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Assessing the eDPSEEA model in seasonal pollen induced asthma in Islamabad

Population Size

Not reported
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Years

2019 - 2021

Years statistic card

Associated BioSamples

Availability to be confirmed

Associated BioSamples statistic card

Geographic coverage

Pakistan

Geographic coverage statistic card

Lead time

Other

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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

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:

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