scholarly journals Contact tracing evaluation for COVID-19 transmission in the different movement levels of a rural college town in the USA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sifat A. Moon ◽  
Caterina M. Scoglio
Keyword(s):  
Basic Reproductive Number ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Contact Network ◽  
Model Parameters ◽  
Maximum Point ◽  
College Town ◽  
Interesting Phenomenon ◽  
The Usa ◽  
Rural College

AbstractContact tracing can play a key role in controlling human-to-human transmission of a highly contagious disease such as COVID-19. We investigate the benefits and costs of contact tracing in the COVID-19 transmission. We estimate two unknown epidemic model parameters (basic reproductive number $$R_0$$ R 0 and confirmed rate $$\delta _2$$ δ 2 ) by using confirmed case data. We model contact tracing in a two-layer network model. The two-layer network is composed by the contact network in the first layer and the tracing network in the second layer. In terms of benefits, simulation results show that increasing the fraction of traced contacts decreases the size of the epidemic. For example, tracing $$25\%$$ 25 % of the contacts is enough for any reopening scenario to reduce the number of confirmed cases by half. Considering the act of quarantining susceptible households as the contact tracing cost, we have observed an interesting phenomenon. The number of quarantined susceptible people increases with the increase of tracing because each individual confirmed case is mentioning more contacts. However, after reaching a maximum point, the number of quarantined susceptible people starts to decrease with the increase of tracing because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases. The goal of this research is to assess the effectiveness of contact tracing for the containment of COVID-19 spreading in the different movement levels of a rural college town in the USA. Our research model is designed to be flexible and therefore, can be used to other geographic locations.

scholarly journals Contact Tracing Evaluation for COVID-19 Transmission during the Reopening Phase in a Rural College Town

2020 ◽  
Author(s):  
Sifat Afroj Moon ◽  
Caterina Scoglio
Keyword(s):  
Epidemic Model ◽  
Infected Individual ◽  
Vital Role ◽  
Stochastic Simulations ◽  
Contact Tracing ◽  
Contact Network ◽  
Unknown Parameters ◽  
Interesting Phenomenon ◽  
Epidemic Size ◽  
The Usa

AbstractContact tracing can play a vital role in controlling human-to-human transmission of a highly contagious disease such as COVID-19. To investigate the benefits and costs of contact tracing, we develop an individual-based contact-network model and a susceptible-exposed-infected-confirmed (SEIC) epidemic model for the stochastic simulations of COVID-19 transmission. We estimate the unknown parameters (reproductive ratio R0 and confirmed rate δ2) by using observed confirmed case data. After a two month-lockdown, states in the USA have started the reopening process. We provide simulations for four different reopening situations: under “stay-at-home” order or no reopening, 25 % reopening, 50 % reopening, and 75 % reopening. We model contact tracing in a two-layer network by modifying the basic SEIC epidemic model. The two-layer network is composed by the contact network in the first layer and the tracing network in the second layer. Since the full contact list of an infected individual patient can be hard to obtain, then we consider different fractions of contacts from 60% to 5%. The goal of this paper is to assess the effectiveness of contact tracing to control the COVID-19 spreading in the reopening process. In terms of benefits, simulation results show that increasing the fraction of traced contacts decreases the size of the epidemic. For example, tracing 20% of the contacts is enough for all four reopening scenarios to reduce the epidemic size by half. Considering the act of quarantining susceptible households as the contact tracing cost, we have observed an interesting phenomenon. When we increase the fraction of traced contacts from 5% to 20%, the number of quarantined susceptible people increases because each individual confirmed case is mentioning more contacts. However, when we increase the fraction of traced contacts from 20% to 60%, the number of quarantined susceptible people decreases because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases. The main contribution of this research lies in the investigation of the effectiveness of contact tracing for the containment of COVID-19 spreading during the initial phase of the reopening process of the USA.

