SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study

Background: Development of strategies for mitigating the severity of COVID-19 is now a top global public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions such as social distancing, self-isolation, tracing and quarantine, wearing facial masks/ personal protective equipment. Methods: We developed an individual-based model for COVID-19 transmission among healthcare workers in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan in a Bayesian framework. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. Results: We estimated that work-related stress increases susceptibility to COVID-19 infection among healthcare workers by 52% (90% Credible Interval (CrI): 16.4% - 93.0%). The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. A strict quarantine policy with the isolation of symptomatic cases and a high fraction of pre-symptomatic/ asymptomatic cases (via contact tracing or high test rate), could only prolong outbreak duration with minimal impact on the outbreak size. Our results indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. Conclusions: Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

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SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study

Royal Society Open Science ◽

10.1098/rsos.201895 ◽

2021 ◽

Vol 8 (3) ◽

Author(s):

Qimin Huang ◽

Anirban Mondal ◽

Xiaobing Jiang ◽

Mary Ann Horn ◽

Fei Fan ◽

...

Keyword(s):

Healthcare Workers ◽

Hospital Setting ◽

Credible Interval ◽

Hospital Unit ◽

Early Implementation ◽

Using Data ◽

And Control ◽

The Impact ◽

Pharmaceutical Interventions ◽

Outbreak Size

Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions. We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. The use of high-efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% credible interval (CrI): 73.1–85.7%) and 87% (CrI: 80.0–92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

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Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China

Science ◽

10.1126/science.abb8001 ◽

2020 ◽

Vol 368 (6498) ◽

pp. 1481-1486 ◽

Cited By ~ 202

Author(s):

Juanjuan Zhang ◽

Maria Litvinova ◽

Yuxia Liang ◽

Yan Wang ◽

Wei Wang ◽

...

Keyword(s):

Confidence Interval ◽

Odds Ratio ◽

School Closure ◽

Hunan Province ◽

Contact Tracing ◽

Transmission Model ◽

Social Distancing ◽

Susceptibility To Infection ◽

Contact Patterns ◽

The Impact

Intense nonpharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease 2019 (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact survey data for Wuhan and Shanghai before and during the outbreak and contact-tracing information from Hunan province. Daily contacts were reduced seven- to eightfold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0 to 14 years of age are less susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than adults 15 to 64 years of age (odds ratio 0.34, 95% confidence interval 0.24 to 0.49), whereas individuals more than 65 years of age are more susceptible to infection (odds ratio 1.47, 95% confidence interval 1.12 to 1.92). Based on these data, we built a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Although proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40 to 60% and delay the epidemic.

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Epidemiological trend of COVID-19 in Nepal and the importance of social distancing to contain the virus

Applied Science and Technology Annals ◽

10.3126/asta.v1i1.30268 ◽

2020 ◽

Vol 1 (1) ◽

pp. 15-25

Author(s):

Amod K. Pokhrel ◽

Yadav P. Joshi ◽

Sopnil Bhattarai

Keyword(s):

Mitigation Measures ◽

Contact Tracing ◽

Limited Information ◽

Social Distancing ◽

Mobility Data ◽

Epidemiological Trend ◽

Reproduction Numbers ◽

The Government ◽

Testing Case ◽

The Impact

There is limited information on the epidemiology and the effects of mitigation measures on the spread of COVID-19 in Nepal. Using publicly available databases, we analyzed the epidemiological trend, the people's movement trends at different intervals across different categories of places and evaluated implications of social mobility on COVID-19. We also estimated the epidemic peak. As of June 9, 2020, Provinces 2 and 5 have most of the cases. People between 15 and 54 years are vulnerable to becoming infected, and more males than females are affected. The cases are growing exponentially. The growth rate of 0.13 and >1 reproduction numbers (R0) over time (median: 1.48; minimum: 0.58, and maximum: 3.71) confirms this trend. The case doubling time is five days. Google's community mobility data suggest that people strictly followed social distancing measures for one month after the lockdown. By around the 4th week of April, the individual's movement started rising, and social contacts increased. The number of cases peaked on May 12, with 83 confirmed cases in one day. The Susceptible-Exposed-Infectious-Removed (SEIR) model suggests that the epidemic will peak approximately on day 41 (July 21, 2020), and start to plateau after day 80. To contain the spread of the virus, people should maintain social distancing. The Government needs to continue active surveillance, more PCR-based testing, case detection, contact tracing, isolation, and quarantine. The Government should also provide financial support and safety-nets to the citizen to limit the impact of COVID-19.

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The impact of SARS‐CoV‐2 on the mental health of healthcare workers in a hospital setting—A Systematic Review

Journal of Occupational Health ◽

10.1002/1348-9585.12175 ◽

2020 ◽

Vol 62 (1) ◽

Cited By ~ 1

Author(s):

Jaspinder Sanghera ◽

Nikhil Pattani ◽

Yousuf Hashmi ◽

Kate F. Varley ◽

Manikandar Srinivas Cheruvu ◽

...

Keyword(s):

Mental Health ◽

Systematic Review ◽

Healthcare Workers ◽

Hospital Setting ◽

The Impact

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Early estimates of COVID-19 infections in small, medium and large population clusters

BMJ Global Health ◽

10.1136/bmjgh-2020-003055 ◽

2020 ◽

Vol 5 (9) ◽

pp. e003055

Author(s):

Amir Siraj ◽

Alemayehu Worku ◽

Kiros Berhane ◽

Maru Aregawi ◽

Munir Eshetu ◽

...

