Invasion speeds of Triatoma dimidiata, vector of Chagas disease: An application of orthogonal polynomials method

Mesk, Mohammed; Mahdjoub, Tewfik; Gourbière, Sébastien; Rabinovich, Jorge E.; Menu, Frédéric

doi:10.1016/j.jtbi.2016.01.017

Cited by 5 publications

(3 citation statements)

References 84 publications

(115 reference statements)

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“…A promising avenue is the application of orthogonal polynomials methods to predict triatomine dispersal based upon exclusively life-history data of each triatomine species 23 . Tackling transmission by native vectors may necessitate alternative control strategies, which would require measuring dispersal and evaluating the efficacy of strategies such as those used for other vector-borne diseases, e.g.…”

Section: Insights Gained From Quantitative and Mathematical Modellingmentioning

confidence: 99%

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease

2019

Gates Open Res

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Chagas disease (CD) persists as one of the neglected tropical diseases (NTDs) with a particularly large impact in the Americas. The World Health Organization (WHO) recently proposed goals for CD elimination as a public health problem to be reached by 2030 by means of achieving intradomiciliary transmission interruption (IDTI), blood transfusion and transplant transmission interruption, diagnostic and treatment scaling-up and prevention and control of congenital transmission. The NTD Modelling Consortium has developed mathematical models to study Trypanosoma cruzi transmission dynamics and the potential impact of control measures. Modelling insights have shown that IDTI is feasible in areas with sustained vector control programmes and no presence of native triatomine vector populations. However, IDTI in areas with native vectors it is not feasible in a sustainable manner. Combining vector control with trypanocidal treatment can reduce the timeframes necessary to reach operational thresholds for IDTI (<2% seroprevalence in children aged <5 years), but the most informative age groups for serological monitoring are yet to be identified. Measuring progress towards the 2030 goals will require availability of vector surveillance and seroprevalence data at a fine scale, and a more active surveillance system, as well as a better understanding of the risks of vector re-colonization and disease resurgence after vector control cessation. Also, achieving scaling-up in terms of access to treatment to the expected levels (75%) will require a substantial increase in screening asymptomatic populations, which is anticipated to become very costly as CD prevalence decreases. Further modelling work includes refining and extending mathematical models (including transmission dynamics and statistical frameworks) to predict transmission at a sub-national scale, and developing quantitative tools to inform IDTI certification, post-certification and re-certification protocols. Potential perverse incentives associated with operational thresholds are discussed. These modelling insights aim to inform discussions on the goals and treatment guidelines for CD.

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Section: Insights Gained From Quantitative and Mathematical Modellingmentioning

confidence: 99%

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease

2019

Gates Open Res

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“…Relying on this conjecture, the asymptotic rate of spread has been studied for various nonlinear models by comparison or asymptotic approximation methods, e.g. [37,39,33,6,41,36,29].…”

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On an upper bound for the spreading speed

Mesk¹,

Moussaoui²

2021

DCDS-B

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<p style='text-indent:20px;'>In this paper, we use the exponential transform to give a unified formal upper bound for the asymptotic rate of spread of a population propagating in a one dimensional habitat. We show through examples how this upper bound can be obtained directly for discrete and continuous time models. This upper bound has the form <inline-formula><tex-math id="M1">\begin{document}$ \min_{s>0} \ln (\rho(s))/s $\end{document}</tex-math></inline-formula> and coincides with the speeds of several models found in the literature.</p>

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“…Mathematical modeling stand a good tool to gain insights into 6092 N. DIB-BAGHDADLI, R. LABBAS, T. MAHDJOUB AND A. MEDEGHRI these processes [21]. These approach used, for example, ordinary differential equations [15], partial differential equations [24] and integro-difference equations [20], [18]. Other studies based on scientific calculus were also used as cellular automaton [23], [5] and agent-based model [6], [9].…”

mentioning

confidence: 99%

On some reaction-diffusion equations generated by non-domiciliated triatominae, vectors of Chagas disease

Dib-Baghdadli¹,

Labbas²,

Mahdjoub³

et al. 2021

DCDS-B

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Invasion speeds of Triatoma dimidiata, vector of Chagas disease: An application of orthogonal polynomials method

Cited by 5 publications

References 84 publications

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease

On an upper bound for the spreading speed

On some reaction-diffusion equations generated by non-domiciliated triatominae, vectors of Chagas disease

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