Transmission dynamics of primary pneumonic plague in the USA

2011 ◽  
Vol 140 (3) ◽  
pp. 554-560 ◽  
Author(s):  
A. F. HINCKLEY ◽  
B. J. BIGGERSTAFF ◽  
K. S. GRIFFITH ◽  
P. S. MEAD
Keyword(s):  
Severe Form ◽  
Antimicrobial Treatment ◽  
Transmission Dynamics ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Published Data ◽  
Pneumonic Plague ◽  
Transmission Potential ◽  
The Usa ◽  
Using Data

SUMMARYPlague is thought to have killed millions during three catastrophic pandemics. Primary pneumonic plague, the most severe form of the disease, is transmissible from person-to-person and has the potential for propagating epidemics. Efforts to quantify its transmission potential have relied on published data from large outbreaks, an approach that artificially inflates the basic reproductive number (R0) and skews the distribution of individual infectiousness. Using data for all primary pneumonic plague cases reported in the USA from 1900 to 2009, we determined that the majority of cases will fail to transmit, even in the absence of antimicrobial treatment or prophylaxis. Nevertheless, potential for sustained outbreaks still exists due to superspreading events. These findings challenge current concepts regarding primary pneumonic plague transmission.

scholarly journals A stochastic epidemiological model to estimate the size of an outbreak at the first case identification

2020 ◽  
Author(s):  
Peter Czuppon ◽  
François Blanquart ◽  
Florence Débarre
Keyword(s):  
Branching Processes ◽  
Single Point ◽  
Basic Reproductive Number ◽  
Contact Tracing ◽  
Upper And Lower Bounds ◽  
Reproductive Number ◽  
Related Case ◽  
Epidemic Size ◽  
First Case ◽  
Over Time

AbstractThe identification of a first case (e.g. by a disease-related death or hospitalization event) raises the question of the actual size of a local outbreak. Quick estimates of the outbreak size are required to assess the necessary testing, contact tracing and potential containment effort. Using general branching processes and assuming that epidemic parameters (including the basic reproductive number) are constant over time, we characterize the distribution of the first hospitalization time and of the epidemic size at this random time. We find that previous estimates either overestimate or largely underestimate the actual epidemic size. In addition, we provide upper and lower bounds for the number of infectious individuals of the local outbreak over time. The upper bound is the cumulative epidemic size, and the lower bound is a constant fraction of it. Lastly, we compute the number of detectable cases if one were to test the whole local outbreak at a single point in time. In a growing epidemic, most individuals have been infected recently, which can strongly limit the detection of infected individuals when there is a delay between an infection and its potential detection. Overall, our analysis provides new analytical estimates about the epidemic size at identification of a first disease-related case. This piece of information is important to inform policy makers during the early stages of an epidemic outbreak.

scholarly journals A Mathematical Analysis of an In-vivo Ebola Virus Transmission Dynamics Model

2021 ◽  
Vol 47 (4) ◽  
pp. 1464-1477
Author(s):  
Seleman Ismail ◽  
Adeline Peter Mtunya
Keyword(s):  
Mathematical Model ◽  
Infection Rate ◽  
Ebola Virus ◽  
Virus Transmission ◽  
Transmission Dynamics ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Model Parameters ◽  
Sensitivity Index

Ebola virus (EBOV) infection is a hemorrhagic and hazardous disease, which is among the most shocking threats to human health causing a large number of deaths. Currently, there are no approved curative therapies for the disease. In this study, a mathematical model for in-vivo Ebola virus transmission dynamics was analyzed. The analysis of the model mainly focused on the sensitivity of basic reproductive number,  pertaining to the model parameters. Particularly, the sensitivity indices of all parameters of  were computed by using the forward normalized sensitivity index method. The results showed that a slight change in the infection rate immensely influences  while the same change in the production rate of the virus has the least impact on . Thus, , being a determining factor  of the disease progression, deliberate control measures targeting the infection rate, the most positively sensitive parameter, are required. This implies that reducing infection rate will redirect the disease to extinction. Keywords: Ebola virus infection, immune response, sensitivity index, mathematical model.

scholarly journals The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated

2020 ◽  
Author(s):  
Steven Sanche ◽  
Yen Ting Lin ◽  
Chonggang Xu ◽  
Ethan Romero-Severson ◽  
Nick Hengartner ◽  
...  
Keyword(s):  
Case Reports ◽  
Individual Case ◽  
Control Measures ◽  
Basic Reproductive Number ◽  
Contact Tracing ◽  
Reproductive Number ◽  
The Novel ◽  
Transmission Potential ◽  
Novel Coronavirus ◽  
Strong Control

AbstractThe novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.One-sentence summaryBy collecting and analyzing spatiotemporal data, we estimated the transmission potential for 2019-nCoV.

