Download
peerj-8601.pdf 676,40KB
WeightNameValue
1000 Titel
  • Modelling the effective reproduction number of vector-borne diseases: the yellow fever outbreak in Luanda, Angola 2015–2016 as an example
1000 Autor/in
  1. Zhao, Shi |
  2. Musa, Salihu S. |
  3. Hebert, Jay T. |
  4. Cao, Peihua |
  5. Ran, Jinjun |
  6. Meng, Jiayi |
  7. He, Daihai |
  8. Qin, Jing |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-02-27
1000 Erschienen in
1000 Quellenangabe
  • 8:e8601
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.7717/peerj.8601 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7049463/ |
1000 Ergänzendes Material
  • https://peerj.com/articles/8601/#supplemental-information |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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, (Reff), strictly less than 1. We established a vector-host compartmental model, and derived (Reff) for vector-borne diseases. The analytic form of the (Reff) 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 (Reff) 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.
1000 Sacherschließung
lokal Reproduction number
lokal Luanda
lokal Mathematical modelling
lokal Vector-borne disease
lokal Angola
lokal Epidemic
lokal Yellow fever
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/WmhhbywgU2hp|https://frl.publisso.de/adhoc/uri/TXVzYSwgU2FsaWh1IFMu|https://frl.publisso.de/adhoc/uri/SGViZXJ0LCBKYXkgVC4=|https://frl.publisso.de/adhoc/uri/Q2FvLCBQZWlodWE=|https://frl.publisso.de/adhoc/uri/UmFuLCBKaW5qdW4=|https://frl.publisso.de/adhoc/uri/TWVuZywgSmlheWk=|https://frl.publisso.de/adhoc/uri/SGUsIERhaWhhaQ==|https://frl.publisso.de/adhoc/uri/UWluLCBKaW5n
1000 (Academic) Editor
1000 Label
1000 Förderer
  1. Hong Kong Polytechnic University |
1000 Fördernummer
  1. 1-ZE8J
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Hong Kong Polytechnic University |
    1000 Förderprogramm -
    1000 Fördernummer 1-ZE8J
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6423862.rdf
1000 Erstellt am 2020-10-30T17:02:58.262+0100
1000 Erstellt von 218
1000 beschreibt frl:6423862
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2020-11-06T10:00:18.427+0100
1000 Objekt bearb. Fri Nov 06 09:59:46 CET 2020
1000 Vgl. frl:6423862
1000 Oai Id
  1. oai:frl.publisso.de:frl:6423862 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source