was set in operation in Bavaria (Germany) equipped with the BAA500 devices. Since spring 2019, it has provided 3-hourly data from eight monitoring locations. Also, in 2019, two Rapid-E devices were put into operation in Serbia and Croatia
That network is being extended in 2020 with the Rapid-E monitor in Lithuania and Rapid-E and Poleno devices in Finland. The geographical distribution of automatic pollen monitors as well as manual counters over the globe has been recently reviewed. This sort of technology to help the sufferers of pollen in India is not easily accessible to people and perhaps is limited to research labs.
Meteorological data and numerical models: Meteorological conditions are a vital driver of plant phenology, with the flowering period being the key phase. Phenology refers to the study of seasonal changes in plants and animals and their relationship to weather and climate. The most widely used and also the oldest concept is the heat-sum-based approach, which computes the amount of heat accumulated by the plants since the beginning of the growth season.
The developments suggested a nearly linear relation between “appropriately computed” heat sum and the stage of the flowering season. Such models were shown to predict the onset of the flowering season within a few days of accuracy, about a week in advance. However, the pollen season depends on pollen long-range transport, which sometimes can make it dramatically different from the local flowering period.
Accounting for the pollen release from inflorescences and subsequent transport in the atmosphere requires numerical models, which compute the whole lifecycle of pollen: maturation and presentation, release into the air, atmospheric transport and transformations, and deposition. Such models currently can predict concentrations of up to six pollen types for up to 5 days for the whole of Europe. perform high-resolution forecasts with grid-cell sizes of 1 and 2.5 km, respectively. The diversity of vegetation across the continents and the severe lack of available observational data so far preclude the development of hemispheric and global pollen dispersion models. Solutions to prevent allergy to pollen are on the way on a larger scale. Hoping to get an immediate remedy for many sufferers of this disorder.