scholarly journals Transmission dynamics and control strategies of COVID-19: a modelling study

2021 ◽  
Vol 102 (2) ◽  
pp. 92-105
Author(s):  
U.T. Mustapha ◽  
◽  
E. Hincal ◽  
A. Yusuf ◽  
S. Qureshi ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Recovery Rate ◽  
Transmission Rate ◽  
Face Mask ◽  
Basic Reproductive Number ◽  
Effective Control ◽  
Reproductive Number ◽  
Model Parameters ◽  
Susceptible Population ◽  
Social Distancing

In this paper a mathematical model is proposed, which incorporates quarantine and hospitalization to assess the community impact of social distancing and face mask among the susceptible population. The model parameters are estimated and fitted to the model with the use of laboratory confirmed COVID-19 cases in Turkey from March 11 to October 10, 2020. The partial rank correlation coefficient is employed to perform sensitivity analysis of the model, with basic reproduction number and infection attack rate as response functions. Results from the sensitivity analysis reveal that the most essential parameters for effective control of COVID-19 infection are recovery rate from quarantine individuals (δ1), recovery rate from hospitalized individuals (δ4), and transmission rate (β). Some simulation results are obtained with the aid of mesh plots with respect to the basic reproductive number as a function of two different biological parameters randomly chosen from the model. Finally, numerical simulations on the dynamics of the model highlighted that infections from the compartments of each state variables decreases with time which causes an increase in susceptible individuals. This implies that avoiding contact with infected individuals by means of adequate awareness of social distancing and wearing face mask are vital to prevent or reduce the spread of COVID-19 infection.

scholarly journals A model of the innate immune response to SARS-CoV-2 in the alveolar epithelium

2021 ◽  
Vol 8 (8) ◽  
pp. 210090
Author(s):  
R. N. Leander ◽  
Y. Wu ◽  
W. Ding ◽  
D. E. Nelson ◽  
Z. Sinkala
Keyword(s):  
Immune Response ◽  
Innate Immune Response ◽  
Interferon Therapy ◽  
Alveolar Epithelium ◽  
Innate Immune ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Infection Model ◽  
Model Parameters ◽  
Type I

We present a differential equation model of the innate immune response to SARS-CoV-2 within the alveolar epithelium. Critical determinants of the viral dynamics and host response, including type I and type II alveolar epithelial cells, interferons, chemokines, toxins and innate immune cells, are included. We estimate model parameters, compute the within-host basic reproductive number, and study the impacts of therapies, prophylactics, and host/pathogen variability on the course of the infection. Model simulations indicate that the innate immune response suppresses the infection and enables the alveolar epithelium to partially recover. While very robust antiviral therapy controls the infection and enables the epithelium to heal, moderate therapy is of limited benefit. Meanwhile interferon therapy is predicted to reduce viral load but exacerbate tissue damage. The deleterious effects of interferon therapy are especially apparent late in the infection. Individual variation in ACE2 expression, epithelial cell interferon production, and SARS-CoV-2 spike protein binding affinity are predicted to significantly impact prognosis.

scholarly journals Evaluating the burden of COVID-19 on hospital resources in Bahia, Brazil: A modelling-based analysis of 14.8 million individuals

2020 ◽  
Author(s):  
Juliane Fonseca Oliveira ◽  
Daniel C. P. Jorge ◽  
Rafael V. Veiga ◽  
Moreno S. Rodrigues ◽  
Matheus F. Torquato ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Health Resources ◽  
Compartment Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Model Parameters ◽  
Resource Setting ◽  
Asymptomatic Individuals ◽  
The One ◽  
The Impact

