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 mo...
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| Format: | Article |
| Language: | English |
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Elsevier
2022
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| Online Access: | https://doi.org/10.1016/j.waojou.2021.100555 http://hdl.handle.net/11408/4686 |
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| 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 | DSpace |
| 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 | Article |
| id | ir-11408-4686 |
| institution | My University |
| language | English |
| publishDate | 2022 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | ir-11408-46862022-06-27T13:49:07Z 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 Food allergy Inhalant allergy Mathematical model 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 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. 2022-03-11T14:17:46Z 2022-03-11T14:17:46Z 2021 Article 1939-4551 https://doi.org/10.1016/j.waojou.2021.100555 http://hdl.handle.net/11408/4686 en World Allergy Organization Journal;Vol. 2; No. 7 open Elsevier |
| spellingShingle | Food allergy Inhalant allergy Mathematical model Zimbabwe 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 | Food allergy Inhalant allergy Mathematical model Zimbabwe |
| url | https://doi.org/10.1016/j.waojou.2021.100555 http://hdl.handle.net/11408/4686 |
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