scholarly journals Age-structured SIR model and resource growth dynamics: A preliminary COVID-19 study

2020 ◽  
Author(s):  
S. G. Babajanyan ◽  
Kang Hao Cheong
Keyword(s):  
Growth Dynamics ◽  
Sir Model ◽  
Disease Outbreak ◽  
Disease Spread ◽  
Logistic Growth ◽  
Economic Implications ◽  
Spread Dynamics ◽  
Resource Dynamics ◽  
Age Structured ◽  
Different Response

In this paper, we discuss three different response strategies to a disease outbreak and their economic implications in an age-structured population. We have utilized the classical age structured SIR-model, thus assuming that recovered people will not be infected again. Available resource dynamics is governed by the well-known logistic growth model, in which the reproduction coefficient depends on the disease outbreak spreading dynamics. We further investigate the feedback interaction of the disease spread dynamics and resource growth dynamics with the premise that the quality of treatment depends on the current economic situation. The very inclusion of mortality rates and economic considerations in the same model may be incongruous under certain positions, but in this model, we take a 'realpolitik' approach by exploring all of these factors together as it is done in reality.

scholarly journals A modified age-structured SIR model for COVID-19 type viruses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vishaal Ram ◽  
Laura P. Schaposnik
Keyword(s):  
Mortality Rate ◽  
Age Distribution ◽  
Social Contact ◽  
Sir Model ◽  
Disease Spread ◽  
Population Parameters ◽  
Specific Contact ◽  
Treatment Measures ◽  
Age Structured ◽  
Varying Population

AbstractWe present a modified age-structured SIR model based on known patterns of social contact and distancing measures within Washington, USA. We find that population age-distribution has a significant effect on disease spread and mortality rate, and contribute to the efficacy of age-specific contact and treatment measures. We consider the effect of relaxing restrictions across less vulnerable age-brackets, comparing results across selected groups of varying population parameters. Moreover, we analyze the mitigating effects of vaccinations and examine the effectiveness of age-targeted distributions. Lastly, we explore how our model can applied to other states to reflect social-distancing policy based on different parameters and metrics.

PyDOSS: An open-source Python-based communicable disease outbreak surveillance system designed and used in a COVID-19 community care facility (Preprint)

2020 ◽  
Author(s):  
Andrew Fang ◽  
Jonathan Kia-Sheng Phua ◽  
Terrence Chiew ◽  
Daniel De-Liang Loh ◽  
Lincoln Ming Han Liow ◽  
...  
Keyword(s):  
Open Source ◽  
Surveillance System ◽  
Community Care ◽  
Communicable Disease ◽  
Low Cost ◽  
Real Life ◽  
Disease Outbreak ◽  
Disease Spread ◽  
Healthcare Team ◽  
Increased Risk

BACKGROUND During the Coronavirus Disease 2019 (COVID-19) outbreak, community care facilities (CCF) were set up as temporary out-of-hospital isolation facilities to contain the surge of cases in Singapore. Confined living spaces within CCFs posed an increased risk of communicable disease spread among residents. OBJECTIVE This inspired our healthcare team managing a CCF operation to design a low-cost communicable disease outbreak surveillance system (CDOSS). METHODS Our CDOSS was designed with the following considerations: (1) comprehensiveness, (2) efficiency through passive reconnoitering from electronic medical record (EMR) data, (3) ability to provide spatiotemporal insights, (4) low-cost and (5) ease of use. We used Python to develop a lightweight application – Python-based Communicable Disease Outbreak Surveillance System (PyDOSS) – that was able perform syndromic surveillance and fever monitoring. With minimal user actions, its data pipeline would generate daily control charts and geospatial heat maps of cases from raw EMR data and logged vital signs. PyDOSS was successfully implemented as part of our CCF workflow. We also simulated a gastroenteritis (GE) outbreak to test the effectiveness of the system. RESULTS PyDOSS was used throughout the entire duration of operation; the output was reviewed daily by senior management. No disease outbreaks were identified during our medical operation. In the simulated GE outbreak, PyDOSS was able to effectively detect an outbreak within 24 hours and provided information about cluster progression which could aid in contact tracing. The code for a stock version of PyDOSS has been made publicly available. CONCLUSIONS PyDOSS is an effective surveillance system which was successfully implemented in a real-life medical operation. With the system developed using open-source technology and the code made freely available, it significantly reduces the cost of developing and operating CDOSS and may be useful for similar temporary medical operations, or in resource-limited settings.