Here we present a general compartment model with a time-varying transmission rate to describe the dynamics of the COVID-19 epidemic, parameterized with the demographics of Bahia, a state in northeast Brazil. The dynamics of the model are influenced by the number of asymptomatic cases, hospitalization requirements and mortality due to the disease. A locally-informed model was determined using actual hospitalization records. Together with cases and casualty data, optimized estimates for model parameters were obtained within a metaheuristic framework based on Particle Swarm Optimization. Our strategy is supported by a statistical sensitivity analysis on the model parameters, adequate to properly account for the simulated scenarios. First, we evaluated the effect of previously enforced interventions on the transmission rate. Then, we studied its effects on the number of deaths as well as hospitalization requirements, considering the state as a whole. Special attention is given to the impact of asymptomatic individuals on the dynamic of COVID-19 transmission, as these were estimated to contribute to a 68% increase in the basic reproductive number. Finally, we delineated scenarios that can set guides to protect the health care system, particularly by keeping demand below total bed occupancy. Our results underscore the challenges related to maintaining a fully capable health infrastructure during the ongoing COVID-19 pandemic, specially in a low-resource setting such as the one focused in this work. The evidences produced by our modelling-based analysis show that decreasing the transmission rate is paramount to success in maintaining health resources availability, but that current local efforts, leading to a 38% decrease in the transmission rate, are still insufficient to prevent its collapse at peak demand. Carefully planned and timely applied interventions, that result in stark decreases in transmission rate, were found to be the most effective in preventing hospital bed shortages for the longest periods.

scholarly journals Modeling the health impact of water and sanitation service deficits on waterborne disease transmission

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rujira Chaysiri ◽  
Garrick E. Louis ◽  
Wirawan Chinviriyasit
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Health Impact ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Model Parameters ◽  
Asymptotically Stable ◽  
Waterborne Disease ◽  
Water And Sanitation ◽  
Globally Asymptotically Stable

AbstractCholera is a waterborne disease that continues to pose serious public health problems in many developing countries. Increasing water and sanitation coverage is a goal for local authorities in these countries, as it can eliminate one of the root causes of cholera transmission. The SIWDR (susceptible–infected–water–dumpsite–recovered) model is proposed here to evaluate the effects of the improved coverage of water and sanitation services in a community at risk of a cholera outbreak. This paper provides a mathematical study of the dynamics of the water and sanitation (WatSan) deficits and their public health impact in a community. The theoretical analysis of the SIWDR model gave a certain threshold value (known as the basic reproductive number and denoted $\mathcal{R}_{0}$ R 0 ) to stop the transmission of cholera. It was found that the disease-free equilibrium was globally asymptotically stable whenever $\mathcal{R}_{0} \leq 1$ R 0 ≤ 1 . The unique endemic equilibrium was globally asymptotically stable whenever $\mathcal{R}_{0} >1$ R 0 > 1 . Sensitivity analysis was performed to determine the relative importance of model parameters to disease transmission and prevention. The numerical simulation results, using realistic parameter values in describing cholera transmission in Haiti, showed that improving the drinking water supply, wastewater and sewage treatment, and solid waste disposal services would be effective strategies for controlling the transmission pathways of this waterborne disease.

scholarly journals Inferring epidemic containment probability from non-pharmaceutical interventions using a Gillespie-based epidemic model

2021 ◽  
Author(s):  
Yasuhiko Kawato ◽  
Masatoshi Yamasaki ◽  
Tomomasa Matsuyama ◽  
Tohru Mekata ◽  
Takafumi Ito ◽  
...  
Keyword(s):  
Stochastic Simulation ◽  
Epidemic Model ◽  
Deterministic Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Model Parameters ◽  
Gillespie Algorithm ◽  
Susceptible Population ◽  
Markovian Processes ◽  
Pharmaceutical Interventions

The Gillespie algorithm, which is a stochastic numerical simulation of continuous-time Markovian processes, has been proposed for simulating epidemic dynamics. In the present study, using the Gillespie-based epidemic model, we focused on each single trajectory by the stochastic simulation to infer the probability of controlling an epidemic by non-pharmaceutical interventions (NPIs). The single trajectory analysis by the stochastic simulation suggested that a few infected people sometimes dissipated spontaneously without spreading of infection. The outbreak probability was affected by basic reproductive number but not by infectious duration and susceptible population size.　A comparative analysis suggested that the mean trajectory by the stochastic simulation has equivalent dynamics to a conventional deterministic model in terms of epidemic forecasting. The probability of outbreak containment by NPIs was inferred by trajectories derived from 1000 Monte Carlo simulation trials using model parameters assuming COVID-19 epidemic. The model-based analysis indicated that complete containment of the disease could be achieved by short-duration NPIs if performed early after the import of infected individuals. Under the correctness of the model assumptions, analysis of each trajectory by Gillespie-based stochastic model would provide a unique and valuable output such as the probabilities of outbreak containment by NPIs.

Sign in / Sign up

Export Citation Format

Share Document