scholarly journals Factors influencing SARS-CoV-2 transmission and outbreak control measures in densely populated settings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rachael Pung ◽  
Bernard Lin ◽  
Sebastian Maurer-Stroh ◽  
Fernanda L. Sirota ◽  
Tze Minn Mak ◽  
...  
Keyword(s):  
Simulation Models ◽  
Control Measures ◽  
Disease Spread ◽  
Medical Attention ◽  
Outbreak Control ◽  
Acute Infections ◽  
Rapid Transmission ◽  
Current Outbreak ◽  
Living Environments ◽  
The Impact

AbstractStarting with a handful of SARS-CoV-2 infections in dormitory residents in late March 2020, rapid transmission in their dense living environments ensued and by October 2020, more than 50,000 acute infections were identified across various dormitories in Singapore. The aim of the study is to identify combination of factors facilitating SARS-CoV-2 transmission and the impact of control measures in a dormitory through extensive epidemiological, serological and phylogenetic investigations, supported by simulation models. Our findings showed that asymptomatic cases and symptomatic cases who did not seek medical attention were major drivers of the outbreak. Furthermore, each resident had about 30 close contacts and each infected resident spread to 4.4 (IQR 3.5–5.3) others at the start of the outbreak. The final attack rate of the current outbreak was 76.2% (IQR 70.6–98.0%) and could be reduced by further 10% under a modified dormitory housing condition. These findings are important when designing living environments in a post COVID-19 future to reduce disease spread and facilitate rapid implementation of outbreak control measures.

scholarly journals Reducing spread of COVID-19 in closed environments: an outbreak investigation and modelling study in dormitory settings

2020 ◽  
Author(s):  
Rachael Pung ◽  
Bernard Lin ◽  
Sebastian Maurer-Stroh ◽  
Fernanda L Sirota ◽  
Tze Minn Mak ◽  
...  
Keyword(s):  
Attack Rate ◽  
Simulation Models ◽  
Housing Condition ◽  
Control Measures ◽  
Disease Spread ◽  
Medical Attention ◽  
Acute Infections ◽  
Current Outbreak ◽  
Living Environments ◽  
Close Contacts

Abstract Starting with a handful of SARS-CoV-2 infections in dormitory residents in late March 2020, rapid tranmission in their dense living environments ensued and by October 2020, more than 50,000 acute infections were identified across various dormitories. Extensive epidemiological, serological and phylogentic investigations, supported by simulation models, helped to reveal the factors of transmission and impact of control measures in a dormitory. We find that asymptomatic cases and symptomatic cases who did not seek medical attention were major drivers of the outbreak. Furthermore, each resident has about 30 close contacts and each infected resident spread to 4.4 (IQR 3.5–5.3) others at the start of the outbreak. The final attack rate of the current outbreak was 76.2% (IQR 70.6%–98.0%) and could be reduced by further 10% under a modified dormitory housing condition. These findings are important when designing living environments in a post COVID-19 future to reduce disease spread and facilitate rapid implementation of outbreak control measures.

scholarly journals Individually Optimal Choices can be Collectively Disastrous in COVID-19 Disease Control

2021 ◽  
Author(s):  
Madison Stoddard ◽  
Debra Van Egeren ◽  
Kaitlyn Johnson ◽  
Smriti Rao ◽  
Josh Furgeson ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Control ◽  
Control Measures ◽  
Disease Spread ◽  
Complete Suppression ◽  
Natural Immunity ◽  
Endemic Disease ◽  
Health Measures ◽  
The Impact

Abstract Background: The word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high basic reproduction number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with interventions (such as vaccines and masks) to limit disease transmission. Our work explores the rationality and impact of noncompliance with COVID-19 disease control measures. Methods: In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals. We then used epidemiological modeling to predict the impact of noncompliance on control of COVID-19, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Results: Our modeling demonstrating that noncompliance is a Nash equilibrium under a broad set of conditions, and that the existence of a noncompliant population can result in extensive endemic disease in the long-term after a return to pre-pandemic social and economic activity. Endemic disease poses a threat for both compliant and noncompliant individuals; all community members are protected if complete suppression is achieved, which is only possible with a high degree of compliance. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. Conclusions: In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering COVID-19 disease control ineffective in the short term and making complete suppression impossible in the long term. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods: We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals On the fallibility of simulation models in informing pandemic responses