scholarly journals Identification of effective spreaders in contact networks using dynamical influence

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruaridh A. Clark ◽  
Malcolm Macdonald
Keyword(s):  
Disease Transmission ◽  
Average Rate ◽  
Laplacian Matrix ◽  
Disease Spread ◽  
Eigenvector Centrality ◽  
Contact Networks ◽  
Human Contact ◽  
Spread Dynamics ◽  
Definition Of ◽  
High Degree

AbstractContact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network’s structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.

scholarly journals Host size and proximity to diseased neighbours drive the spread of a coral disease outbreak in Hawai‘i

2018 ◽  
Vol 285 (1870) ◽  
pp. 20172265 ◽  
Author(s):  
Jamie M. Caldwell ◽  
Megan J. Donahue ◽  
C. Drew Harvell
Keyword(s):  
Disease Risk ◽  
Coral Disease ◽  
Disease Outbreaks ◽  
Disease Outbreak ◽  
Host Size ◽  
Disease Spread ◽  
Wildlife Diseases ◽  
Infectious Individual ◽  
Force Of Infection ◽  
Affected Tissue

Understanding how disease risk varies over time and across heterogeneous populations is critical for managing disease outbreaks, but this information is rarely known for wildlife diseases. Here, we demonstrate that variation in host and pathogen factors drive the direction, duration and intensity of a coral disease outbreak. We collected longitudinal health data for 200 coral colonies, and found that disease risk increased with host size and severity of diseased neighbours, and disease spread was highest among individuals between 5 and 20 m apart. Disease risk increased by 2% with every 10 cm increase in host size. Healthy colonies with severely diseased neighbours (greater than 75% affected tissue) were 1.6 times more likely to develop disease signs compared with colonies with moderately diseased neighbours (25–75% affected tissue). Force of infection ranged from 7 to 20 disease cases per 1000 colonies (mean = 15 cases per 1000 colonies). The effective reproductive ratio, or average number of secondary infections per infectious individual, ranged from 0.16 to 1.22. Probability of transmission depended strongly on proximity to diseased neighbours, which demonstrates that marine disease spread can be highly constrained within patch reefs.

Dynamics of Consumer-Resource Systems

2013 ◽  
Author(s):  
André M. de Roos ◽  
Lennart Persson
Keyword(s):  
Model Organism ◽  
Growth Dynamics ◽  
Population Cycles ◽  
Food Density ◽  
Juvenile Period ◽  
Ecological Processes ◽  
Resource Dynamics ◽  
Cladoceran Zooplankton ◽  
The Individual ◽  
Consumer Resource

This chapter focuses on consumer-resource dynamics in systems where consumers of different sizes compete for a shared resource. It considers the implications of three important aspects of consumer life history: the explicit handling of a juvenile period leading to a delay between the time when an individual is born to when it starts to reproduce; the rate by which individual ecological processes scale with body size; and whether the rate by which the individual grows is dependent on food density or not. The chapter examines the effects of different resource growth dynamics to illustrate the fundamental differences between population cycles driven by interactions between individuals of different sizes, and classical predator–prey cycles driven by interactions between the consumer and the resource, also referred to as paradox of enrichment cycles. It also discusses experiments with the model organism, the cladoceran zooplankton Daphnia, to elucidate our current understanding of cycles driven by cohort interactions in this organism.

scholarly journals Defying the Footprint Oracle: Implications of Country Resource Trends

