scholarly journals Resolving the impact of waiting time distributions on the persistence of measles

2009 ◽  
Vol 7 (45) ◽  
pp. 623-640 ◽  
Author(s):  
Andrew J. K. Conlan ◽  
Pejman Rohani ◽  
Alun L. Lloyd ◽  
Matthew Keeling ◽  
Bryan T. Grenfell
Keyword(s):  
Waiting Time ◽  
Population Biology ◽  
Stochastic Dynamics ◽  
Theoretical Models ◽  
Human Populations ◽  
Community Size ◽  
Spatial Coupling ◽  
Statistical Measures ◽  
Population Sizes ◽  
The Impact

Measles epidemics in human populations exhibit what is perhaps the best empirically characterized, and certainly the most studied, stochastic persistence threshold in population biology. A critical community size (CCS) of around 250 000–500 000 separates populations where measles is predominantly persistent from smaller communities where there are frequent extinctions of measles between major epidemics. The fundamental mechanisms contributing to this pattern of persistence, which are long-lasting immunity to re-infection, recruitment of susceptibles, seasonality in transmission, age dependence of transmission and the spatial coupling between communities, have all been quantified and, to a greater or lesser level of success, captured by theoretical models. Despite these successes there has not been a consensus over whether simple models can successfully predict the value of the CCS, or indeed which mechanisms determine the persistence of measles over a broader range of population sizes. Specifically, the level of the CCS has been thought to be particularly sensitive to the detailed stochastic dynamics generated by the waiting time distribution (WTD) in the infectious and latent periods. We show that the relative patterns of persistence between models with different WTDs are highly sensitive to the criterion of comparison—in particular, the statistical measure of persistence that is employed. To this end, we introduce two new statistical measures of persitence—fade-outs post epidemic and fade-outs post invasion. Contrary to previous reports, we demonstrate that, no matter the choice of persistence measure, appropriately parametrized models of measles demonstrate similar predictions for the level of the CCS.

scholarly journals Interconnections Accelerate Collapse in a Socio-Ecological Metapopulation

2019 ◽  
Vol 11 (7) ◽  
pp. 1852 ◽  
Author(s):  
Zachary Dockstader ◽  
Chris Bauch ◽  
Madhur Anand
Keyword(s):  
Theoretical Models ◽  
Ecological Sustainability ◽  
Human Populations ◽  
Metapopulation Model ◽  
Single Population ◽  
Metapopulation Structure ◽  
Model Dynamics ◽  
Simplifying Assumptions ◽  
Over Exploitation ◽  
The Impact

Over-exploitation of natural resources can have profound effects on both ecosystems and their resident human populations. Simple theoretical models of the dynamics of a population of human harvesters and the abundance of a natural resource being harvested have been studied previously, but relatively few models consider the effect of metapopulation structure (i.e., a population distributed across discrete patches). Here we analyze a socio-ecological metapopulation model based on an existing single-population model used to study persistence and collapse in human populations. Resources grow logistically on each patch. Each population harvests resources on its own patch to support population growth, but can also harvest resources from other patches when their own patch resources become scarce. We show that when populations are allowed to harvest resources from other patches, the peak population size is higher, but subsequent population collapse is significantly accelerated and across a broader parameter regime. As the number of patches in the metapopulation increases, collapse is more sudden, more severe, and occurs sooner. These effects persist under scenarios of asymmetry and inequality between patches. Our model makes simplifying assumptions in order to facilitate insight and understanding of model dynamics. However, the robustness of the model prediction suggests that more sophisticated models should be developed to ascertain the impact of metapopulation structure on socio-ecological sustainability.

scholarly journals INCLUSIVE HEALTH: MODELING COVID-19 IN CORRECTIONAL FACILITIES AND COMMUNITIES

2021 ◽  
Author(s):  
Scott Greenhalgh ◽  
Ashley Provencher
Keyword(s):  
Disease Transmission ◽  
Local Community ◽  
Health Resources ◽  
Correctional Facilities ◽  
Community Size ◽  
Infected People ◽  
Population Sizes ◽  
Incarcerated Population ◽  
State Prisons ◽  
The Impact

