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

2020 ◽  
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.

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

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.

scholarly journals Full-spectrum dynamics of the coronavirus disease outbreak in Wuhan, China: a modeling study of 32,583 laboratory-confirmed cases

2020 ◽  
Author(s):  
Xingjie Hao ◽  
Shanshan Cheng ◽  
Degang Wu ◽  
Tangchun Wu ◽  
Xihong Lin ◽  
...  
Keyword(s):  
Credible Interval ◽  
Disease Outbreak ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Time Varying ◽  
Full Spectrum ◽  
Population Movements ◽  
Transmission Rates ◽  
The Impact ◽  
Pharmaceutical Interventions

ABSTRACTVigorous non-pharmaceutical interventions have largely suppressed the COVID-19 outbreak in Wuhan, China. We developed a susceptible-exposed-infectious-recovered model to study the transmission dynamics and evaluate the impact of interventions using 32,583 laboratory-confirmed cases from December 8, 2019 till March 8, 2020, accounting for time-varying ascertainment rates, transmission rates, and population movements. The effective reproductive number R0 dropped from 3.89 (95% credible interval: 3.79-4.00) before intervention to 0.14 (0.11-0.28) after full-scale multi-8 pronged interventions. By projection, the interventions reduced the total infections in Wuhan by 96.5% till March 8. Furthermore, we estimated that 79% (lower bound: 60%) of the total infections were unascertained, potentially including asymptomatic and mild-symptomatic cases. The probability of resurgence was 0.22 and 0.10 based on models with 79% and 60% infections unascertained, respectively, assuming interventions were lifted after a 14-day period of no new ascertained infections. These results provide important implications for continuing surveillance and interventions to eventually contain the outbreak.

scholarly journals Modeling non-pharmaceutical interventions in the COVID-19 pandemic with survey-based simulations

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0259108
Author(s):  
Marius Kaffai ◽  
Raphael H. Heiberger
Keyword(s):  
Large Scale ◽  
Age Groups ◽  
Representative Survey ◽  
Home Office ◽  
Infected People ◽  
Demographic Groups ◽  
Federal States ◽  
Demographic Attributes ◽  
The Impact ◽  
Pharmaceutical Interventions

Governments around the globe use non-pharmaceutical interventions (NPIs) to curb the spread of coronavirus disease 2019 (COVID-19) cases. Making decisions under uncertainty, they all face the same temporal paradox: estimating the impact of NPIs before they have been implemented. Due to the limited variance of empirical cases, researchers could so far not disentangle effects of individual NPIs or their impact on different demographic groups. In this paper, we utilize large-scale agent-based simulations in combination with Susceptible-Exposed-Infectious-Recovered (SEIR) models to investigate the spread of COVID-19 for some of the most affected federal states in Germany. In contrast to other studies, we sample agents from a representative survey. Including more realistic demographic attributes that influence agents’ behavior yields accurate predictions of COVID-19 transmissions and allows us to investigate counterfactual what-if scenarios. Results show that quarantining infected people and exploiting industry-specific home office capacities are the most effective NPIs. Disentangling education-related NPIs reveals that each considered institution (kindergarten, school, university) has rather small effects on its own, yet, that combined openings would result in large increases in COVID-19 cases. Representative survey-characteristics of agents also allow us to estimate NPIs’ effects on different age groups. For instance, re-opening schools would cause comparatively few infections among the risk-group of people older than 60 years.

scholarly journals Modeling non-pharmaceutical interventions in the COVID-19 pandemic with survey-based simulations

2021 ◽  
Author(s):  
Marius Kaffai ◽  
Raphael H. Heiberger
Keyword(s):  
Large Scale ◽  
Age Groups ◽  
Representative Survey ◽  
Home Office ◽  
Infected People ◽  
Demographic Groups ◽  
Federal States ◽  
Demographic Attributes ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractGovernments around the globe use non-pharmaceutical interventions (NPIs) to curb the spread of coronavirus disease 2019 (COVID-19) cases. Making decisions under uncertainty, they all face the same temporal paradox: estimating the impact of NPIs before they have been implemented. Due to the limited variance of empirical cases, researcher could so far not disentangle effects of individual NPIs or their impact on different demographic groups. In this paper, we utilize large-scale agent-based simulations in combination with Susceptible-Exposed-Infectious-Recovered (SEIR) models to investigate the spread of COVID-19 for some of the most affected federal states in Germany. In contrast to other studies, we sample agents from a representative survey. Including more realistic demographic attributes that influence agents’ behavior yields accurate predictions of COVID-19 transmissions and allows us to investigate counterfactual “what-if” scenarios. Results show that quarantining infected people and exploiting industry-specific home office capacities are the most effective NPIs. Disentangling education-related NPIs reveals that each considered institution (kindergarten, school, university) has rather small effects on its own, yet, that combined openings would result in large increases in COVID-19 cases. Representative survey-characteristics of agents also allow us to estimate NPIs’ effects on different age groups. For instance, re-opening schools would cause comparatively few infections among the risk-group of people older than 60 years.

