Evidence map›Paper›PMID 34257796›Full record

ArticleThe World Allergy Organization journal2021

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

Caroline Mushayi, Farai Nyabadza, Esther Chigidi, Hope Mataramvura, Lorraine Pfavayi, Simbarashe Rusakaniko, Elopy Nimele Sibanda

Open access · goldAbstract read
In one paragraph

Article in The World Allergy Organization journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Modeling COVID-19 infection in high-risk settings and low-risk settings.Physics and chemistry of the earth (2002) · 2022
    Article
  2. Modelling COVID-19 infection with seasonality in Zimbabwe.Physics and chemistry of the earth (2002) · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Caroline MushayiMidlands State University, Department of Mathematics, Senga Road, Gweru, Zimbabwe.
Farai NyabadzaUniversity of Johannesburg, Department of Mathematics and Applied Mathematics, Auckland Park, Johannesburg, 2006, South Africa.
Esther ChigidiMidlands State University, Department of Mathematics, Senga Road, Gweru, Zimbabwe.
Hope MataramvuraAsthma, Allergy and Immune Dysfunction Clinic, 113 Kwame Nkrumah Ave., Harare, Zimbabwe.
Lorraine PfavayiAsthma, Allergy and Immune Dysfunction Clinic, 113 Kwame Nkrumah Ave., Harare, Zimbabwe.
Simbarashe RusakanikoUniversity of Zimbabwe, College of Health Sciences, Department of Community Medicine, Avondale, Harare, Zimbabwe.
Elopy Nimele SibandaAsthma, Allergy and Immune Dysfunction Clinic, 113 Kwame Nkrumah Ave., Harare, Zimbabwe.
Midlands State University · ZWNational University of Science and Technology · ZWUniversity of Zimbabwe · ZWUniversity of Johannesburg · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodWe 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.

resultsThe 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.

conclusionOur 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.

Indexed as

Food allergyInhalant allergyMathematical modelZimbabwe

Identifiers

PMID34257796
PMCPMC8246639
OpenAlexW3173368452

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.