Mass incarceration, commonly associated with overcrowding and inadequate health resources for incarcerated people, creates a fertile environment for the spread of the coronavirus disease 2019 (COVID-19) in U.S. correctional facilities. The exact role that correctional facilities play in enhancing COVID-19 spread and enabling community re-emergence of COVID-19 is unknown. We constructed a novel stochastic model of COVID-19 transmission to estimate the impact of correctional facilities, specifically jails and state prisons, for enhancing disease transmission and enabling disease re-emergence in local communities. Using our model, we evaluated scenarios of testing and quarantining infected incarcerated people at 0.0, 0.5, and 1.0 times the rate that occurs for infected people in the local community for population sizes of 5, 10, and 20 thousand people. Our results illustrate testing and quarantining an incarcerated population of 800 would reduce the probability of a major community outbreak by 6% and also prevent between 250 to 730 incidences of COVID-19 per year, depending on local community size. These findings illustrate that managing COVID-19 in correctional facilities is essential to mitigate risks to community health, and thereby stresses the importance of improving the health standards of incarcerated people.

scholarly journals CAN CULLING TO PREVENT MONKEYPOX INFECTION BE COUNTER-PRODUCTIVE? SCENARIOS FROM A THEORETICAL MODEL

2012 ◽  
Vol 20 (03) ◽  
pp. 259-283 ◽  
Author(s):  
JEAN M. TCHUENCHE ◽  
CHRIS T. BAUCH
Keyword(s):  
Control Strategies ◽  
Theoretical Models ◽  
Transmission Model ◽  
Human Populations ◽  
Contact Rate ◽  
Disease Dynamics ◽  
Human Contact ◽  
Animal Populations ◽  
The Impact ◽  
Animal Reservoirs

In the last two decades, monkeypox outbreaks in human populations in Africa and North America have reminded us that smallpox is not the only poxvirus with potential to cause harm in human populations. Monkeypox transmission is sustained in animal reservoirs, and animal–human contacts are responsible for sporadic outbreaks in humans. Here, we develop and analyze a deterministic epizootic (animal-based) transmission model capturing disease dynamics in an animal population, disease dynamics in an age-structured human population, and their coupling through animal–human contacts. We develop a single-patch model as well as a two-patch meta-population extension. We derive mathematical expressions for the basic reproduction number, which governs the likelihood of a large outbreak. We also investigate the effectiveness of culling strategies and the impact of changes in the animal–human contact rate. Numerical analysis of the model suggests that, for some parameter values, culling can actually have the counter-productive outcome of increasing monkeypox infection in children, if animal reproduction is a density-dependent process. The likelihood of this happening, as well as the prevalence of monkeypox in humans, depends sensitively on the animal–human contact rate. We also find that ignoring age structure in human populations can lead to overestimating the transmissibility of monkeypox in humans. The effectiveness of monkeypox control strategies such as culling can strongly depend on the details of demography and epidemiology in the animal reservoirs that sustain it. Therefore, to better understand how to prevent and control monkeypox outbreaks in humans, better empirical data from wild animal populations where monkeypox is endemic must be collected, and these data must be incorporated into highly structured theoretical models.

The Effects of Employment Protection legislationon Personnel Policies: A Review of Theoretical Modelsand Empirical results

2014 ◽  
pp. 126-140
Author(s):  
O. Mironenko
Keyword(s):  
Personnel Selection ◽  
Selection Criteria ◽  
Theoretical Models ◽  
Employment Protection ◽  
Empirical Results ◽  
Protection Legislation ◽  
Labour Contracts ◽  
Hiring And Firing ◽  
The Impact ◽  
Personnel Policies

Employers incur costs while fulfilling the requirements of employment protection legislation. The article contains a review of the core theoretical models and empirical results concerning the impact of these costs on firms’ practices in hiring, firing, training and remuneration. Overall, if wages are flexible or enforcement is weak, employment protection does not significantly influence employers’ behavior. Otherwise, stringent employment protection results in the reduction of hiring and firing rates, changes in personnel selection criteria, types of labour contracts and dismissal procedures, and, in some cases, it may lead to the growth of wages and firms’ investments to human capital.

