scholarly journals Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Matthew Abueg ◽  
Robert Hinch ◽  
Neo Wu ◽  
Luyang Liu ◽  
William Probert ◽  
...  
Keyword(s):  
Washington State ◽  
Disease Spread ◽  
Contact Tracing ◽  
Notification System ◽  
Health Authorities ◽  
Individual Based Models ◽  
Pharmaceutical Interventions

AbstractContact tracing is increasingly used to combat COVID-19, and digital implementations are now being deployed, many based on Apple and Google’s Exposure Notification System. These systems utilize non-traditional smartphone-based technology, presenting challenges in understanding possible outcomes. In this work, we create individual-based models of three Washington state counties to explore how digital exposure notifications combined with other non-pharmaceutical interventions influence COVID-19 disease spread under various adoption, compliance, and mobility scenarios. In a model with 15% participation, we found that exposure notification could reduce infections and deaths by approximately 8% and 6% and could effectively complement traditional contact tracing. We believe this can provide health authorities in Washington state and beyond with guidance on how exposure notification can complement traditional interventions to suppress the spread of COVID-19.

scholarly journals Modeling the combined effect of digital exposure notification and non-pharmaceutical interventions on the COVID-19 epidemic in Washington state

2020 ◽  
Author(s):  
Matthew Abueg ◽  
Robert Hinch ◽  
Neo Wu ◽  
Luyang Liu ◽  
William J M Probert ◽  
...  
Keyword(s):  
Computational Models ◽  
Washington State ◽  
Health Interventions ◽  
Disease Spread ◽  
Contact Tracing ◽  
Notification System ◽  
Health Authorities ◽  
Smartphone Technology ◽  
Representative Model ◽  
Pharmaceutical Interventions

Contact tracing is increasingly being used to combat COVID-19, and digital implementations are now being deployed, many of them based on Apple and Google's Exposure Notification System. These systems are new and are based on smartphone technology that has not traditionally been used for this purpose, presenting challenges in understanding possible outcomes. In this work, we use individual-based computational models to explore how digital exposure notifications can be used in conjunction with non-pharmaceutical interventions, such as traditional contact tracing and social distancing, to influence COVID-19 disease spread in a population. Specifically, we use a representative model of the household and occupational structure of three counties in the state of Washington together with a proposed digital exposure notifications deployment to quantify impacts under a range of scenarios of adoption, compliance, and mobility. In a model in which 15% of the population participated, we found that digital exposure notification systems could reduce infections and deaths by approximately 8% and 6%, effectively complementing traditional contact tracing. We believe this can serve as guidance to health authorities in Washington state and beyond on how exposure notification systems can complement traditional public health interventions to suppress the spread of COVID-19.

scholarly journals Investigation of the Efficiency of Mask Wearing, Contact Tracing, and Case Isolation during the COVID-19 Outbreak

2021 ◽  
Vol 10 (13) ◽  
pp. 2761
Author(s):  
Tatiana Filonets ◽  
Maxim Solovchuk ◽  
Wayne Gao ◽  
Tony Wen-Hann Sheu
Keyword(s):  
Mathematical Model ◽  
Reproduction Number ◽  
Control Measures ◽  
Disease Spread ◽  
Contact Tracing ◽  
Imported Cases ◽  
Quantitative Results ◽  
High Level ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

Case isolation and contact tracing are two essential parts of control measures to prevent the spread of COVID-19, however, additional interventions, such as mask wearing, are required. Taiwan successfully contained local COVID-19 transmission after the initial imported cases in the country in early 2020 after applying the above-mentioned interventions. In order to explain the containment of the disease spread in Taiwan and understand the efficiency of different non-pharmaceutical interventions, a mathematical model has been developed. A stochastic model was implemented in order to estimate the effectiveness of mask wearing together with case isolation and contact tracing. We investigated different approaches towards mask usage, estimated the effect of the interventions on the basic reproduction number (R0), and simulated the possibility of controlling the outbreak. With the assumption that non-medical and medical masks have 20% and 50% efficiency, respectively, case isolation works on 100%, 70% of all people wear medical masks, and R0 = 2.5, there is almost 80% probability of outbreak control with 60% contact tracing, whereas for non-medical masks the highest probability is only about 20%. With a large proportion of infectiousness before the onset of symptoms (40%) and the presence of asymptomatic cases, the investigated interventions (isolation of cases, contact tracing, and mask wearing by all people), implemented on a high level, can help to control the disease spread. Superspreading events have also been included in our model in order to estimate their impact on the outbreak and to understand how restrictions on gathering and social distancing can help to control the outbreak. The obtained quantitative results are in agreement with the empirical COVID-19 data in Taiwan.

