scholarly journals A multi-scale epidemic model of Salmonella infection with heterogeneous shedding

2020 ◽  
Vol 67 ◽  
pp. 261-284
Author(s):  
Simon Labarthe ◽  
Béatrice Laroche ◽  
Thi Nhu Tao Nguyen ◽  
Bastien Polizzi ◽  
Florian Patout ◽  
...  
Keyword(s):  
Control Strategies ◽  
Food Poisoning ◽  
Population Level ◽  
Pathogen Transmission ◽  
Modeling Framework ◽  
Multi Scale ◽  
Multiscale Modeling Framework ◽  
The Individual ◽  
Random Fluctuations ◽  
The Impact

Salmonella strains colonize the digestive tract of farm livestock, such as chickens or pigs, without affecting them, and potentially infect food products, representing a threat for human health ranging from food poisoning to typhoid fever. It has been shown that the ability to excrete the pathogen in the environment and contaminate other animals is variable. This heterogeneity in pathogen carriage and shedding results from interactions between the host’s immune response, the pathogen and the commensal intestinal microbiota. In this paper we propose a novel generic multiscale modeling framework of heterogeneous pathogen transmission in an animal population. At the intra-host level, the model describes the interaction between the commensal microbiota, the pathogen and the inflammatory response. Random fluctuations in the ecological dynamics of the individual microbiota and transmission at between-host scale are added to obtain a drift-diffusion PDE model of the pathogen distribution at the population level. The model is further extended to represent transmission between several populations. The asymptotic behavior as well as the impact of control strategies including cleaning and antimicrobial administration are investigated through numerical simulation.

A multi-scale cholera model linking between-host and within-host dynamics

2018 ◽  
Vol 11 (03) ◽  
pp. 1850034
Author(s):  
Chayu Yang ◽  
Drew Posny ◽  
Feng Bao ◽  
Jin Wang
Keyword(s):  
Human Body ◽  
Population Level ◽  
Sir Model ◽  
Disease Dynamics ◽  
Modeling Framework ◽  
Multi Scale ◽  
Scale Modeling ◽  
Individual Host ◽  
Multi Scale Modeling ◽  
The Individual

We propose a multi-scale modeling framework to investigate the transmission dynamics of cholera. At the population level, we employ a SIR model for the between-host transmission of the disease. At the individual host level, we describe the evolution of the pathogen within the human body. The between-host and within-host dynamics are connected through an environmental equation that characterizes the growth of the pathogen and its interaction with the hosts outside the human body. We put a special emphasis on the within-host dynamics by making a distinction for each individual host. We conduct both mathematical analysis and numerical simulation for our model in order to explore various scenarios associated with cholera transmission and to better understand the complex, multi-scale disease dynamics.

Introduction to pertussis transmission and epidemiological dynamics

Pertussis ◽  
2018 ◽  
pp. 6-25
Author(s):  
Pejman Rohani ◽  
Samuel V. Scarpino
Keyword(s):  
Control Strategies ◽  
Age Distribution ◽  
Population Level ◽  
Vaccine Uptake ◽  
Effective Control ◽  
Transmission Potential ◽  
Epidemic Period ◽  
The Impact ◽  
Pertussis Epidemiology

Resolving the long-term, population-level consequences of changes in pertussis epidemiology, arising from bacterial evolution, shifts in vaccine-induced immunity, or changes in surveillance, are key challenges for devising effective control strategies. This chapter reviews some of the key features of pertussis epidemiology, together with the underlying epidemiological principles that set the context for their interpretation. These include the relationship between the age distribution of cases and pertussis transmission potential, the impact of vaccine uptake on incidence, periodicity and age incidence, as well as spatially explicit recurrent pertussis epidemics and associated extinction frequency. This review highlights some of the predictable and consistent aspects of pertussis epidemiology (e.g. the systematic increase in the inter-epidemic period with the introduction of whole-cell vaccines) and a number of important heterogeneities, including variations in contemporary patterns of incidence and geographic spread.

scholarly journals Analyzing 24-Hour Blood Pressure Measurements with a Novel Cuffless Pulse Transit Time Device in Clinical Practice—Does the Software for Heartbeat Detection Matter?

