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Assessing the eDPSEEA model in seasonal pollen induced asthma in Islamabad

Population Size

Not reported

Years

2019 - 2021

Associated BioSamples

Availability to be confirmed

Geographic coverage

Pakistan

Lead time

Other

Summary

This project aims to assess the feasibility of using the eDPSEEA model in predicting the shedding of paper mulberry pollen which may cause acute asthma.

Documentation

The eDPSEEA model (ecosystems-enriched Drivers, Pressures, State, Exposure, Effects, Actions) is a conceptual framework for an integrated assessment of human and ecosystem health, which facilitates an understanding and prediction of complex human-environment and ecosystem interactions.

This project aims to assess the feasibility of using the eDPSEEA model in predicting the shedding of paper mulberry pollen which may cause acute asthma, by collecting pollen data and correlating it with weather and other parameters; while also studying a cohort of sensitised vs non-sensitised asthma patients, and their response to pollen allergens. A modelling exercise in collaboration with German scientists, will help to devise the prediction model, to predict pollen shedding and dispersal up to 3 days prior to the event. This is important to allow patients and other stakeholders to plan for an impending peak of pollen allergy and it’s subsequent associated complications.

The outcome of this project will help to use the eDPSEEA model in other countries as well, as it is currently being used in Malaysia too.

For further information, see: https://www.ed.ac.uk/usher/respire/chronic-respiratory-disorders/seasonal-pollen-induced-asthma

Dataset type
Health and disease
Dataset sub-type
Not applicable

Keywords

Asthma, Pollen, BREATHE, RESPIRE, Pakistan

Observations

Observed Node
Disambiguating Description
Measured Value
Measured Property
Observation Date

Findings

1

Count

28 Feb 2021

Provenance

Image contrast
Not stated
Biological sample availability
Availability to be confirmed

Details

Publishing frequency
Static
Version
6.0.0
Modified

08/10/2024

Citation Requirements
RESPIRE Collaboration

Coverage

Start date

01/09/2019

End date

28/02/2021

Time lag
Not applicable
Geographic coverage
Pakistan
Minimum age range
18
Maximum age range
150

Accessibility

Language
en
Controlled vocabulary
LOCAL
Format
text

Data Access Request

Dataset pipeline status
Not available
Time to dataset access
Other
Access method category
Varies based on project
Access service description
Access is managed on a project-by-project basis. Please contact the RESPIRE team.
Jurisdiction
PK
Data Controller
RESPIRE
Data Processor
RESPIRE

Dataset Types: Health and disease


Collection Sources: