Literature DB >> 8834738

Vector-borne diseases and the basic reproduction number: a case study of African horse sickness.

C C Lord1, M E Woolhouse, J A Heesterbeek, P S Mellor.   

Abstract

The basic reproduction number, R0, can be used to determine factors important in the ability of a disease to invade or persist. We show how this number can be derived or estimated for vector-borne diseases with different complicating factors. African horse sickness is a viral disease transmitted mainly by the midge Culicoides imicola. We use this as an example of such a vector-transmitted disease where latent periods, seasonality in vector populations, and multiple host types may be important. The effect of vector population dynamics which are dependent on either host or vector density are also addressed. If density-dependent constraints on vector population density are less severe, R0 is more sensitive to vector mortality and the virus development rate. Host-dependent vector dynamics change the relationship between R0 and host population size. Seasonality can either increase or decrease the estimate of R0, depending on the lag between the peak of the midge population and the infective host population. The relative abundance of two host types is a factor in the ability of a disease to invade, but the strength of this factor depends on the differences between the hosts in recovery from infection, mortality and transmission. Removal of a reservoir host may increase R0.

Entities:  

Mesh:

Year:  1996        PMID: 8834738     DOI: 10.1111/j.1365-2915.1996.tb00077.x

Source DB:  PubMed          Journal:  Med Vet Entomol        ISSN: 0269-283X            Impact factor:   2.739


  21 in total

Review 1.  Modeling and biological control of mosquitoes.

Authors:  Cynthia C Lord
Journal:  J Am Mosq Control Assoc       Date:  2007       Impact factor: 0.917

2.  Seasonal population dynamics and behaviour of insects in models of vector-borne pathogens.

Authors:  Cynthia C Lord
Journal:  Physiol Entomol       Date:  2004       Impact factor: 1.833

3.  Resonance of the epidemic threshold in a periodic environment.

Authors:  Nicolas Bacaër; Xamxinur Abdurahman
Journal:  J Math Biol       Date:  2008-05-07       Impact factor: 2.259

4.  Bifurcation thresholds and optimal control in transmission dynamics of arboviral diseases.

Authors:  Hamadjam Abboubakar; Jean Claude Kamgang; Leontine Nkague Nkamba; Daniel Tieudjo
Journal:  J Math Biol       Date:  2017-06-06       Impact factor: 2.259

5.  The Effect of Multiple Vectors on Arbovirus Transmission.

Authors:  Cynthia C Lord
Journal:  Isr J Ecol Evol       Date:  2010-01-01       Impact factor: 0.559

6.  Seasonal infectious disease epidemiology.

Authors:  Nicholas C Grassly; Christophe Fraser
Journal:  Proc Biol Sci       Date:  2006-10-07       Impact factor: 5.349

7.  Sheep movement networks and the transmission of infectious diseases.

Authors:  Victoriya V Volkova; Richard Howey; Nicholas J Savill; Mark E J Woolhouse
Journal:  PLoS One       Date:  2010-06-17       Impact factor: 3.240

8.  A new method for estimating the effort required to control an infectious disease.

Authors:  M G Roberts; J A P Heesterbeek
Journal:  Proc Biol Sci       Date:  2003-07-07       Impact factor: 5.349

9.  Can Horton hear the whos? The importance of scale in mosquito-borne disease.

Authors:  C C Lord; B W Alto; S L Anderson; C R Connelly; J F Day; S L Richards; C T Smartt; W J Tabachnick
Journal:  J Med Entomol       Date:  2014-03       Impact factor: 2.278

10.  Where are the horses? With the sheep or cows? Uncertain host location, vector-feeding preferences and the risk of African horse sickness transmission in Great Britain.

Authors:  Giovanni Lo Iacono; Charlotte A Robin; J Richard Newton; Simon Gubbins; James L N Wood
Journal:  J R Soc Interface       Date:  2013-04-17       Impact factor: 4.118

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.