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 361
Author(s):  
Leo Kilian ◽  
Philipp Krisai ◽  
Thenral Socrates ◽  
Christian Arranto ◽  
Otmar Pfister ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Population Level ◽  
Raw Data ◽  
Invasive Blood Pressure ◽  
Individual Level ◽  
Non Invasive ◽  
The Individual ◽  
The Impact

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.

scholarly journals Maximizing and evaluating the impact of test-trace-isolate programs: A modeling study

PLoS Medicine ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. e1003585
Author(s):  
Kyra H. Grantz ◽  
Elizabeth C. Lee ◽  
Lucy D’Agostino McGowan ◽  
Kyu Han Lee ◽  
C. Jessica E. Metcalf ◽  
...  
Keyword(s):  
Control Strategies ◽  
R Package ◽  
Sensitivity Analyses ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Case Detection ◽  
Modeling Framework ◽  
Online Application ◽  
Almost All ◽  
The Impact

Background Test-trace-isolate programs are an essential part of Coronavirus Disease 2019 (COVID-19) control that offer a more targeted approach than many other nonpharmaceutical interventions. Effective use of such programs requires methods to estimate their current and anticipated impact. Methods and findings We present a mathematical modeling framework to evaluate the expected reductions in the reproductive number, R, from test-trace-isolate programs. This framework is implemented in a publicly available R package and an online application. We evaluated the effects of completeness in case detection and contact tracing and speed of isolation and quarantine using parameters consistent with COVID-19 transmission (R0: 2.5, generation time: 6.5 days). We show that R is most sensitive to changes in the proportion of cases detected in almost all scenarios, and other metrics have a reduced impact when case detection levels are low (<30%). Although test-trace-isolate programs can contribute substantially to reducing R, exceptional performance across all metrics is needed to bring R below one through test-trace-isolate alone, highlighting the need for comprehensive control strategies. Results from this model also indicate that metrics used to evaluate performance of test-trace-isolate, such as the proportion of identified infections among traced contacts, may be misleading. While estimates of the impact of test-trace-isolate are sensitive to assumptions about COVID-19 natural history and adherence to isolation and quarantine, our qualitative findings are robust across numerous sensitivity analyses. Conclusions Effective test-trace-isolate programs first need to be strong in the “test” component, as case detection underlies all other program activities. Even moderately effective test-trace-isolate programs are an important tool for controlling the COVID-19 pandemic and can alleviate the need for more restrictive social distancing measures.

scholarly journals Multi-scale immunoepidemiological modeling of within-host and between-host HIV dynamics: systematic review of mathematical models

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3877 ◽  
Author(s):  
Nargesalsadat Dorratoltaj ◽  
Ryan Nikin-Beers ◽  
Stanca M. Ciupe ◽  
Stephen G. Eubank ◽  
Kaja M. Abbas
Keyword(s):  
Systematic Review ◽  
Population Level ◽  
Transmission Dynamics ◽  
Time Varying ◽  
Individual Level ◽  
Multi Scale ◽  
Hiv Dynamics ◽  
Single Scale ◽  
Scale Models ◽  
The Individual

Objective The objective of this study is to conduct a systematic review of multi-scale HIV immunoepidemiological models to improve our understanding of the synergistic impact between the HIV viral-immune dynamics at the individual level and HIV transmission dynamics at the population level. Background While within-host and between-host models of HIV dynamics have been well studied at a single scale, connecting the immunological and epidemiological scales through multi-scale models is an emerging method to infer the synergistic dynamics of HIV at the individual and population levels. Methods We reviewed nine articles using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework that focused on the synergistic dynamics of HIV immunoepidemiological models at the individual and population levels. Results HIV immunoepidemiological models simulate viral immune dynamics at the within-host scale and the epidemiological transmission dynamics at the between-host scale. They account for longitudinal changes in the immune viral dynamics of HIV+ individuals, and their corresponding impact on the transmission dynamics in the population. They are useful to analyze the dynamics of HIV super-infection, co-infection, drug resistance, evolution, and treatment in HIV+ individuals, and their impact on the epidemic pathways in the population. We illustrate the coupling mechanisms of the within-host and between-host scales, their mathematical implementation, and the clinical and public health problems that are appropriate for analysis using HIV immunoepidemiological models. Conclusion HIV immunoepidemiological models connect the within-host immune dynamics at the individual level and the epidemiological transmission dynamics at the population level. While multi-scale models add complexity over a single-scale model, they account for the time varying immune viral response of HIV+ individuals, and the corresponding impact on the time-varying risk of transmission of HIV+ individuals to other susceptibles in the population.

