Effects of Metapopulation Mobility and Climate Change in SI-SIR Model for Malaria Disease

Marie, Ingabire Emma; Kimura, Masaomi

doi:10.1145/3408066.3408084

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Several studies exist on the coinfection with specific diseases. There are also studies [19,16,17,7,14] which have addressed this issue in general. In [6], a mathematical model has been studied and showed that strains with differing degree of infectivity extinct, except for those that have higher the basic reproduction number.…”

Section: Introductionmentioning

confidence: 99%

Effect of density dependence on coinfection dynamics

Andersson¹,

Ghersheen²,

Kozlov³

et al. 2020

Preprint

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In this paper we develop an SIR model for coinfection. We discuss how the underlying dynamics depends on the carrying capacity K: from a simple dynamics to a more complicated. This can help in understanding of appearance of more complicated dynamics, for example, chaos etc. The density dependent population growth is also considered. It is presented that pathogens can invade in population and their invasion depends on the carrying capacity K which shows that the progression of disease in population depends on carrying capacity. Our approach is based on a bifurcation analysis which allows to generalize considerably the previous Lotka-Volterra model considered previously in [12].

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Section: Introductionmentioning

confidence: 99%

Effect of density dependence on coinfection dynamics

Andersson¹,

Ghersheen²,

Kozlov³

et al. 2020

Preprint

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Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Lazebnik

2024

Soc. Netw. Anal. Min.

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Sexually transmitted diseases (STDs) are a group of pathogens infecting new hosts through sexual interactions. Due to its social and economic burden, multiple models have been proposed to study the spreading of pathogens. In parallel, in the ever-evolving landscape of digital social interactions, the pervasive utilization of dating apps has become a prominent facet of modern society. Despite the surge in popularity and the profound impact on relationship formation, a crucial gap in the literature persists regarding the potential ramifications of dating apps usage on the dynamics of STDs. In this paper, we address this gap by presenting a novel mathematical framework - an extended Susceptible-Infected-Susceptible (SIS) epidemiological model to elucidate the intricate interplay between dating apps engagement and the propagation of STDs. Namely, as dating apps are designed to make users revisit them and have mainly casual sexual interactions with other users, they increase the number of causal partners, which increases the overall spread of STDS. Using extensive simulation, based on real-world data, explore the effect of dating apps adoption and control on the STD spread. We show that an increased adoption of dating apps can result in an STD outbreak if not handled appropriately.

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Effect of density dependence on coinfection dynamics

et al. 2021

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In this paper we develop a compartmental model of SIR type (the abbreviation refers to the number of Susceptible, Infected and Recovered people) that models the population dynamics of two diseases that can coinfect. We discuss how the underlying dynamics depends on the carrying capacity K: from a simple dynamics to a more complex. This can also help in understanding the appearance of more complicated dynamics, for example, chaos and periodic oscillations, for large values of K. It is also presented that pathogens can invade in population and their invasion depends on the carrying capacity K which shows that the progression of disease in population depends on carrying capacity. More specifically, we establish all possible scenarios (the so-called transition diagrams) describing an evolution of an (always unique) locally stable equilibrium state (with only non-negative compartments) for fixed fundamental parameters (density independent transmission and vital rates) as a function of the carrying capacity K. An important implication of our results is the following important observation. Note that one can regard the value of K as the natural ‘size’ (the capacity) of a habitat. From this point of view, an isolation of individuals (the strategy which showed its efficiency for COVID-19 in various countries) into smaller resp. larger groups can be modelled by smaller resp. bigger values of K. Then we conclude that the infection dynamics becomes more complex for larger groups, as it fairly maybe expected for values of the reproduction number $$R_0\approx 1$$ R 0 ≈ 1 . We show even more, that for the values $$R_0>1$$ R 0 > 1 there are several (in fact four different) distinguished scenarios where the infection complexity (the number of nonzero infected classes) arises with growing K. Our approach is based on a bifurcation analysis which allows to generalize considerably the previous Lotka-Volterra model considered previously in Ghersheen et al. (Math Meth Appl Sci 42(8), 2019).

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Effects of Metapopulation Mobility and Climate Change in SI-SIR Model for Malaria Disease

Cited by 3 publications

References 12 publications

Effect of density dependence on coinfection dynamics

Effect of density dependence on coinfection dynamics

Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Effect of density dependence on coinfection dynamics

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