scholarly journals Counter-intuitive COVID-19 Trajectories - Explanations, Early Warning Indicator and Mitigation Strategies

2021 ◽  
Author(s):  
B Shayak ◽  
Mohit Manoj Sharma
Keyword(s):  
Social Interactions ◽  
Early Warning ◽  
Critical Mass ◽  
Mass Effect ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Epidemiological Models ◽  
Early Warning Indicator ◽  
Small Change ◽  
Parameter Values

The COVID-19 trajectories worldwide have shown several surprising features which are outside the purview of classical epidemiological models. These include (a) almost constant and low daily case rates over extended periods of time, (b) sudden waves emerging from the above solution despite no or minimal change in the level of non-pharmaceutical interventions (NPI), and (c) reduction or flattening of case counts following relaxation of NPI. To explain these phenomena, we add contact tracing to our recently developed cluster seeding and transmission (CST) model. We find no fewer than four effects which make prediction of epidemic trajectories uncertain. These are (a) cryptogenic instability, where a small increase in population-averaged contact rate causes a large increase in cases, (b) critical mass effect, where a wave manifests after weeks of quiescence with no change in parameter values, (c) knife-edge effect, where a small change in parameter across a critical value causes a huge change in the response of the system, and (d) hysteresis effect, where the timing and not just the strength of a particular NPI determines the subsequent behaviour. Despite these effects however, some non-obvious conclusions regarding NPI appear to be robust. In particular, (a) narrowing the circle of one's social interactions can be as effective a measure as reducing interactions altogether, and (b) a good contact tracing program can effectively substitute for much more invasive measures. Finally, we propose the contact tracing capacity ratio - a metric of the load to which the tracers are subject - as a reliable early warning indicator of an imminent epidemic wave.

scholarly journals A Cluster-based Model of COVID-19 Transmission Dynamics

2021 ◽  
Author(s):  
B Shayak ◽  
Mohit Manoj Sharma
Keyword(s):  
Preventive Measures ◽  
Critical Mass ◽  
Mass Effect ◽  
Spreading Rate ◽  
Epidemiological Models ◽  
Successful Management ◽  
Stochastic Effects ◽  
Discrete Population ◽  
Closed Groups ◽  
Case Rate

Many countries have manifested COVID-19 trajectories where extended periods of constant and low daily case rate suddenly transition to epidemic waves of considerable severity with no correspondingly drastic relaxation in preventive measures. Such solutions are outside the scope of classical epidemiological models. Here we construct a deterministic, discrete-time, discrete-population mathematical model which can explain these non-classical phenomena. Our key hypothesis is that with partial preventive measures in place, viral transmission occurs primarily within small, closed groups of family members and friends, which we call clusters. Inter-cluster transmission is infrequent compared to intra-cluster transmission but it is the key to determining the course of the epidemic. If inter-cluster transmission is low enough, we see stable plateau solutions. Above a cutoff level however, such transmission can destabilize a plateau into a huge wave even though its contribution to the population-averaged spreading rate still remains small. We call this the cryptogenic instability. We also find that stochastic effects when case counts are very low may result in a temporary and artificial suppression of an instability; we call this the critical mass effect. Both these phenomena are absent from conventional infectious disease models and militate against the successful management of the epidemic.

scholarly journals The Research of Coal and Gas Outburst Warning Based on Logistic Regression and Geographic Information System

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bo You ◽  
Bo Li ◽  
Shi Liang Shi ◽  
He Qing Liu ◽  
Yi Lu ◽  
...  
Keyword(s):  
Information System ◽  
Logistic Regression ◽  
Geographic Information System ◽  
Early Warning ◽  
Warning System ◽  
Indicator System ◽  
Geographic Information ◽  
Coal And Gas Outburst ◽  
Gas Outburst ◽  
Early Warning Indicator

Coal and gas outburst is one of the major disasters in the safety production of coal mine. According to the mechanism of coal and gas outburst, based on the comprehensive analysis of various influencing factors of coal and gas outburst, with the principles of selected early warning indicator, the basic information database of coal and gas outburst warning is constructed, and the information data query function is realized. The mathematical model of coal and gas outburst warning is established by the logistic regression analysis based on the gas concentration, the gas desorption index of drill cuttings, and the initial velocity of gas emission from the borehole. The multivariate information coupled warning was conducted according to the selected early warning indicator system, and the early warning level was divided with the result of early warning. The design and research of the coal and gas outburst warning system are carried out based on the geographic information system (GIS). The coal and gas outburst warning system was verified by taking the Tunliu mine of Lu’an Group as an example. The establishment of the early warning system is a new technical way to the early warning management of coal and gas outburst and can provide a guarantee for coal and gas outburst prevention.

