Demographic and Spatial Factors as Causes of an Epidemic Spread, the Copule Approach: Application to the Retro-prediction of the Black Death Epidemy of 1346

Gaudart, Jean; Ghassani, Mohamad; Mintsa, Julie; Waku, Jules; Rachdi, Mustapha; Doumbo, Ogobara K.; Demongeot, Jacques

doi:10.1109/waina.2010.79

Cited by 12 publications

(13 citation statements)

References 28 publications

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“…While the classical model assumes that populations during epidemics remain constant, the experiences with more recent pandemics demonstrated host and vector population changes, as well as transient or even permanent migration and diffusion of hosts [90][91][92]. As described by Lloyd-Smith et.al., the emergence of epidemics due to zoonotic diseases (resulting from cross-species spillover) depend on the prevalence of the infection in the animal reservoir, the rate at which human hosts have contact with the diseased animal reservoir, and lastly the probability that humans become infected upon contact with diseased animals [92].…”

Section: Human Activity Factors Associated With Infectious Disease Oumentioning

confidence: 99%

Lessons Learned from Historic Plague Epidemics: The Relevance of an Ancient Disease in Modern Times

Boire¹

2014

J Anc Dis Prev Rem

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Section: Human Activity Factors Associated With Infectious Disease Oumentioning

confidence: 99%

Lessons Learned from Historic Plague Epidemics: The Relevance of an Ancient Disease in Modern Times

Boire¹

2014

J Anc Dis Prev Rem

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“…about 1,500 km/year (Brandenburg and Multamaki 2004). The model used in this paper for modelling the Black Death spread is a SIRD model as in the Bankoumana study (Gaudart et al 2007(Gaudart et al , 2009(Gaudart et al , 2010, but without vector terms and has for its reaction term the form of a Lotka-Volterra Ordinary Differential Equation (ODE) of dimension 3, plus a diffusion term:…”

Section: The Modelmentioning

confidence: 99%

“…consideration of host and vector populations whose global size changes during both epidemic and endemic histories) as well as spatial aspects about host, vector or infectious agent spread or genetic change (Gaudart et al 2010). Mathematical tools corresponding to these improvements have been recently introduced making the classical models more realistic, hence more convenient for prediction and anticipation (like vaccination or other measures of public health limiting the contagion).…”

Section: Introductionmentioning

confidence: 99%

“…These models are called SIGR with Diffusion (SIGRD) (de Magny et al 2005). The Bankoumana model is a double SIGRD model (Gaudart et al 2007(Gaudart et al , 2009(Gaudart et al , 2010 whose PDE equations have spatial initial conditions essentially determined by the spawning zones of mosquitos in backwater places. These zones are depending on the rainfall, e.g.…”

Section: Introduction Of a Spatial Dynamicsmentioning

confidence: 99%

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Demography and Diffusion in Epidemics: Malaria and Black Death Spread

et al. 2010

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The classical models of epidemics dynamics by Ross and McKendrick have to be revisited in order to incorporate elements coming from the demography (fecundity, mortality and migration) both of host and vector populations and from the diffusion and mutation of infectious agents. The classical approach is indeed dealing with populations supposed to be constant during the epidemic wave, but the presently observed pandemics show duration of their spread during years imposing to take into account the host and vector population changes as well as the transient or permanent migration and diffusion of hosts (susceptible or infected), as well as vectors and infectious agents. Two examples are presented, one concerning the malaria in Mali and the other the plague at the middle-age.

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“…by considering morphogen, cell, pathogen, host and vector populations whose global size changes during morphogenetic, epidemic and endemic histories, as well as spatial aspects about their diffusion, spread or genetic changes [Gaudart et al, 2007[Gaudart et al, , 2009[Gaudart et al, , 2010a[Gaudart et al, , 2010bGlade et al, 2007;Abbas et al, 2009;Horie et al, 2010;Demongeot et al, to appear].…”

Section: Introductionmentioning

confidence: 99%

Zero-Diffusion Domains in Reaction–diffusion Morphogenetic and Epidemiologic Processes

Demongeot

Gaudart

Lontos

et al. 2012

Int. J. Bifurcation Chaos

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Classical models of morphogenesis by Murray and Meinhardt and of epidemics by Ross andMcKendrick can be revisited in order to consider the colocalizations favoring interaction between morphogens and cells or between pathogens and hosts. The classical epidemic models suppose, for example, that the populations in interaction have a constant size and are spatially fixed during the epidemic waves, but the presently observed pandemics show that the long duration of their spread during months or years imposes to take into account the pathogens, hosts and vectors migration in epidemics, as well as the morphogens and cells diffusion in morphogenesis. That leads naturally to study the occurrence of complex spatio-temporal behaviors in dynamics of population sizes and also to consider preferential zones of interaction, i.e. the zero-diffusion sets, for respectively building anatomic frontiers and confining contagion domains. Three examples of application will be presented, the first proposing a model of Black Death spread in Europe (1348-1350), and the last ones related to two morphogenetic processes, feather morphogenesis in chicken and gastrulation in Drosophila.

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Demographic and Spatial Factors as Causes of an Epidemic Spread, the Copule Approach: Application to the Retro-prediction of the Black Death Epidemy of 1346

Cited by 12 publications

References 28 publications

Lessons Learned from Historic Plague Epidemics: The Relevance of an Ancient Disease in Modern Times

Lessons Learned from Historic Plague Epidemics: The Relevance of an Ancient Disease in Modern Times

Demography and Diffusion in Epidemics: Malaria and Black Death Spread

Zero-Diffusion Domains in Reaction–diffusion Morphogenetic and Epidemiologic Processes

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