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Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example
The burden of vector-borne diseases (Dengue, Zika virus, yellow fever, etc.) gradually increased in the past decade across the globe. Mathematical modelling on infectious diseases helps to study the transmission dynamics of the pathogens. Theoretically, the diseases can be controlled and eventually...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049463/ https://www.ncbi.nlm.nih.gov/pubmed/32149023 http://dx.doi.org/10.7717/peerj.8601 |
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author | Zhao, Shi Musa, Salihu S. Hebert, Jay T. Cao, Peihua Ran, Jinjun Meng, Jiayi He, Daihai Qin, Jing |
author_facet | Zhao, Shi Musa, Salihu S. Hebert, Jay T. Cao, Peihua Ran, Jinjun Meng, Jiayi He, Daihai Qin, Jing |
author_sort | Zhao, Shi |
collection | PubMed |
description | The burden of vector-borne diseases (Dengue, Zika virus, yellow fever, etc.) gradually increased in the past decade across the globe. Mathematical modelling on infectious diseases helps to study the transmission dynamics of the pathogens. Theoretically, the diseases can be controlled and eventually eradicated by maintaining the effective reproduction number, ([Image: see text] ), strictly less than 1. We established a vector-host compartmental model, and derived ([Image: see text] ) for vector-borne diseases. The analytic form of the ([Image: see text] ) was found to be the product of the basic reproduction number and the geometric average of the susceptibilities of the host and vector populations. The ([Image: see text] ) formula was demonstrated to be consistent with the estimates of the 2015–2016 yellow fever outbreak in Luanda, and distinguished the second minor epidemic wave. For those using the compartmental model to study the vector-borne infectious disease epidemics, we further remark that it is important to be aware of whether one or two generations is considered for the transition “from host to vector to host” in reproduction number calculation. |
format | Online Article Text |
id | pubmed-7049463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70494632020-03-06 Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example Zhao, Shi Musa, Salihu S. Hebert, Jay T. Cao, Peihua Ran, Jinjun Meng, Jiayi He, Daihai Qin, Jing PeerJ Mathematical Biology The burden of vector-borne diseases (Dengue, Zika virus, yellow fever, etc.) gradually increased in the past decade across the globe. Mathematical modelling on infectious diseases helps to study the transmission dynamics of the pathogens. Theoretically, the diseases can be controlled and eventually eradicated by maintaining the effective reproduction number, ([Image: see text] ), strictly less than 1. We established a vector-host compartmental model, and derived ([Image: see text] ) for vector-borne diseases. The analytic form of the ([Image: see text] ) was found to be the product of the basic reproduction number and the geometric average of the susceptibilities of the host and vector populations. The ([Image: see text] ) formula was demonstrated to be consistent with the estimates of the 2015–2016 yellow fever outbreak in Luanda, and distinguished the second minor epidemic wave. For those using the compartmental model to study the vector-borne infectious disease epidemics, we further remark that it is important to be aware of whether one or two generations is considered for the transition “from host to vector to host” in reproduction number calculation. PeerJ Inc. 2020-02-27 /pmc/articles/PMC7049463/ /pubmed/32149023 http://dx.doi.org/10.7717/peerj.8601 Text en ©2020 Zhao et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Mathematical Biology Zhao, Shi Musa, Salihu S. Hebert, Jay T. Cao, Peihua Ran, Jinjun Meng, Jiayi He, Daihai Qin, Jing Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title | Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title_full | Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title_fullStr | Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title_full_unstemmed | Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title_short | Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example |
title_sort | modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in luanda, angola 2015–2016 as an example |
topic | Mathematical Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049463/ https://www.ncbi.nlm.nih.gov/pubmed/32149023 http://dx.doi.org/10.7717/peerj.8601 |
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