scholarly journals The Normative Underpinnings of Population-Level Alcohol Use: An Individual-Level Simulation Model

2020 ◽  
Vol 47 (2) ◽  
pp. 224-234
Author(s):  
Charlotte Probst ◽  
Tuong Manh Vu ◽  
Joshua M. Epstein ◽  
Alexandra E. Nielsen ◽  
Charlotte Buckley ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Social Norms ◽  
Drinking Behavior ◽  
Population Level ◽  
Drinking Patterns ◽  
Individual Level ◽  
Behavioral Rules ◽  
Level Model ◽  
The Individual ◽  
The Impact

Background. By defining what is “normal,” appropriate, expected, and unacceptable, social norms shape human behavior. However, the individual-level mechanisms through which social norms impact population-level trends in health-relevant behaviors are not well understood. Aims. To test the ability of social norms mechanisms to predict changes in population-level drinking patterns. Method. An individual-level model was developed to simulate dynamic normative mechanisms and behavioral rules underlying drinking behavior over time. The model encompassed descriptive and injunctive drinking norms and their impact on frequency and quantity of alcohol use. A microsynthesis initialized in 1979 was used as a demographically representative synthetic U.S. population. Three experiments were performed in order to test the modelled normative mechanisms. Results. Overall, the experiments showed limited influence of normative interventions on population-level alcohol use. An increase in the desire to drink led to the most meaningful changes in the population’s drinking behavior. The findings of the experiments underline the importance of autonomy, that is, the degree to which an individual is susceptible to normative influence. Conclusion. The model was able to predict theoretically plausible changes in drinking patterns at the population level through the impact of social mechanisms. Future applications of the model could be used to plan norms interventions pertaining to alcohol use as well as other health behaviors.

scholarly journals African Gene Flow Reduces Beta-Ionone Anosmia/Hyposmia Prevalence in Admixed Malagasy Populations

2021 ◽  
Vol 11 (11) ◽  
pp. 1405
Author(s):  
Harilanto Razafindrazaka ◽  
Veronica Pereda-Loth ◽  
Camille Ferdenzi ◽  
Margit Heiske ◽  
Omar Alva ◽  
...  
Keyword(s):  
Gene Flow ◽  
African Ancestry ◽  
Sensory Perception ◽  
Population Level ◽  
P Value ◽  
Individual Level ◽  
Specific Anosmia ◽  
Odorant Molecule ◽  
The Individual ◽  
The Impact

While recent advances in genetics make it possible to follow the genetic exchanges between populations and their phenotypic consequences, the impact of the genetic exchanges on the sensory perception of populations has yet to be explored. From this perspective, the present study investigated the consequences of African gene flow on odor perception in a Malagasy population with a predominantly East Asian genetic background. To this end, we combined psychophysical tests with genotype data of 235 individuals who were asked to smell the odorant molecule beta-ionone (βI). Results showed that in this population the ancestry of the OR5A1 gene significantly influences the ability to detect βI. At the individual level, African ancestry significantly protects against specific anosmia/hyposmia due to the higher frequency of the functional gene (OR ratios = 14, CI: 1.8–110, p-value = 0.012). At the population level, African introgression decreased the prevalence of specific anosmia/hyposmia to this odorous compound. Taken together, these findings validate the conjecture that in addition to cultural exchanges, genetic transfer may also influence the sensory perception of the population in contact.

scholarly journals Endocrine disruption in wildlife: The future?

2003 ◽  
Vol 75 (11-12) ◽  
pp. 2355-2360 ◽  
Author(s):  
J. P. Sumpter
Keyword(s):  
Endocrine Disruption ◽  
Sewage Treatment ◽  
Population Level ◽  
Paper Mill ◽  
Individual Organism ◽  
Paper Mill Effluent ◽  
The Future ◽  
Over Exploitation ◽  
The Individual ◽  
The Impact