Characterizing the impact of recovering sea otters on commercially important crabs in California estuaries

2020 ◽  
Vol 655 ◽  
pp. 123-137
Author(s):  
TM Grimes ◽  
MT Tinker ◽  
BB Hughes ◽  
KE Boyer ◽  
L Needles ◽  
...  
Keyword(s):  
Abiotic Factors ◽  
Sea Otter ◽  
Dungeness Crab ◽  
Sea Otters ◽  
Elkhorn Slough ◽  
Enhydra Lutris Nereis ◽  
Crab Abundance ◽  
Population Sizes ◽  
Commercially Important ◽  
The Impact

Protective legislation and management have led to an increase in California’s sea otter Enhydra lutris nereis population. While sea otter recovery has been linked to ecosystem benefits, sea otter predation may negatively affect commercially valuable species. Understanding the potential influence of sea otters is of particular importance as their range expands into estuaries that function as nurseries for commercially valuable species like Dungeness crab Metacarcinus magister. We consider how sea otter predation has affected the abundance and size of juvenile Dungeness crab in Elkhorn Slough, California, USA, and analyzed cancrid crab abundance and size across 4 California estuaries with and without sea otters to understand how biotic and abiotic factors contribute to observed variation in crab size and abundance. We compared trends in southern sea otters relative to Dungeness crab landings in California to assess whether increasing sea otter abundance have negatively impacted landings. In Elkhorn Slough, juvenile Dungeness crab abundance and size have declined since 2012, coinciding with sea otter population growth. However, the impact of sea otters on juvenile Dungeness crab size was habitat-specific and only significant in unvegetated habitat. Across estuaries, we found that cancrid crab abundance and size were negatively associated with sea otter presence. While abiotic factors varied among estuaries, these factors explained little of the observed variation in crab abundance or size. Although we found evidence that sea otters can have localized effects on cancrid crab populations within estuaries, we found no evidence that southern sea otters, at recent population sizes, have negatively impacted Dungeness crab landings in California from 2000-2014.

scholarly journals The Impact of Health Policies and Sociodemographic Factors on Doubling Time of the COVID-19 Pandemic in Mexico

2021 ◽  
Vol 18 (5) ◽  
pp. 2354
Author(s):  
Lina Díaz-Castro ◽  
Héctor Cabello-Rangel ◽  
Kurt Hoffman
Keyword(s):  
Population Density ◽  
Doubling Time ◽  
Sociodemographic Factors ◽  
Health Policies ◽  
Government Response ◽  
University Of Oxford ◽  
Negative Effect ◽  
Population Sizes ◽  
The University ◽  
The Impact

Background. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. Methods. A retrospective longitudinal study was carried out across March–August, 2020. Policies issued by each of the 32 Mexican states during each week of this period were classified according to the University of Oxford Coronavirus Government Response Tracker (OxCGRT), and the doubling time of COVID-19 cases was calculated. Additionally, variables such as population size and density, poverty and mobility were included. A panel data model was applied to measure the effect of these variables on doubling time. Results. States with larger population sizes issued a larger number of policies. Delay in the issuance of policies was associated with accelerated propagation. The policy index (coefficient 0.60, p < 0.01) and the income per capita (coefficient 3.36, p < 0.01) had a positive effect on doubling time; by contrast, the population density (coefficient −0.012, p < 0.05), the mobility in parks (coefficient −1.10, p < 0.01) and the residential mobility (coefficient −4.14, p < 0.01) had a negative effect. Conclusions. Health policies had an effect on slowing the pandemic’s propagation, but population density and mobility played a fundamental role. Therefore, it is necessary to implement policies that consider these variables.

scholarly journals The Impact of Longer Consultation Time: A Simulation-Based Approach

2020 ◽  
Vol 11 (05) ◽  
pp. 857-864
Author(s):  
Abdulrahman M. Jabour
Keyword(s):  
Waiting Time ◽  
Quality Care ◽  
Working Hours ◽  
Discrete Events ◽  
Simulation Based ◽  
Patient Waiting Time ◽  
Free Environment ◽  
The Impact ◽  
Consultation Time ◽  
Patient Waiting

