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Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases
According to the information reflected by Anhui Center for Disease Control (Anhui CDC) in Hefei, Anhui province of China, some patients infected with respiratory diseases did not seek medical treatment (nonclinic visits) due to their strong resistance, and the influence of them on the spread of resp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281825/ https://www.ncbi.nlm.nih.gov/pubmed/32565884 http://dx.doi.org/10.1155/2020/8049631 |
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author | Bao, Yunting Xu, Yanlong Qi, Longxing Zhai, Sulan |
author_facet | Bao, Yunting Xu, Yanlong Qi, Longxing Zhai, Sulan |
author_sort | Bao, Yunting |
collection | PubMed |
description | According to the information reflected by Anhui Center for Disease Control (Anhui CDC) in Hefei, Anhui province of China, some patients infected with respiratory diseases did not seek medical treatment (nonclinic visits) due to their strong resistance, and the influence of them on the spread of respiratory diseases has not been known. A SIS model with considering the nonclinic visits was established; a qualitative theory of the model was analyzed to obtain the basic reproduction number R(0), disease-free equilibrium, endemic equilibrium, and stability of two equilibriums. Then, the model is combined with the daily number of respiratory diseases for parameter estimation and numerical simulation. Numerical simulation results showed that respiratory diseases were easy to break out in the autumn and winter and were relatively stable in the spring and summer. Through parameter estimation, the unknown parameter value was achieved and the result was obtained that the initial number of nonclinic visits is 10-11 times that of clinic visits. Finally, the result of sensitivity analysis displayed that the proportion of the number of nonclinic visits to the total number of patients has a significant influence on the final number of patients. If persons improve their resistance so that the number of nonclinic visits increases, the total number of patients will be reduced or even reduced to zero. Besides, reducing contact infection rate of disease and increasing the cure rate can also reduce the final total number of patients. |
format | Online Article Text |
id | pubmed-7281825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-72818252020-06-20 Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases Bao, Yunting Xu, Yanlong Qi, Longxing Zhai, Sulan Comput Math Methods Med Research Article According to the information reflected by Anhui Center for Disease Control (Anhui CDC) in Hefei, Anhui province of China, some patients infected with respiratory diseases did not seek medical treatment (nonclinic visits) due to their strong resistance, and the influence of them on the spread of respiratory diseases has not been known. A SIS model with considering the nonclinic visits was established; a qualitative theory of the model was analyzed to obtain the basic reproduction number R(0), disease-free equilibrium, endemic equilibrium, and stability of two equilibriums. Then, the model is combined with the daily number of respiratory diseases for parameter estimation and numerical simulation. Numerical simulation results showed that respiratory diseases were easy to break out in the autumn and winter and were relatively stable in the spring and summer. Through parameter estimation, the unknown parameter value was achieved and the result was obtained that the initial number of nonclinic visits is 10-11 times that of clinic visits. Finally, the result of sensitivity analysis displayed that the proportion of the number of nonclinic visits to the total number of patients has a significant influence on the final number of patients. If persons improve their resistance so that the number of nonclinic visits increases, the total number of patients will be reduced or even reduced to zero. Besides, reducing contact infection rate of disease and increasing the cure rate can also reduce the final total number of patients. Hindawi 2020-05-31 /pmc/articles/PMC7281825/ /pubmed/32565884 http://dx.doi.org/10.1155/2020/8049631 Text en Copyright © 2020 Yunting Bao et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Bao, Yunting Xu, Yanlong Qi, Longxing Zhai, Sulan Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title | Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title_full | Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title_fullStr | Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title_full_unstemmed | Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title_short | Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases |
title_sort | modeling the influence of nonclinic visits on the transmission of respiratory diseases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281825/ https://www.ncbi.nlm.nih.gov/pubmed/32565884 http://dx.doi.org/10.1155/2020/8049631 |
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