Probably the only thing that can be said with certainty about the future of this field of ecotoxicology is that predicting it is foolish; the chances of being right are very slim. Instead, it seems to me likely that unexpected discoveries will probably have more influence on the field of endocrine disruption than the outcomes of all the planned experiments. It is certainly true that chance discoveries, such as masculinized fish in rivers receiving paper-mill effluent, imposex in molluscs due to exposure to tributyltin and feminized fish in rivers receiving effluent from sewage-treatment works, have been pivotal in the development of the field of endocrine disruption in wildlife. I consider that further such discoveries are likely, but I do not know which species will be affected, what effects will be found, what chemical(s) will be the cause, or what endocrine mechanism(s) will underlie the effects. The recent realization that many pharmaceuticals are present in the aquatic environment only underscores the range of effects that could, in theory at least, occur in exposed wildlife. What is somewhat easier to predict is the research that will be conducted in the immediate future, which will build upon what is known already. For example, it is clear that wildlife is rarely, if ever, exposed to single chemicals, but instead is exposed to highly complex, ill-defined mixtures of chemicals, including many that are endocrine active in various ways. We need to understand much better how chemicals interact, and what overall effects will occur upon exposure to such mixtures. We also need to move from assessing effects at the individual organism level, to understanding the consequences of these effects at the population level. Then, we need to determine the significance of any population-level effects due to endocrine disruption in comparison with the impact of many other significant stressors (e.g., over-exploitation, habitat loss, climate change) that also negatively impact wildlife. Such research will be difficult, and time-consuming, and will probably produce many surprises. All I can be fairly certain about is that the next few years are likely to be as interesting and exciting as the last few have been.

Horizontal transmission of a parasite is influenced by infected host phenotype and density

Parasitology ◽  
2014 ◽  
Vol 142 (2) ◽  
pp. 395-405 ◽  
Author(s):  
K. E. ROBERTS ◽  
W. O. H. HUGHES
Keyword(s):  
Control Strategies ◽  
Horizontal Transmission ◽  
Population Level ◽  
Pathogen Transmission ◽  
Parasite Transmission ◽  
Microsporidian Parasite ◽  
Female Workers ◽  
Host Parasite Interactions ◽  
The Social ◽  
Host Parasite

SUMMARYTransmission is a key determinant of parasite fitness, and understanding the dynamics of transmission is fundamental to the ecology and evolution of host–parasite interactions. Successful transmission is often reliant on contact between infected individuals and susceptible hosts. The social insects consist of aggregated groups of genetically similar hosts, making them particularly vulnerable to parasite transmission. Here we investigate how the ratio of infected to susceptible individuals impacts parasite transmission, using the honey bee, Apis mellifera and its microsporidian parasite Nosema ceranae. We used 2 types of infected hosts found simultaneously in colonies; sterile female workers and sexual males. We found a higher ratio of infected to susceptible individuals in groups resulted in a greater proportion of susceptibles becoming infected, but this effect was non-linear and interestingly, the ratio also affected the spore production of infected individuals. The transmission level was much greater in an experiment where the infected individuals were drones than in an experiment where they were workers, suggesting drones may act as intracolonial ‘superspreaders’. Understanding the subtleties of transmission and how it is influenced by the phenotype of the infected/susceptible individuals is important for understanding pathogen transmission at population level, and for optimum targeting of parasite control strategies.

scholarly journals The impact of antiretroviral therapy on population-level virulence evolution of HIV-1

2015 ◽  
Vol 12 (113) ◽  
pp. 20150888 ◽  
Author(s):  
Hannah E. Roberts ◽  
Philip J. R. Goulder ◽  
Angela R. McLean
Keyword(s):  
Antiretroviral Therapy ◽  
Deterministic Model ◽  
Population Level ◽  
Threshold Condition ◽  
Virulence Evolution ◽  
Downward Pressure ◽  
The Individual ◽  
The Impact ◽  
Hiv 1

In HIV-infected patients, an individual's set point viral load (SPVL) strongly predicts disease progression. Some think that SPVL is evolving, indicating that the virulence of the virus may be changing, but the data are not consistent. In addition, the widespread use of antiretroviral therapy (ART) has the potential to drive virulence evolution. We develop a simple deterministic model designed to answer the following questions: what are the expected patterns of virulence change in the initial decades of an epidemic? Could administration of ART drive changes in virulence evolution and, what is the potential size and direction of this effect? We find that even without ART we would not expect monotonic changes in average virulence. Transient decreases in virulence following the peak of an epidemic are not necessarily indicative of eventual evolution to avirulence. In the short term, we would expect widespread ART to cause limited downward pressure on virulence. In the long term, the direction of the effect is determined by a threshold condition, which we define. We conclude that, given the surpassing benefits of ART to the individual and in reducing onward transmission, virulence evolution considerations need have little bearing on how we treat.

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