Contact Tracing Applications Against COVID-19: A Systematic Review (Preprint)

2021 ◽  
Author(s):  
Ahmad Nabeel ◽  
Salman AlSabah ◽  
Eliana Al Haddad ◽  
Hutan Ashrafian
Keyword(s):  
Systematic Review ◽  
Critical Mass ◽  
Population Level ◽  
Ease Of Use ◽  
Contact Tracing ◽  
The Novel ◽  
Scientific Databases ◽  
Manual Methods ◽  
Novel Coronavirus ◽  
Transmission Of Disease

BACKGROUND The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. OBJECTIVE We aimed to investigate the effectiveness of contact tracing applications currently available in the context of the COVID-19 pandemic. METHODS We undertook a systematic review and narrative synthesis of all literature relating to contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. RESULTS Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of application adoption must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. CONCLUSIONS The COVID-19 pandemic has claimed more than 2 million lives globally, with over 100 million confirmed cases. Contact tracing can rapidly identify potentially infected individuals before the emergence of severe or critical symptoms, and it can also prevent the subsequent transmission of disease from secondary cases when implemented efficiently. Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labor intensive manual methods.

scholarly journals Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2

Science ◽  
2020 ◽  
pp. eabe2424 ◽  
Author(s):  
Kaiyuan Sun ◽  
Wei Wang ◽  
Lidong Gao ◽  
Yan Wang ◽  
Kaiwei Luo ◽  
...  
Keyword(s):  
Social Interactions ◽  
Population Level ◽  
Transmission Risk ◽  
Contact Tracing ◽  
Symptom Presentation ◽  
Secondary Infections ◽  
The Family ◽  
Infectious Disease Dynamics ◽  
Kinetics Of

A long-standing question in infectious disease dynamics concerns the role of transmission heterogeneities, driven by demography, behavior and interventions. Based on detailed patient and contact tracing data in Hunan, China we find 80% of secondary infections traced back to 15% of SARS-CoV-2 primary infections, indicating substantial transmission heterogeneities. Transmission risk scales positively with the duration of exposure and the closeness of social interactions and is modulated by demographic and clinical factors. The lockdown period increases transmission risk in the family and households, while isolation and quarantine reduce risks across all types of contacts. The reconstructed infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom presentation. Modeling indicates SARS-CoV-2 control requires the synergistic efforts of case isolation, contact quarantine, and population-level interventions, owing to the specific transmission kinetics of this virus.

scholarly journals Parameter-robustness analysis for a biochemical oscillator model describing the social-behaviour transition phase of myxobacteria

2018 ◽  
Vol 474 (2209) ◽  
pp. 20170499 ◽  
Author(s):  
Hadi Taghvafard ◽  
Hildeberto Jardón-Kojakhmetov ◽  
Ming Cao
Keyword(s):  
Social Behaviour ◽  
Robustness Analysis ◽  
Convergence Result ◽  
Transition Phase ◽  
Proposed Model ◽  
The Social ◽  
Small Change ◽  
Parameter Values ◽  
Biochemical Oscillator ◽  
Parameter Robustness

We develop a tool based on bifurcation analysis for parameter-robustness analysis for a class of oscillators and, in particular, examine a biochemical oscillator that describes the transition phase between social behaviours of myxobacteria. Myxobacteria are a particular group of soil bacteria that have two dogmatically different types of social behaviour: when food is abundant they live fairly isolated forming swarms, but when food is scarce, they aggregate into a multicellular organism. In the transition between the two types of behaviours, spatial wave patterns are produced, which is generally believed to be regulated by a certain biochemical clock that controls the direction of myxobacteria’s motion. We provide a detailed analysis of such a clock and show that, for the proposed model, there exists some interval in parameter space where the behaviour is robust, i.e. the system behaves similarly for all parameter values. In more mathematical terms, we show the existence and convergence of trajectories to a limit cycle, and provide estimates of the parameter under which such a behaviour occurs. In addition, we show that the reported convergence result is robust, in the sense that any small change in the parameters leads to the same qualitative behaviour of the solution.

scholarly journals Speech can produce jet-like transport relevant to asymptomatic spreading of virus

2020 ◽  
Vol 117 (41) ◽  
pp. 25237-25245 ◽  
Author(s):  
Manouk Abkarian ◽  
Simon Mendez ◽  
Nan Xue ◽  
Fan Yang ◽  
Howard A. Stone
Keyword(s):  
Social Interactions ◽  
Disease Transmission ◽  
Laboratory Experiments ◽  
Scaling Laws ◽  
Mitigation Strategies ◽  
Directed Transport ◽  
Transport Distance ◽  
Long Time ◽  
Phonetic Features

Many scientific reports document that asymptomatic and presymptomatic individuals contribute to the spread of COVID-19, probably during conversations in social interactions. Droplet emission occurs during speech, yet few studies document the flow to provide the transport mechanism. This lack of understanding prevents informed public health guidance for risk reduction and mitigation strategies, e.g., the “6-foot rule.” Here we analyze flows during breathing and speaking, including phonetic features, using orders-of-magnitude estimates, numerical simulations, and laboratory experiments. We document the spatiotemporal structure of the expelled airflow. Phonetic characteristics of plosive sounds like “P” lead to enhanced directed transport, including jet-like flows that entrain the surrounding air. We highlight three distinct temporal scaling laws for the transport distance of exhaled material including 1) transport over a short distance (<0.5 m) in a fraction of a second, with large angular variations due to the complexity of speech; 2) a longer distance, ∼1 m, where directed transport is driven by individual vortical puffs corresponding to plosive sounds; and 3) a distance out to about 2 m, or even farther, where sequential plosives in a sentence, corresponding effectively to a train of puffs, create conical, jet-like flows. The latter dictates the long-time transport in a conversation. We believe that this work will inform thinking about the role of ventilation, aerosol transport in disease transmission for humans and other animals, and yield a better understanding of linguistic aerodynamics, i.e., aerophonetics.

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