Keyword(s):

Large Population ◽

Face Mask ◽

Sub Saharan Africa ◽

Contact Tracing ◽

Local Context ◽

African Region ◽

Social Distancing ◽

Population Sizes ◽

Sub Saharan ◽

The Impact

IntroductionSince its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres.MethodsTo address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask.ResultsWe showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%.ConclusionsIn SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent.

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Situating ‘careful surveillance’

International Journal of Cultural Studies ◽

10.1177/1367877921997450 ◽

2021 ◽

pp. 136787792199745

Author(s):

Mark Andrejevic ◽

Hugh Davies ◽

Ruth DeSouza ◽

Larissa Hjorth ◽

Ingrid Richardson

Keyword(s):

Public Health ◽

Public Space ◽

Social Care ◽

Cultural Practices ◽

Contact Tracing ◽

Social Distancing ◽

Health Measures ◽

Relationship Of ◽

The Impact ◽

The Relationship

In this article we explore preliminary findings from the study COVIDSafe and Beyond: Perceptions and Practices conducted in Australia in 2020. The study involved a survey followed by interviews, and aimed to capture the dynamic ways in which members of the Australian public perceive the impact of Covid practices – especially public health measures like the introduction of physical and social distancing, compulsory mask wearing, and contact tracing. In the rescripting of public space, different notions of formal and informal surveillance, along with different textures of mediated and social care, appeared. In this article, we explore perceptions around divergent forms of surveillance across social, technological, governmental modes, and the relationship of surveillance to care in our media and cultural practices. What does it mean to care for self and others during a pandemic? How does care get enacted in, and through, media interfaces and public interaction?

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

10.21203/rs.3.rs-30131/v1 ◽

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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Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China

10.1101/2020.03.03.20030593 ◽

2020 ◽

Cited By ~ 68

Author(s):

Chaolong Wang ◽

Li Liu ◽

Xingjie Hao ◽

Huan Guo ◽

Qi Wang ◽

...

Keyword(s):

Attack Rate ◽

Healthcare Workers ◽

Age Groups ◽

Credible Interval ◽

Reproductive Number ◽

Demographic Groups ◽

Individual Level ◽

Epidemiological Characteristics ◽

The Impact ◽

Pharmaceutical Interventions

ABSTRACTBACKGROUNDWe described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China.METHODSIndividual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions.RESULTSThe median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age <20) whose attack rate continued to increase. Healthcare workers and elderly people had higher attack rates and severity risk increased with age. The effective reproductive number dropped from 3.86 (95% credible interval 3.74 to 3.97) before interventions to 0.32 (0.28 to 0.37) post interventions. The interventions were estimated to prevent 94.5% (93.7 to 95.2%) infections till February 18. We found that at least 59% of infected cases were unascertained in Wuhan, potentially including asymptomatic and mild-symptomatic cases.CONCLUSIONSConsiderable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.

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Downsizing of contact tracing during COVID-19 vaccine roll-out

10.1101/2021.11.03.21265863 ◽

2021 ◽

Author(s):

Maria M Martignoni ◽

Joshua Renault ◽

Joseph Baafi ◽

Amy Hurford

Keyword(s):

Exponential Growth ◽

Cost Effective ◽

Quantitative Information ◽

Vaccination Status ◽

Outbreak Detection ◽

Contact Tracing ◽

Epidemic Spread ◽

Social Distancing ◽

The Impact ◽

Roll Out

Contact tracing is a key component of successful management of COVID-19. Contacts of infected individuals are asked to quarantine, which can significantly slow down (or prevent) community spread. Contact tracing is particularly effective when infections are detected quickly (e.g., through rapid testing), when contacts are traced with high probability, when the initial number of cases is low, and when social distancing and border restrictions are in place. However, the magnitude of the individual contribution of these factors in reducing epidemic spread and the impact of vaccination in determining contact tracing outputs is not fully understood. We present a delayed differential equation model to investigate how vaccine roll-out and the relaxation of social distancing requirements affect contact tracing practises. We provide an analytical criteria to determine the minimal contact tracing efficiency (defined as the the probability of identifying and quarantining contacts of symptomatic individuals) required to keep an outbreak under control, with respect to the contact rate and vaccination status of the population. Additionally, we consider how delays in outbreak detection and increased case importation rates affect the number of contacts to be traced daily. We show that in vaccinated communities a lower contact tracing efficiency is required to avoid uncontrolled epidemic spread, and delayed outbreak detection and relaxation of border restrictions do not lead to a significantly higher risk of overwhelming contact tracing. We find that investing in testing programs, rather than increasing the contact tracing capacity, has a larger impact in determining whether an outbreak will be controllable. This is because early detection activates contact tracing, which will slow, and eventually reverse exponential growth, while the contact tracing capacity is a threshold that will easily become overwhelmed if exponential growth is not curbed. Finally, we evaluate quarantine effectiveness during vaccine roll-out, by considering the proportion of people that will develop an infection while in isolation in relation to the vaccination status of the population and for different viral variants. We show that quarantine effectiveness decreases with increasing proportion of fully vaccinated individuals, and increases in the presence of more transmissible variants. These results suggest that a cost-effective approach during vaccine roll-out is to establish different quarantine rules for vaccinated and unvaccinated individuals, where rules should depend on viral transmissibility. Altogether, our study provides quantitative information for contact tracing downsizing during vaccine roll-out, to guide COVID-19 exit strategies.

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