2019 ◽  
Vol 11 (7) ◽  
pp. 2164 ◽  
Author(s):  
Mathis Wackernagel ◽  
David Lin ◽  
Mikel Evans ◽  
Laurel Hanscom ◽  
Peter Raven
Keyword(s):  
International Development ◽  
Low Income ◽  
Economic Performance ◽  
Analysis Data ◽  
Low Income Countries ◽  
Data Sets ◽  
Economic Policies ◽  
Economic Implications ◽  
Financial Assessment ◽  
Resource Dynamics

Mainstream competitiveness and international development analyses pay little attention to the significance of a country’s resource security for its economic performance. This paper challenges this neglect, examining the economic implications of countries resource dynamics, particularly for low-income countries. It explores typologies of resource patterns in the context of those countries’ economic prospects. To begin, the paper explains why it uses Ecological Footprint and biocapacity accounting for its analysis. Data used for the analysis stem from Global Footprint Network’s 2018 edition of its National Footprint and Biocapacity Accounts. Ranging from 1961 to 2014, these accounts are computed from UN data sets. The accounts track, year by year, how much biologically productive space is occupied by people’s consumption and compare this with how much productive space is available. Both demand and availability are expressed in productivity-adjusted hectares, called global hectares. Using this biophysical accounting perspective, the paper predicts countries’ future socio-economic performance. This analysis is then contrasted with a financial assessment of those countries. The juxtaposition reveals a paradox: Financial assessments seem to contradict assessments based on biophysical trends. The paper offers a way to reconcile this paradox, which also elevates the significance of biophysical country assessments for shaping successful economic policies.

Asymptotic Analysis of an Age-Structured HIV Infection Model with Logistic Target-Cell Growth and Two Infecting Routes

2020 ◽  
Vol 30 (04) ◽  
pp. 2050059
Author(s):  
Dongxue Yan ◽  
Xianlong Fu
Keyword(s):  
Steady State ◽  
Hiv Infection ◽  
Logistic Growth ◽  
Infection Model ◽  
Target Cells ◽  
Cell Infection ◽  
Numerical Examples ◽  
Distribution Of Eigenvalues ◽  
Age Structured ◽  
Hiv Infection Model

This paper deals with an age-structured HIV infection model with logistic growth for target cells and both virus-to-cell and cell-to-cell infection routes. Based on the existence of the infection-free and infection equilibria and some rigorous analyses for the considered model, we study the asymptotic stability of these equilibria via determining the distribution of eigenvalues. We also address the persistence of the solution semi-flow by proving the existence of a global attractor. Furthermore, Hopf bifurcation occurring at the positive steady state is exploited. At last, some numerical examples are provided to illustrate the obtained results.

scholarly journals Disease spread in age structured populations with maternal age effects

2017 ◽  
Vol 20 (4) ◽  
pp. 445-451 ◽  
Author(s):  
Jessica Clark ◽  
Jennie S. Garbutt ◽  
Luke McNally ◽  
Tom J. Little
Keyword(s):  
Maternal Age ◽  
Age Effects ◽  
Structured Populations ◽  
Disease Spread ◽  
Age Structured

scholarly journals Self-Limiting Factors in Pandemics and Multi-Disease Syndemics

2018 ◽  
Author(s):  
David Manheim
Keyword(s):  
Infectious Disease ◽  
Disease Outbreak ◽  
Disease Spread ◽  
Limiting Factors ◽  
Disease Models ◽  
Human History ◽  
Infectious Disease Outbreak ◽  
Seir Model ◽  
Link Type ◽  
Infectious Disease Models

AbstractThe potential for an infectious disease outbreak that is much worse than those which have been observed in human history, whether engineered or natural, has been the focus of significant concern in biosecurity. Fundamental dynamics of disease spread make such outbreaks much less likely than they first appear. Here we present a slightly modified formulation of the typical SEIR model that illustrates these dynamics more clearly, and shows the unlikely cases where concern may still be warranted. This is then applied to an extreme version of proposed pandemic risk, multi-disease syndemics, to show that (absent much clearer reasons for concern) the suggested dangers are overstated.The models used in this paper are available here: https://github.com/davidmanheim/Infectious-Disease-Models

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