Literature DB >> 18706917

The control of vector-borne disease epidemics.

Geoffrey R Hosack1, Philippe A Rossignol, P van den Driessche.   

Abstract

The theoretical underpinning of our struggle with vector-borne disease, and still our strongest tool, remains the basic reproduction number, R(0), the measure of long term endemicity. Despite its widespread application, R(0) does not address the dynamics of epidemics in a model that has an endemic equilibrium. We use the concept of reactivity to derive a threshold index for epidemicity, E(0), which gives the maximum number of new infections produced by an infective individual at a disease free equilibrium. This index describes the transitory behavior of disease following a temporary perturbation in prevalence. We demonstrate that if the threshold for epidemicity is surpassed, then an epidemic peak can occur, that is, prevalence can increase further, even when the disease is not endemic and so dies out. The relative influence of parameters on E(0) and R(0) may differ and lead to different strategies for control. We apply this new threshold index for epidemicity to models of vector-borne disease because these models have a long history of mathematical analysis and application. We find that both the transmission efficiency from hosts to vectors and the vector-host ratio may have a stronger effect on epidemicity than endemicity. The duration of the extrinsic incubation period required by the pathogen to transform an infected vector to an infectious vector, however, may have a stronger effect on endemicity than epidemicity. We use the index E(0) to examine how vector behavior affects epidemicity. We find that parasite modified behavior, feeding bias by vectors for infected hosts, and heterogeneous host attractiveness contribute significantly to transitory epidemics. We anticipate that the epidemicity index will lead to a reevaluation of control strategies for vector-borne disease and be applicable to other disease transmission models.

Entities:  

Mesh:

Year:  2008        PMID: 18706917     DOI: 10.1016/j.jtbi.2008.07.033

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

1.  Transient indicators of tipping points in infectious diseases.

Authors:  Suzanne M O'Regan; Eamon B O'Dea; Pejman Rohani; John M Drake
Journal:  J R Soc Interface       Date:  2020-09-16       Impact factor: 4.118

2.  A reaction-diffusion malaria model with seasonality and incubation period.

Authors:  Zhenguo Bai; Rui Peng; Xiao-Qiang Zhao
Journal:  J Math Biol       Date:  2017-11-29       Impact factor: 2.259

3.  Modelling vertical transmission in vector-borne diseases with applications to Rift Valley fever.

Authors:  Nakul Chitnis; James M Hyman; Carrie A Manore
Journal:  J Biol Dyn       Date:  2013       Impact factor: 2.179

4.  The epidemicity index of recurrent SARS-CoV-2 infections.

Authors:  Lorenzo Mari; Renato Casagrandi; Enrico Bertuzzo; Damiano Pasetto; Stefano Miccoli; Andrea Rinaldo; Marino Gatto
Journal:  Nat Commun       Date:  2021-05-12       Impact factor: 14.919

Review 5.  The failure of R0.

Authors:  Jing Li; Daniel Blakeley; Robert J Smith
Journal:  Comput Math Methods Med       Date:  2011-08-16       Impact factor: 2.238

6.  Impact of biodiversity and seasonality on Lyme-pathogen transmission.

Authors:  Yijun Lou; Jianhong Wu; Xiaotian Wu
Journal:  Theor Biol Med Model       Date:  2014-11-28       Impact factor: 2.432

7.  Data-driven modeling to assess receptivity for Rift Valley Fever virus.

Authors:  Christopher M Barker; Tianchan Niu; William K Reisen; David M Hartley
Journal:  PLoS Negl Trop Dis       Date:  2013-11-14
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.