Literature DB >> 25417817

Interpretations and pitfalls in modelling vector-transmitted infections.

M Amaku1, F Azevedo2, M N Burattini2, F A B Coutinho2, L F Lopez2, E Massad2.   

Abstract

In this paper we propose a debate on the role of mathematical models in evaluating control strategies for vector-borne infections. Mathematical models must have their complexity adjusted to their goals, and we have basically two classes of models. At one extreme we have models that are intended to check if our intuition about why a certain phenomenon occurs is correct. At the other extreme, we have models whose goals are to predict future outcomes. These models are necessarily very complex. There are models in between these classes. Here we examine two models, one of each class and study the possible pitfalls that may be incurred. We begin by showing how to simplify the description of a complicated model for a vector-borne infection. Next, we examine one example found in a recent paper that illustrates the dangers of basing control strategies on models without considering their limitations. The model in this paper is of the second class. Following this, we review an interesting paper (a model of the first class) that contains some biological assumptions that are inappropriate for dengue but may apply to other vector-borne infections. In conclusion, we list some misgivings about modelling presented in this paper for debate.

Entities:  

Keywords:  Dengue; mathematical modelling; vector-borne infections

Mesh:

Year:  2014        PMID: 25417817      PMCID: PMC9507249          DOI: 10.1017/S0950268814002660

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   4.434


  18 in total

1.  Modelling the dynamics of dengue real epidemics.

Authors:  S T R Pinho; C P Ferreira; L Esteva; F R Barreto; V C Morato e Silva; M G L Teixeira
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2010-12-28       Impact factor: 4.226

2.  Threshold conditions for a non-autonomous epidemic system describing the population dynamics of dengue.

Authors:  F A B Coutinho; M N Burattini; L F Lopez; E Massad
Journal:  Bull Math Biol       Date:  2006-09-02       Impact factor: 1.758

3.  A hypothesis for explaining single outbreaks (like the Black Death in European cities) of vector-borne infections.

Authors:  M N Burattini; F A B Coutinho; E Massad
Journal:  Med Hypotheses       Date:  2009-03-04       Impact factor: 1.538

4.  Estimation of R0 from the initial phase of an outbreak of a vector-borne infection.

Authors:  E Massad; F A B Coutinho; M N Burattini; M Amaku
Journal:  Trop Med Int Health       Date:  2009-11-03       Impact factor: 2.622

Review 5.  The transmission dynamics of human immunodeficiency virus (HIV).

Authors:  R M May; R M Anderson
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1988-10-31       Impact factor: 6.237

6.  The cost of dengue control.

Authors:  Eduardo Massad; Francisco Antonio Bezerra Coutinho
Journal:  Lancet       Date:  2011-05-03       Impact factor: 79.321

7.  A comparative analysis of the relative efficacy of vector-control strategies against dengue fever.

Authors:  Marcos Amaku; Francisco Antonio Bezerra Coutinho; Silvia Martorano Raimundo; Luis Fernandez Lopez; Marcelo Nascimento Burattini; Eduardo Massad
Journal:  Bull Math Biol       Date:  2014-03-12       Impact factor: 1.758

8.  Maximum equilibrium prevalence of mosquito-borne microparasite infections in humans.

Authors:  Marcos Amaku; Marcelo Nascimento Burattini; Francisco Antonio Bezerra Coutinho; Luis Fernandez Lopez; Eduardo Massad
Journal:  Comput Math Methods Med       Date:  2013-12-24       Impact factor: 2.238

9.  Modeling the risk of malaria for travelers to areas with stable malaria transmission.

Authors:  Eduardo Massad; Ronald H Behrens; Marcelo N Burattini; Francisco A B Coutinho
Journal:  Malar J       Date:  2009-12-16       Impact factor: 2.979

10.  Transmission dynamics of the four dengue serotypes in southern Vietnam and the potential impact of vaccination.

Authors:  Laurent Coudeville; Geoff P Garnett
Journal:  PLoS One       Date:  2012-12-10       Impact factor: 3.240

View more
  4 in total

1.  Magnitude and frequency variations of vector-borne infection outbreaks using the Ross-Macdonald model: explaining and predicting outbreaks of dengue fever.

Authors:  M Amaku; F Azevedo; M N Burattini; G E Coelho; F A B Coutinho; D Greenhalgh; L F Lopez; R S Motitsuki; A Wilder-Smith; E Massad
Journal:  Epidemiol Infect       Date:  2016-08-19       Impact factor: 4.434

2.  Estimating the size of Aedes aegypti populations from dengue incidence data: Implications for the risk of yellow fever outbreaks.

Authors:  Eduardo Massad; Marcos Amaku; Francisco Antonio Bezerra Coutinho; Claudio José Struchiner; Luis Fernandez Lopez; Annelies Wilder-Smith; Marcelo Nascimento Burattini
Journal:  Infect Dis Model       Date:  2017-12-08

3.  Estimation of the Basic Reproductive Ratio for Dengue Fever at the Take-Off Period of Dengue Infection.

Authors:  Sapto W Indratno; Nuning Nuraini; Asep K Supriatna; Edy Soewono
Journal:  Comput Math Methods Med       Date:  2015-08-25       Impact factor: 2.238

4.  The risk of dengue for non-immune foreign visitors to the 2016 summer olympic games in Rio de Janeiro, Brazil.

Authors:  Raphael Ximenes; Marcos Amaku; Luis Fernandez Lopez; Francisco Antonio Bezerra Coutinho; Marcelo Nascimento Burattini; David Greenhalgh; Annelies Wilder-Smith; Claudio José Struchiner; Eduardo Massad
Journal:  BMC Infect Dis       Date:  2016-04-29       Impact factor: 3.090

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.