Searcharxiv⌕ Search

arXiv · 0709.3049

Epidemic Size in the Sis Model of Endemic Infec- Tions

Abstract

We study the Susceptible-Infected-Susceptible model of the spread of an endemic infection. We calculate an exact expression for the mean number of transmissions for all values of the population and the infectivity. We derive the large-N asymptotic behavior for the infectivitiy below, above, and in the critical region. We obtain an analytical expression for the probability distribution of the number of transmissions, n, in the critical region. We show that this distribution has a $n^3/2$ singularity for small n and decays exponentially for large n. The exponent decreases with the distance from threshold, diverging to infinity far below and approaching zero far above.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

David A. Kessler. 2007-09-19. Epidemic Size in the Sis Model of Endemic Infec- Tions. https://arxiv.org/abs/0709.3049

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Molecular genetics of Aedes aegypti: historical advances and oversights

The yellow fever mosquito Aedes aegypti has a rich history of molecular genetic work but in recent years this has lagged behind rivals such as Anopheles, owing to the nature of control efforts focused on Ae. aegypti and the complex structure of its genome. However, Ae. aegypti has now entered the whole-genomic era of molecular genetics, with many whole genome sequences of individuals now publicly available for analysis. These resources enable an unprecedented view on several core genetic questions that have vexed research on the species for decades. They also create the possibility for new genomic analyses to be developed in the future. In this review, we consider the history of molecular genetic technology as it applies to Ae. aegypti, with a special emphasis on how emerging pictures of the genome both enabled and in some cases constrained the development of work on population genetics and insecticide resistance. We integrate historical and contemporary perspectives to diagnose gaps and biases within the Ae. aegypti literature that require further clarification and research. In particular, these highlight underrepresentation of the Indo-Pacific region in whole genome datasets relative to its dengue burden, and the overlooking of copy number variation in resistance studies owing to difficulties of sequence alignment in duplicated regions, particularly around the glutathione S-transferase epsilon class of genes.

q-bio.PE↗

Viral mutation spread controlled by inter-host network dynamics

The increase in the connectivity between hosts in recent times has facilitated the emergence of more aggressive mutant viral strains, making their containment and eradication significantly more challenging compared to the original variants. We focus on the evolution of a new more aggressive mutant strain that appears in the system and competes with a previous version. The role of host interaction network topology in the emergence and spatial diffusion of these highly contagious strains is analyzed, as well as how network-based interventions can help mitigate their spread. To address these issues, we present simplified mathematical models that qualitatively describe the occurrence, propagation, and impact of such mutations within host-interaction networks. By incorporating the topology of the host network into the analysis, a more advanced framework is proposed to curb the growth of mutant strains. Extensive numerical simulations of these models offer insights into the mechanisms driving viral evolution, the dynamics of contagion, and the topological influence of host networks on viral spread and containment strategies.

q-bio.PE↗

How deterministic trajectories and their fluctuations underlie allele-frequency statistics in the strong-selection regime

We determine statistics of allele-frequency trajectories across replicate populations. Defining $R = 2N_e|s|$ where $N_e$ is the effective population size and $s$ is the additive selection coefficient of a focal allele, we focus on strong selection which corresponds to $R \gg 1$. Strong selection does not require large selection coefficients: in populations of realistic size, it can readily arise from small selection coefficients. Our analysis concerns a biallelic locus over timescales on which mutation can be neglected. Every allele-frequency trajectory belongs to one of two absorbing classes: fixation or loss. When $R$ is large, individual allele-frequency trajectories can appear nearly deterministic. This does not imply that an approximation of allele-frequency statistics can be based on a single deterministic trajectory. For a beneficial allele, the deterministic trajectory approaches fixation, yet a non-negligible fraction of stochastic trajectories may be lost. Ignoring trajectories that achieve loss can produce severely erroneous statistics. We address this by conditioning separately on the eventual loss and eventual fixation of the focal allele. This yields an outcome-conditioned representation of a statistic. In the strong-selection regime, we apply a small-noise expansion that reasonably captures transient behaviours of statistics while recovering their exact long-time limits. We illustrate results with numerical examples for the mean allele frequency and its variance. The biological interpretation of this work is that, even under strong selection, both trajectory types are of importance. We provide a simple framework for calculating time-dependent allele-frequency statistics relevant to experimental evolution, longitudinal population-genomic data, and the dynamics of alleles driving selective sweeps.

q-bio.PE↗