scholarly journals Observations and conversations: how communities learn about infection risk can impact the success of non-pharmaceutical interventions against epidemics

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew J. Silk ◽  
Simon Carrignon ◽  
R. Alexander Bentley ◽  
Nina H. Fefferman
Keyword(s):  
Social Norms ◽  
Social Communication ◽  
Physical Contact ◽  
Disease Spread ◽  
Contact Tracing ◽  
Accurate Information ◽  
The Social ◽  
Communication Layer ◽  
Perceived Social Norms ◽  
Pharmaceutical Interventions

Abstract Background Individual behavioural decisions are responses to a person’s perceived social norms that could be shaped by both their physical and social environment. In the context of the COVID-19 pandemic, these environments correspond to epidemiological risk from contacts and the social construction of risk by communication within networks of friends. Understanding the circumstances under which the influence of these different social networks can promote the acceptance of non-pharmaceutical interventions and consequently the adoption of protective behaviours is critical for guiding useful, practical public health messaging. Methods We explore how information from both physical contact and social communication layers of a multiplex network can contribute to flattening the epidemic curve in a community. Connections in the physical contact layer represent opportunities for transmission, while connections in the communication layer represent social interactions through which individuals may gain information, e.g. messaging friends. Results We show that maintaining focus on awareness of risk among each individual’s physical contacts promotes the greatest reduction in disease spread, but only when an individual is aware of the symptoms of a non-trivial proportion of their physical contacts (~ ≥ 20%). Information from the social communication layer without was less useful when these connections matched less well with physical contacts and contributed little in combination with accurate information from physical contacts. Conclusions We conclude that maintaining social focus on local outbreak status will allow individuals to structure their perceived social norms appropriately and respond more rapidly when risk increases. Finding ways to relay accurate local information from trusted community leaders could improve mitigation even where more intrusive/costly strategies, such as contact-tracing, are not possible.

scholarly journals Fueling the Covid-19 pandemic: summer school holidays and incidence rates in German districts

2021 ◽  
Author(s):  
Thomas Plümper ◽  
Eric Neumayer
Keyword(s):  
Public Health ◽  
Fixed Effects ◽  
Summer School ◽  
Incidence Rates ◽  
Contact Tracing ◽  
Robert Koch Institute ◽  
Cross Sectional ◽  
Holiday Period ◽  
Health Authorities ◽  
Public Health Authorities

AbstractBackgroundThe Robert-Koch-Institute reports that during the summer holiday period a foreign country is stated as the most likely place of infection for an average of 27 and a maximum of 49% of new SARS-CoV-2 infections in Germany.MethodsCross-sectional study on observational data. In Germany, summer school holidays are coordinated between states and spread out over 13 weeks. Employing a dynamic model with district fixed effects, we analyze the association between these holidays and weekly incidence rates across 401 German districts.ResultsWe find effects of the holiday period of around 45% of the average district incidence rates in Germany during their respective final week of holidays and the 2 weeks after holidays end. Western states tend to experience stronger effects than Eastern states. We also find statistically significant interaction effects of school holidays with per capita taxable income and the share of foreign residents in a district’s population.ConclusionsOur results suggest that changed behavior during the holiday season accelerated the pandemic and made it considerably more difficult for public health authorities to contain the spread of the virus by means of contact tracing. Germany’s public health authorities did not prepare adequately for this acceleration.