Abstract Background Maintaining a sufficient consultation length in primary health care (PHC) is a fundamental part of providing quality care that results in patient safety and satisfaction. Many facilities have limited capacity and increasing consultation time could result in a longer waiting time for patients and longer working hours for physicians. The use of simulation can be practical for quantifying the impact of workflow scenarios and guide the decision-making. Objective To examine the impact of increasing consultation time on patient waiting time and physician working hours. Methods Using discrete events simulation, we modeled the existing workflow and tested five different scenarios with a longer consultation time. In each scenario, we examined the impact of consultation time on patient waiting time, physician hours, and rate of staff utilization. Results At baseline scenarios (5-minute consultation time), the average waiting time was 9.87 minutes and gradually increased to 89.93 minutes in scenario five (10 minutes consultation time). However, the impact of increasing consultation time on patients waiting time did not impact all patients evenly where patients who arrive later tend to wait longer. Scenarios with a longer consultation time were more sensitive to the patients' order of arrival than those with a shorter consultation time. Conclusion By using simulation, we assessed the impact of increasing the consultation time in a risk-free environment. The increase in patients waiting time was somewhat gradual, and patients who arrive later in the day are more likely to wait longer than those who arrive earlier in the day. Increasing consultation time was more sensitive to the patients' order of arrival than those with a shorter consultation time.

Systematic benchmark of ancient DNA read mapping

2021 ◽  
Author(s):  
Adrien Oliva ◽  
Raymond Tobler ◽  
Alan Cooper ◽  
Bastien Llamas ◽  
Yassine Souilmi
Keyword(s):  
Ancient Dna ◽  
Dna Sequences ◽  
Population Genetic ◽  
Reference Genome ◽  
Population Data ◽  
Human Populations ◽  
Current Standard ◽  
Read Mapping ◽  
Reference Bias ◽  
The Impact

Abstract The current standard practice for assembling individual genomes involves mapping millions of short DNA sequences (also known as DNA ‘reads’) against a pre-constructed reference genome. Mapping vast amounts of short reads in a timely manner is a computationally challenging task that inevitably produces artefacts, including biases against alleles not found in the reference genome. This reference bias and other mapping artefacts are expected to be exacerbated in ancient DNA (aDNA) studies, which rely on the analysis of low quantities of damaged and very short DNA fragments (~30–80 bp). Nevertheless, the current gold-standard mapping strategies for aDNA studies have effectively remained unchanged for nearly a decade, during which time new software has emerged. In this study, we used simulated aDNA reads from three different human populations to benchmark the performance of 30 distinct mapping strategies implemented across four different read mapping software—BWA-aln, BWA-mem, NovoAlign and Bowtie2—and quantified the impact of reference bias in downstream population genetic analyses. We show that specific NovoAlign, BWA-aln and BWA-mem parameterizations achieve high mapping precision with low levels of reference bias, particularly after filtering out reads with low mapping qualities. However, unbiased NovoAlign results required the use of an IUPAC reference genome. While relevant only to aDNA projects where reference population data are available, the benefit of using an IUPAC reference demonstrates the value of incorporating population genetic information into the aDNA mapping process, echoing recent results based on graph genome representations.

scholarly journals Transport Properties of Natural and Artificial Smart Fabrics Impregnated by Graphite Nanomaterial Stacks

Nanomaterials ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1018
Author(s):  
Carola Esposito Corcione ◽  
Francesca Ferrari ◽  
Raffaella Striani ◽  
Antonio Greco
Keyword(s):  
Electrical Conductivity ◽  
Transport Properties ◽  
Low Cost ◽  
Empirical Relationship ◽  
Theoretical Models ◽  
Expandable Graphite ◽  
Easy Method ◽  
Textile Materials ◽  
Fabric Materials ◽  
The Impact

In this work, we studied the transport properties (thermal and electrical conductivity) of smart fabric materials treated with graphite nanomaterial stacks–acetone suspensions. An innovative and easy method to produce graphite nanomaterial stacks–acetone-based formulations, starting from a low-cost expandable graphite, is proposed. An original, economical, fast, and easy method to increase the thermal and electrical conductivity of textile materials was also employed for the first time. The proposed method allows the impregnation of smart fabric materials, avoiding pre-coating of the fibers, thus reducing costs and processing time, while obtaining a great increase in the transport properties. Two kinds of textiles, cotton and Lycra®, were selected as they represent the most used natural and artificial fabrics, respectively. The impact of the dimensions of the produced graphite nanomaterial stacks–acetone-based suspensions on both the uniformity of the treatment and the transport properties of the selected textile materials was accurately evaluated using several experimental techniques. An empirical relationship between the two transport properties was also successfully identified. Finally, several theoretical models were applied to predict the transport properties of the developed smart fabric materials, evidencing a good agreement with the experimental data.

Sign in / Sign up

Export Citation Format

Share Document