2020 ◽  
Author(s):  
Deepti Gurdasani ◽  
Hisham Ziauddeen
Keyword(s):  
Simulation Models ◽  
Control Measures ◽  
Disease Spread ◽  
Contact Tracing ◽  
Parameter Estimates ◽  
Case Detection ◽  
Rapid Testing ◽  
Real World Data ◽  
Effective Strategies ◽  
Reliable Parameter

In the early stages of pandemics, mathematical models can provide invaluable insights into transmission dynamics, help predict disease spread, and evaluate control measures. However models are only valid within the limits of the parameters examined. As reliable parameter estimates are rarely available early in a new pandemic, best-guess estimates are used, which need to be constantly reviewed as new real-world data emerge. Estimating how sensitive the model is to changes in its parameters can provide useful information about validity when parameters are uncertain. Interpreting models without considering these factors can lead to flawed inferences, which can have far reaching effects when they inform public health policy. We illustrate this, here, using an example from the Hellewell et al. model published in Lancet Global Health, 2020. This model suggested that case detection and contact tracing was unlikely to be an effective strategy for pandemic control, and is likely to have informed UK government strategy to cease testing and contact tracing on the 12th March 2020. We show that this model is very sensitive to the parameter of delay between case detection and isolation. We demonstrate that when the delay scenario parameter is changed to a median of 1 day, which is very plausible in the context of current rapid testing, this model predicts a >80% probability of controlling the epidemic within 12 weeks, with relatively modest contact tracing. These results suggest that rapid testing, contact tracing and isolation could be effective strategies to control transmission.

STRUCTURED INFLUENZA MODEL FOR META-POPULATION

2009 ◽  
Vol 02 (04) ◽  
pp. 525-541 ◽  
Author(s):  
MARIJA ŽIVKOVIĆ GOJOVIĆ ◽  
DONG LIANG ◽  
JIANHONG WU
Keyword(s):  
Control Strategies ◽  
Influenza Pandemic ◽  
Influenza Infection ◽  
Control Measures ◽  
Disease Spread ◽  
Behavior Changes ◽  
Spatial Spread ◽  
Structured Population ◽  
Age Structured ◽  
The Impact

We present a mathematical model parameterized to simulate the 1918 pandemic and modified to account for today's achievements in medical care and technology. Our goal is to use the model with carefully selected parameters to analyze and simulate different scenarios in a changing environment including behavior changes and reduction of mobility as the disease progresses. The model is structured by the disease age, representing the time elapsed since the exposure to influenza infection, and most of the parameters used in this study are thus disease-age dependent. We also consider the case where an influenza pandemic affects two distinct regions, connected only through controlled mobility. We evaluate the influence of different control measures on temporal patterns of disease dynamics and consider the impact of the movement of disease age structured population on spatial spread. A special example is examined that considers different scenarios of disease spread between Canada and USA when different border control strategies are implemented.

scholarly journals A multi-scale model quantifies the impact of limited movement of the population and mandatory wearing of face masks in containing the COVID-19 epidemic in Morocco

2020 ◽  
Vol 15 ◽  
pp. 31 ◽  
Author(s):  
Anass Bouchnita ◽  
Aissam Jebrane
Keyword(s):  
Control Measures ◽  
Disease Spread ◽  
Scale Model ◽  
Population Movement ◽  
Force Model ◽  
Global Public Health ◽  
Social Force ◽  
Indirect Transmission ◽  
Multi Scale ◽  
The Impact

The coronavirus disease (COVID-19) pandemic emerged in Wuhan, China, in December 2019 and caused a serious threat to global public health. In Morocco, the first confirmed COVID-19 case was reported on March 2, 2020. Since then, several non-pharmaceutical interventions were used to slow down the spread of the disease. In this work, we use a previously developed multi-scale model of COVID-19 transmission dynamics to quantify the effects of restricting population movement and wearing face masks on disease spread in Morocco. In this model, individuals are represented as agents that move, become infected, transmit the disease, develop symptoms, go into quarantine, die by the disease, or become immunized. We describe the movement of agents using a social force model and we consider both modes of direct and indirect transmission. We use the model to simulate the impact of restricting the movement of the population movement and mandating the wearing of masks on the spread of COVID-19. The model predicts that adopting these two measures would reduce the total number of cases by 64%. Furthermore, the relative incidence of indirect transmission increases when control measures are adopted.

scholarly journals The impact of current and future control measures on the spread of COVID-19 in Germany