scholarly journals How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Konstantin D. Pandl ◽  
Scott Thiebes ◽  
Manuel Schmidt-Kraepelin ◽  
Ali Sunyaev
Keyword(s):  
Disease Spread ◽  
Contact Tracing ◽  
Behavioral Characteristics ◽  
Policy Makers ◽  
Detection Range ◽  
Proximity Detection ◽  
Effective Technology ◽  
Different Types ◽  
Effectiveness And Efficiency ◽  
The Impact

AbstractTo combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing.

scholarly journals Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e047227
Author(s):  
Xiaoming Cui ◽  
Lin Zhao ◽  
Yuhao Zhou ◽  
Xin Lin ◽  
Runze Ye ◽  
...  
Keyword(s):  
Close Contact ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Population Mobility ◽  
Wholesale Market ◽  
The People ◽  
Spatiotemporal Analyses ◽  
Epidemiological Characteristics ◽  
Pharmaceutical Interventions ◽  
Modelling Study

ObjectiveTo evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.DesignDescriptive and modelling study based on surveillance data of COVID-19 in Beijing.SettingOutbreak in Beijing.ParticipantsThe database included 335 confirmed cases of COVID-19.MethodsTo conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.ResultsWe found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.ConclusionsThe non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.

scholarly journals Taiwan’s Successful COVID-19 Mitigation and Containment Strategy: Achieving Quasi Population Immunity

2020 ◽  
pp. 1-4 ◽  
Author(s):  
Li-Chien Chien ◽  
Christian K. Beÿ ◽  
Kristi L. Koenig
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Health Management ◽  
Mainland China ◽  
Emerging Infectious Diseases ◽  
Contact Tracing ◽  
Population Immunity ◽  
Containment Strategy ◽  
Local Transmission ◽  
Pharmaceutical Interventions

ABSTRACT The authors describe Taiwan’s successful strategy in achieving control of coronavirus disease (COVID-19) without economic shutdown, despite the prediction that millions of infections would be imported from travelers returning from Chinese New Year celebrations in Mainland China in early 2020. As of September 2, 2020, Taiwan reports 489 cases, 7 deaths, and no locally acquired COVID-19 cases for the last 135 days (greater than 4 months) in its population of over 23.8 million people. Taiwan created quasi population immunity through the application of established public health principles. These non-pharmaceutical interventions, including public masking and social distancing, coupled with early and aggressive identification, isolation, and contact tracing to inhibit local transmission, represent a model for optimal public health management of COVID-19 and future emerging infectious diseases.

scholarly journals A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic: The COVID-19 Application in Italy

2020 ◽  
Vol 8 (6) ◽  
pp. 911
Author(s):  
Lara Savini ◽  
Luca Candeloro ◽  
Paolo Calistri ◽  
Annamaria Conte
Keyword(s):  
Census Data ◽  
Human Mobility ◽  
Industrial Area ◽  
Disease Spread ◽  
Geographical Patterns ◽  
Italian Government ◽  
Health Authorities ◽  
Vulnerability Map ◽  
Different Levels ◽  
Emergency Measures

In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible–Infectious stochastic model and we estimated a municipality-specific infection contact rate (β) to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high β, due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different β values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.

scholarly journals Estimating the effectiveness of non-pharmaceutical interventions on COVID-19 control in South Korea

2020 ◽  
Author(s):  
Kyung-Duk Min ◽  
Heewon Kang ◽  
Ju-Yeun Lee ◽  
Seonghee Jeon ◽  
Sung-il Cho
Keyword(s):  
South Korea ◽  
Compartment Model ◽  
Contact Tracing ◽  
Contact Rate ◽  
Global Public Health ◽  
Spring Semester ◽  
Detection Rates ◽  
Social Distancing ◽  
Effective Contact ◽  
Pharmaceutical Interventions

Abstract Background: The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. South Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model.Methods: A compartment model with a susceptible-exposed-infectious-quarantined-hospitalized (SEIQH) structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs’ sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI.Results: Relaxed social distancing among adults would have increased the number of cases 27-fold until the end of March, and the epidemic curve would have been similar to other high burden countries. Spring semester non-postponement would have increased the effective contact rate 2·4-fold among individuals aged 0-19, while lower quarantine and detection rates would have increased the number of cases 1·4-fold. Conclusions: Among the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered for developing an exit strategy.

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