Cargando…

A mathematical model for the prediction of the prevalence of allergies in Zimbabwe

BACKGROUND: The prevalence of allergies has been observed to be increasing in the past years in Zimbabwe. It is thus important to consider the long term prevalence of allergies. Our interest is in investigating the trends of allergies in the next 2 decades. METHOD: We formulate a deterministic model...

Descripción completa

Detalles Bibliográficos
Autores principales: Mushayi, Caroline, Nyabadza, Farai, Chigidi, Esther, Mataramvura, Hope, Pfavayi, Lorraine, Rusakaniko, Simbarashe, Sibanda, Elopy Nimele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: World Allergy Organization 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246639/
https://www.ncbi.nlm.nih.gov/pubmed/34257796
http://dx.doi.org/10.1016/j.waojou.2021.100555
_version_ 1783716352326893568
author Mushayi, Caroline
Nyabadza, Farai
Chigidi, Esther
Mataramvura, Hope
Pfavayi, Lorraine
Rusakaniko, Simbarashe
Sibanda, Elopy Nimele
author_facet Mushayi, Caroline
Nyabadza, Farai
Chigidi, Esther
Mataramvura, Hope
Pfavayi, Lorraine
Rusakaniko, Simbarashe
Sibanda, Elopy Nimele
author_sort Mushayi, Caroline
collection PubMed
description BACKGROUND: The prevalence of allergies has been observed to be increasing in the past years in Zimbabwe. It is thus important to consider the long term prevalence of allergies. Our interest is in investigating the trends of allergies in the next 2 decades. METHOD: We formulate a deterministic model with 6 compartments to predict the prevalence of allergies in Zimbabwe. The human population is divided into 4 distinct epidemiological, classes based on their exposure to 2 allergen groups (food and inhalants), represented by 2 compartments. The model is used to predict the prevalence of allergen sensitization. The number of human allergen groups in each compartment are tracked through a system of differential equations. Model parameters were obtained by fitting observed data to the model. Graphical solutions of the model were developed using Matlab and Excel. RESULTS: The rate of sensitisation to food allergen sources is found to be lower than the rate of sensitisation to inhalant allergens. The rate at which individuals develop tolerance to food allergen sources is found to be almost twice the rate of developing tolerance to inhalant allergies. The equilibrium solutions (the long-term states of the populations) of the model are found to be non-zero implying that there will never be an allergy-free population. Our results also show that the prevalence of food allergy is likely to increase in the next 2 decades while inhalant allergy prevalence is expected to decrease. CONCLUSION: Our long-term solutions show endemicity in allergies in Zimbabwe. So, allergy will be endemic in the Zimbabwean population; hence there is a need for allergy care and management facilities to be increased. These results are critical in policy development and planning around allergies in the near future.
format Online
Article
Text
id pubmed-8246639
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher World Allergy Organization
record_format MEDLINE/PubMed
spelling pubmed-82466392021-07-12 A mathematical model for the prediction of the prevalence of allergies in Zimbabwe Mushayi, Caroline Nyabadza, Farai Chigidi, Esther Mataramvura, Hope Pfavayi, Lorraine Rusakaniko, Simbarashe Sibanda, Elopy Nimele World Allergy Organ J Article BACKGROUND: The prevalence of allergies has been observed to be increasing in the past years in Zimbabwe. It is thus important to consider the long term prevalence of allergies. Our interest is in investigating the trends of allergies in the next 2 decades. METHOD: We formulate a deterministic model with 6 compartments to predict the prevalence of allergies in Zimbabwe. The human population is divided into 4 distinct epidemiological, classes based on their exposure to 2 allergen groups (food and inhalants), represented by 2 compartments. The model is used to predict the prevalence of allergen sensitization. The number of human allergen groups in each compartment are tracked through a system of differential equations. Model parameters were obtained by fitting observed data to the model. Graphical solutions of the model were developed using Matlab and Excel. RESULTS: The rate of sensitisation to food allergen sources is found to be lower than the rate of sensitisation to inhalant allergens. The rate at which individuals develop tolerance to food allergen sources is found to be almost twice the rate of developing tolerance to inhalant allergies. The equilibrium solutions (the long-term states of the populations) of the model are found to be non-zero implying that there will never be an allergy-free population. Our results also show that the prevalence of food allergy is likely to increase in the next 2 decades while inhalant allergy prevalence is expected to decrease. CONCLUSION: Our long-term solutions show endemicity in allergies in Zimbabwe. So, allergy will be endemic in the Zimbabwean population; hence there is a need for allergy care and management facilities to be increased. These results are critical in policy development and planning around allergies in the near future. World Allergy Organization 2021-06-25 /pmc/articles/PMC8246639/ /pubmed/34257796 http://dx.doi.org/10.1016/j.waojou.2021.100555 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Mushayi, Caroline
Nyabadza, Farai
Chigidi, Esther
Mataramvura, Hope
Pfavayi, Lorraine
Rusakaniko, Simbarashe
Sibanda, Elopy Nimele
A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title_full A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title_fullStr A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title_full_unstemmed A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title_short A mathematical model for the prediction of the prevalence of allergies in Zimbabwe
title_sort mathematical model for the prediction of the prevalence of allergies in zimbabwe
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8246639/
https://www.ncbi.nlm.nih.gov/pubmed/34257796
http://dx.doi.org/10.1016/j.waojou.2021.100555
work_keys_str_mv AT mushayicaroline amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT nyabadzafarai amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT chigidiesther amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT mataramvurahope amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT pfavayilorraine amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT rusakanikosimbarashe amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT sibandaelopynimele amathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT mushayicaroline mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT nyabadzafarai mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT chigidiesther mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT mataramvurahope mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT pfavayilorraine mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT rusakanikosimbarashe mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe
AT sibandaelopynimele mathematicalmodelforthepredictionoftheprevalenceofallergiesinzimbabwe