scholarly journals Evolving Epidemiology and Effect of Non-pharmaceutical Interventions on the Epidemic of Coronavirus Disease 2019 in Shenzhen, China

2020 ◽  
Author(s):  
Suli Huang ◽  
Zhen Zhang ◽  
Yongsheng Wu ◽  
Shujiang Mei ◽  
Yuan Li ◽  
...  
Keyword(s):  
Emergency Response ◽  
Attack Rate ◽  
Age Groups ◽  
Health Policies ◽  
Reproductive Number ◽  
Public Health Policies ◽  
The Third ◽  
Disease Information ◽  
Novel Coronavirus ◽  
Pharmaceutical Interventions

Previous studies have demonstrated the characteristics of patients with 2019 novel coronavirus disease (COVID-19). However, the effect of non-pharmaceutical interventions on the epidemic in Shenzhen, China remains unknown. Individual data of 417 cases were extracted from the epidemiological investigations and the National Infectious Disease Information System between January 1, 2020 and February 29, 2020. On the basis of important interventions, the epidemic was divided into four periods (January 1-15, January 16-22, January 23-February 5 and after February 6). We used a susceptible-exposed-infectious-asymptomatic-recovered model to evaluate the effect of interventions. Results suggested that about 53.7% were imported from Wuhan. The median age was 47 years and 52.8% were women. Severity risk increased with age and associated with male and co-existing disorders. The attack rate peaked in the third period and drastically decreased afterwards across sex, age groups and geographic regions. Children younger than 5 years showed a higher attack rate than those aged of 6~19. The effective reproductive number decreased from 1.44 to 0.05 after the highest level emergency response since January 23. Overall, the non-pharmaceutical interventions have effectively mitigated the COVID-19 outbreak in Shenzhen, China. These findings may facilitate the introduction of public health policies in other countries and regions.

scholarly journals Premature mortality attributable to COVID-19: potential years of life lost in 17 countries around the world, January–August 2020

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Maider Pagola Ugarte ◽  
Souzana Achilleos ◽  
Annalisa Quattrocchi ◽  
John Gabel ◽  
Ourania Kolokotroni ◽  
...  
Keyword(s):  
Age Groups ◽  
Premature Mortality ◽  
The United States ◽  
Cape Verde ◽  
Years Of Life Lost ◽  
Demographic Groups ◽  
The World ◽  
The Usa ◽  
Research Consortium ◽  
The Impact

Abstract Background Understanding the impact of the burden of COVID-19 is key to successfully navigating the COVID-19 pandemic. As part of a larger investigation on COVID-19 mortality impact, this study aims to estimate the Potential Years of Life Lost (PYLL) in 17 countries and territories across the world (Australia, Brazil, Cape Verde, Colombia, Cyprus, France, Georgia, Israel, Kazakhstan, Peru, Norway, England & Wales, Scotland, Slovenia, Sweden, Ukraine, and the United States [USA]). Methods Age- and sex-specific COVID-19 death numbers from primary national sources were collected by an international research consortium. The study period was established based on the availability of data from the inception of the pandemic to the end of August 2020. The PYLL for each country were computed using 80 years as the maximum life expectancy. Results As of August 2020, 442,677 (range: 18–185,083) deaths attributed to COVID-19 were recorded in 17 countries which translated to 4,210,654 (range: 112–1,554,225) PYLL. The average PYLL per death was 8.7 years, with substantial variation ranging from 2.7 years in Australia to 19.3 PYLL in Ukraine. North and South American countries as well as England & Wales, Scotland and Sweden experienced the highest PYLL per 100,000 population; whereas Australia, Slovenia and Georgia experienced the lowest. Overall, males experienced higher PYLL rate and higher PYLL per death than females. In most countries, most of the PYLL were observed for people aged over 60 or 65 years, irrespective of sex. Yet, Brazil, Cape Verde, Colombia, Israel, Peru, Scotland, Ukraine, and the USA concentrated most PYLL in younger age groups. Conclusions Our results highlight the role of PYLL as a tool to understand the impact of COVID-19 on demographic groups within and across countries, guiding preventive measures to protect these groups under the ongoing pandemic. Continuous monitoring of PYLL is therefore needed to better understand the burden of COVID-19 in terms of premature mortality.

