Recasting the theory of mosquito-borne pathogen transmission dynamics and control

Smith, David L.; Perkins, T. Alex; Reiner, Robert C.; Barker, Christopher M.; Niu, Tianchan; Chaves, Luis Fernando; Ellis, Alicia M.; George, Dylan B.; Menach, Arnaud Le; Pulliam, Juliet R. C.; Bisanzio, Donal; Buckee, Caroline O.; Chiyaka, Christinah; Cummings, Derek A. T.; García, Andrés J.; Gatton, Michelle L.; Gething, Peter W.; Hartley, David; Johnston, Geoffrey L.; Klein, Eili Y.; Michael, Edwin; Lloyd, Alun L.; Pigott, David M.; Reisen, William K.; Ruktanonchai, Nick W.; Singh, Bhavna; Stoller, Jeremy; Tatem, Andrew J.; Kitron, Uriel; Godfray, H. Charles J.; Cohen, Justin M.; Hay, Simon I.; Scott, Thomas W.

doi:10.1093/trstmh/tru026

Cited by 147 publications

(133 citation statements)

References 87 publications

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“…Assumptions on the proportionality between infected mosquitoes and the force of infection, as well as the density-dependence assumption in these models could be questioned. Indeed even if these assumptions are at the heart of the mathematical models of mosquito-borne pathogen transmission (Reiner et al, 2013; Smith et al, 2014), a recent review (Halstead, 2008) and recent experimental results (Bowman et al, 2014; Harrington et al, 2014) question these important points.…”

Section: Discussionmentioning

confidence: 99%

Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Champagne

Salthouse

Rácz

et al. 2016

eLife

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Before the outbreak that reached the Americas in 2015, Zika virus (ZIKV) circulated in Asia and the Pacific: these past epidemics can be highly informative on the key parameters driving virus transmission, such as the basic reproduction number (R0). We compare two compartmental models with different mosquito representations, using surveillance and seroprevalence data for several ZIKV outbreaks in Pacific islands (Yap, Micronesia 2007, Tahiti and Moorea, French Polynesia 2013-2014, New Caledonia 2014). Models are estimated in a stochastic framework with recent Bayesian techniques. R0 for the Pacific ZIKV epidemics is estimated between 1.5 and 4.1, the smallest islands displaying higher and more variable values. This relatively low range of R0 suggests that intervention strategies developed for other flaviviruses should enable as, if not more effective control of ZIKV. Our study also highlights the importance of seroprevalence data for precise quantitative analysis of pathogen propagation, to design prevention and control strategies.DOI: http://dx.doi.org/10.7554/eLife.19874.001

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Section: Discussionmentioning

confidence: 99%

Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Champagne

Salthouse

Rácz

et al. 2016

eLife

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“…Understanding the impact of such variation on vector‐borne disease dynamics is an important research frontier (Smith et al . ).…”

Section: Mechanisms Promoting Heterogeneitymentioning

confidence: 97%

Heterogeneity in pathogen transmission: mechanisms and methodology

2016

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Summary1. Heterogeneity in the ability of hosts to transmit pathogens is among the most fundamental concepts in disease dynamics and has major implications for disease control strategies. 2. The number of secondary infections produced by an infected individual is a function of three components: an individual's infectiousness, the rate at which it contacts susceptible individuals and the duration of infection. Individual-level variation can emerge in each of these components through a combination of behavioural and physiological mechanisms. 3. In this review, we describe mechanisms that promote variation in the number of individuals to which an individual transmits a pathogen, emphasizing insights that can be gained by understanding which components of transmission (infectiousness, contact rate, infection duration) are primarily affected. We also discuss how behavioural and physiological processes generate transmission heterogeneities across multiple scales, from individual-level variation to heterogeneity among species. 4. Strategies for quantifying each transmission component are presented, and we discuss why studies focusing on only one component of the infection process may be misleading. 5. To conclude, we describe how future research focusing on variation in transmission across all three components can provide a more holistic view of heterogeneity in pathogen transmission.

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“…If this heterogeneity is great, then the concept of an average might be wrong (e.g. Dye (1986); Smith et al (2014)). The consequence of mistakenly believing individuals are all essentially equal is usually to under-estimate the control effort required (i.e.…”

Section: Current Data and Initial Modelsmentioning

confidence: 99%

Progress in the Mathematical Modelling of Visceral Leishmaniasis

Rock¹,

Quinnell²,

Medley³

et al. 2016

Mathematical Models for Neglected Tropical Diseases - Essential Tools for Control and Elimination, Part B

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The leishmaniases comprise a complex of diseases characterised by clinical outcomes that range from self-limiting to chronic, disfiguring and stigmatising, to life-threatening. Diagnostic methods, treatments, and vector and reservoir control options exist, but deciding the most effective interventions requires a quantitative understanding of the population level infection and disease dynamics. The effectiveness of any set of interventions has to be determined within the context of operational conditions, including economic and political commitment. Mathematical models are the best available tools for studying quantitative systems crossing disciplinary spheres (biology, medicine, economics) within environmental and societal constraints.In 2005, the World Health Assembly and government health ministers of India, Nepal, and Bangladesh signed a Memorandum of Understanding to eliminate the life threatening form of leishmaniasis, visceral leishmaniasis (VL), on the Indian subcontinent by 2015 through a combination of early case detection, improved treatments, and vector control. The elimination target is <1/10,000 population at the district or subdistrict level compared to the current 20/10,000 in the regions of highest transmission.Towards this goal, this chapter focuses on mathematical models of VL, and the biology driving those models, to enable realistic predictions of the * Corresponding author Email address: orin.courtenay@warwick.ac.uk (Orin Courtenay)Preprint submitted to Advances in Parasitology July 18, 2016 best combination of interventions. Several key issues will be discussed which have affected previous modelling of VL and the direction future modelling may take. Current understanding of the natural history of disease, immunity (and loss of immunity), as well as stages of infection and their durations are considered particularly for humans, but also for dogs. Asymptomatic and clinical infection are discussed in the context of their relative roles in Leishmania transmission, as well as key components of the parasite-sandfly-vector interaction and intervention strategies including diagnosis, treatment and vector control. Gaps in current biological knowledge and potential avenues to improve model structures and mathematical predictions are identified. Underpinning the marriage between biology and mathematical modelling, the content of this chapter represents the first step towards developing the next generation of models for VL.

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Recasting the theory of mosquito-borne pathogen transmission dynamics and control

Cited by 147 publications

References 87 publications

Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Heterogeneity in pathogen transmission: mechanisms and methodology

Progress in the Mathematical Modelling of Visceral Leishmaniasis

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