2020 ◽  
Author(s):  
Maria Vittoria Barbarossa ◽  
Jan Fuhrmann ◽  
Jan H. Meinke ◽  
Stefan Krieg ◽  
Hridya Vinod Varma ◽  
...  
Keyword(s):  
Age Groups ◽  
Risk Groups ◽  
Control Measures ◽  
The Novel ◽  
Slowing Down ◽  
Initial Work ◽  
Current Outbreak ◽  
Novel Coronavirus ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractThe novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020 [37]. In view of most recent information on testing activity [32], we present here an update of our initial work [4]. In this work, mathematical models have been developed to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended here to account for undetected infections, as well as for stages of infections and age groups. The models are calibrated on data until April 5, data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases and reduced contact to risk groups.

scholarly journals Implementation of novel and conventional outbreak control measures in managing a COVID-19 outbreak in a large UK prison

2020 ◽  
Author(s):  
Paul Coleman ◽  
Roger Gajraj ◽  
Joht Singh Chandan ◽  
Anjana Roy ◽  
Victoria Lumby ◽  
...  
Keyword(s):  
Public Health ◽  
Cost Effective ◽  
Control Measures ◽  
Correctional Facilities ◽  
Outbreak Control ◽  
Wide Range ◽  
Rapid Transmission ◽  
Uk National Health Service ◽  
The Uk ◽  
Health Experts

Background: SARS-CoV-2 can spread rapidly within correctional facilities. On 22nd March 2020, following identification of a confirmed COVID-19 case in a prisoner in Prison A (UK), an Outbreak Control Team was convened consisting of prison staff and public health experts from Public Health England and the UK National Health Service. Methods: At the start of the outbreak, four prisoners and 40 staff were isolating with COVID-19 symptoms. An outbreak was declared and full prison lockdown implemented. Prompt implementation of novel outbreak control measures prevented an explosive prison outbreak, specifically establishment of dedicated isolation and cohorting units, including (i) Reverse Cohorting Units (RCUs) for accommodating new detainees; (ii) Protective Isolation Units (PIUs) for isolating symptomatic prisoners (new detainees and existing residents), and (iii) Shielding Units (SUs) to protect medically vulnerable prisoners. Findings: In total, 120 probable and 25 confirmed cases among prisoners and staff were recorded between March and June 2020. Among prisoners, there were six possible, 79 probable, and three confirmed cases. Among staff, there were 83 possible, 79 probable, and 22 confirmed cases. Testing of symptomatic prisoners was limited for most of the outbreak, with only 33% of probable cases tested. This explains the low number of confirmed cases (three) among prisoners despite the large number of probable cases (n=81; 92%). Over 50% of the initial cases among prisoners were on the two wings associated with the index case. Interpretation: Rapid transmission of SARS-COV-2 was prevented through proactive steps in identifying and isolating infected prisoners (and staff), cohorting new admissions and shielding vulnerable individuals. These novel and cost-effective approaches can be implemented in a wide range of correctional facilities globally and proved effective even in the absence of mass testing.

scholarly journals Ohio Response to COVID-19 and Its Impact on Interventional Pain Management Practices

2020 ◽  
Vol 4S;23 (8;4S) ◽  
pp. S439-S447
Author(s):  
Amol Soin
Keyword(s):  
Pain Management ◽  
Infection Control ◽  
Management Practices ◽  
Substantial Reduction ◽  
Control Measures ◽  
Disease Spread ◽  
Social Distancing ◽  
Infection Control Measures ◽  
Interventional Pain Management ◽  
The Impact

Background: The coronavirus disease 2019 (COVID-19) pandemic has drastically altered daily living and medical care for Ohio residents and the practice of medicine for the interventional pain management physician. As a state, Ohio tends to be demographically representative of the broader US population. Objective: Reviewing the efforts deployed by Ohio to flatten the COVID-19 infection curve and reduce the spread of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an important component of determining optimal procedures for mitigating the effects of the COVID-19 pandemic. Methods: Over the course of several announcements and orders during the months of March and April, new policies were put into place to prevent COVID-19 transmission, which included efforts to facilitate social distancing and ensure the health care system could manage the number of COVID-19 cases at peak infection rate. Efforts directed toward medical providers included delay of elective procedures, expansion of telehealth options, and new temporary guidance for prescribing controlled substances. Results: The Ohio COVID-19 containment approach resulted in a substantial reduction in COVID-19 cases compared with early models of disease spread, and the state has begun a phased reopening. Continued vigilance in applying social distancing and infection control measures will be a critical component of preventing or reducing the impact of a second wave of COVID-19 in Ohio. Limitations: A narrative review with paucity of literature. Key words: COVID-19, infection rates, mitigating effects, pandemic, infection control

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