scholarly journals Attack rate and the price of SARS-CoV-2 herd immunity in Brazil

2021 ◽  
Author(s):  
Tarcisio Rocha Filho ◽  
José Mendes ◽  
Carson Chow ◽  
James Phillips ◽  
Antônio Cordeiro ◽  
...  
Keyword(s):  
Attack Rate ◽  
Contact Structure ◽  
Compartmental Model ◽  
Total Population ◽  
Herd Immunity ◽  
Age Groups ◽  
Time Dependent ◽  
Contact Matrix ◽  
The City ◽  
Pharmaceutical Interventions

Abstract We introduce a compartmental model with age structure to study the dynamics of the SARS-COV−2 pandemic. The contagion matrix in the model is given by the product of a probability per contact with a contact matrix explicitly taking into account the contact structure among different age groups. The probability of contagion per contact is considered as time dependent to represent non-pharmaceutical interventions, and is fitted from the time series of deaths. The approach is used to study the evolution of the COVID−19 pandemic in the main Brazilian cities and compared to two good quality serological surveys. We also discuss with some detail the case of the city of Manaus which raised special attention due to a previous report of three-quarters attack rate by the end of 2020. We discuss estimates for Manaus and all Brazilian cities with a total population of more than one million. We also estimate the attack rate with respect to the total population, in each Brazilian state by January, 1 st 2021 and May, 23 2021.

Heterogeneity in norovirus shedding duration affects community risk

2013 ◽  
Vol 141 (8) ◽  
pp. 1572-1584 ◽  
Author(s):  
M. O. MILBRATH ◽  
I. H. SPICKNALL ◽  
J. L. ZELNER ◽  
C. L. MOE ◽  
J. N. S. EISENBERG
Keyword(s):  
Attack Rate ◽  
Transmission Model ◽  
Reproductive Number ◽  
Risk Models ◽  
Common Cause ◽  
Viral Shedding ◽  
Duration Data ◽  
Community Risk ◽  
Community Transmission ◽  
The Impact

SUMMARYNorovirus is a common cause of gastroenteritis in all ages. Typical infections cause viral shedding periods of days to weeks, but some individuals can shed for months or years. Most norovirus risk models do not include these long-shedding individuals, and may therefore underestimate risk. We reviewed the literature for norovirus-shedding duration data and stratified these data into two distributions: regular shedding (mean 14–16 days) and long shedding (mean 105–136 days). These distributions were used to inform a norovirus transmission model that predicts the impact of long shedders. Our transmission model predicts that this subpopulation increases the outbreak potential (measured by the reproductive number) by 50–80%, the probability of an outbreak by 33%, the severity of transmission (measured by the attack rate) by 20%, and transmission duration by 100%. Characterizing and understanding shedding duration heterogeneity can provide insights into community transmission that can be useful in mitigating norovirus risk.

scholarly journals Estimating the burden of SARS-CoV-2 in France

Science ◽  
2020 ◽  
Vol 369 (6500) ◽  
pp. 208-211 ◽  
Author(s):  
Henrik Salje ◽  
Cécile Tran Kiem ◽  
Noémie Lefrancq ◽  
Noémie Courtejoie ◽  
Paolo Bosetti ◽  
...  
Keyword(s):  
Intensive Care ◽  
Severe Acute Respiratory Syndrome ◽  
Credible Interval ◽  
Control Measures ◽  
Reproductive Number ◽  
Infected Population ◽  
Population Immunity ◽  
The Impact ◽  
Second Wave ◽  
Death Data

France has been heavily affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and went into lockdown on 17 March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find that 2.9% of infected individuals are hospitalized and 0.5% of those infected die (95% credible interval: 0.3 to 0.9%), ranging from 0.001% in those under 20 years of age to 8.3% in those 80 years of age or older. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 2.90 to 0.67 (77% reduction). By 11 May 2020, when interventions are scheduled to be eased, we project that 3.5 million people (range: 2.1 million to 6.0 million), or 5.3% of the population (range: 3.3 to 9.3%), will have been infected. Population immunity appears to be insufficient to avoid a second wave if all control measures are released at the end of the lockdown.

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

2020 ◽  
Author(s):  
Qimin Huang ◽  
Anirban Mondal ◽  
Xiaobing Jiang ◽  
Mary Ann Horn ◽  
Fei Fan ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Hospital Setting ◽  
Credible Interval ◽  
Contact Tracing ◽  
Global Public Health ◽  
Minimal Impact ◽  
Social Distancing ◽  
Work Related ◽  
The Impact ◽  
Outbreak Size

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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