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

Science ◽  
2020 ◽  
Vol 368 (6498) ◽  
pp. 1481-1486 ◽  
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.

scholarly journals Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China

2020 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Yuxia Liang ◽  
Yan Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Hunan Province ◽  
Contact Tracing ◽  
Transmission Model ◽  
The Novel ◽  
School Closures ◽  
Social Distancing ◽  
Susceptibility To Infection ◽  
Contact Patterns ◽  
Age Profile ◽  
Novel Coronavirus

AbstractStrict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

scholarly journals Isolation and contact tracing can tip the scale to containment of COVID-19 in populations with social distancing

2020 ◽  
Author(s):  
Mirjam E. Kretzschmar ◽  
Ganna Rozhnova ◽  
Michiel van Boven
Keyword(s):  
Reproduction Number ◽  
Added Value ◽  
Contact Tracing ◽  
Transmission Model ◽  
Critical Threshold ◽  
Strong Impact ◽  
Social Distancing ◽  
Household Contacts ◽  
Novel Coronavirus ◽  
The Impact

AbstractBackgroundNovel coronavirus (SARS-CoV-2) has extended its range of transmission in all parts of the world, with substantial variation in rates of transmission and severity of associated disease. Many countries have implemented social distancing as a measure to control further spread.MethodsWe evaluate whether and under which conditions containment or slowing down COVID-19 epidemics are possible by isolation and contact tracing in settings with various levels of social distancing. We use a stochastic transmission model in which every person generates novel infections according to a probability distribution that is affected by the incubation period distribution (time from infection to symptoms), distribution of the latent period (time from infection to onset of infectiousness), and overall transmissibility. The model distinguishes between close contacts (e.g., within a household) and other contacts in the population. Social distancing affects the number of contacts outside but not within the household.FindingsThe proportion of asymptomatic or unascertained cases has a strong impact on the controllability of the disease. If the proportion of asymptomatic infections is larger than 30%, contact tracing and isolation cannot achieve containment for an R0 of 2.5. Achieving containment by social distancing requires a reduction of numbers of non-household contacts by around 90%. Depending on the realized level of contact reduction, tracing and isolation of only household contacts, or of household and non-household contacts are necessary to reduce the effective reproduction number to below 1. A combination of social distancing with isolation and contact tracing leads to synergistic effects that increase the prospect of containment.InterpretationIsolation and contact tracing can be an effective means to slow down epidemics, but only if the majority of cases are ascertained. In a situation with social distancing, contact tracing can act synergistically and tip the scale towards containment, and can therefore be a tool for controlling COVID-19 epidemics as part of an exit strategy from current lockdown measures.FundingThis research was partly funded by ZonMw project number 91216062.Research in contextEvidence before this studyAs of 8 April 2020, the novel coronavirus (SARS-CoV-2) has spread to more than 170 countries and has caused near 90,000 deaths of COVID-19 worldwide. In the absence of effective medicines and vaccines, the preventive measures are limited to social distancing, isolation of confirmed and suspected cases, and identification and quarantining of their contacts. Evidence suggests that a substantial portion of transmission may occur before the onset of symptoms and before cases can be isolated, and that many cases remain unascertained. This has potentially important implications for the prospect of containment by combinations of these measures.Added value of this studyUsing a stochastic transmission model armed with current best estimates of epidemiological parameters, we evaluated under which conditions containment could be achieved with combinations of social distancing, isolation and contact tracing. We investigated the level of social distancing needed for containment, and how an additional implementation of isolation and contact tracing may likely help to in reducing the effective reproduction number to below 1, the critical threshold. We analyzed what proportion of household and non-household contacts need to be isolated effectively to achieve containment depending on the level of social distancing in the population. We estimated the impact of combinations of these measures on epidemic growth rate and doubling time for the number of infections. We find that under realistic assumptions on the level of social distancing, additional isolation and contact tracing are needed for stopping the epidemic. Whether quarantining only household contacts is sufficient, depends on levels of social distancing and timeliness of tracing and isolation.Implications of all the available evidenceOur analyses based on best understanding of the epidemiology of COVID-19, highlight that if social distancing is not complete, isolation and contact tracing at least of household contacts can help to delay and lower the epidemic peak. High levels of timely contact tracing of household and non-household contacts may be sufficient to control the epidemic.

scholarly journals Digital proximity tracing on empirical contact networks for pandemic control

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Outbreaks ◽  
Physical Distance ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Modeling Framework ◽  
Infectious Disease Outbreaks ◽  
Contact Patterns ◽  
Contact Data ◽  
The Impact

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.

scholarly journals Impact of self-imposed prevention measures and short-term government intervention on mitigating and delaying a COVID-19 epidemic

2020 ◽  
Author(s):  
Alexandra Teslya ◽  
Thi Mui Pham ◽  
Noortje G. Godijk ◽  
Mirjam E. Kretzschmar ◽  
Martin C.J. Bootsma ◽  
...  
Keyword(s):  
Attack Rate ◽  
Government Intervention ◽  
Healthcare Systems ◽  
Transmission Model ◽  
Prevention Measures ◽  
Short Term ◽  
Government Interventions ◽  
Social Distancing ◽  
Peak Number ◽  
The Impact

AbstractBackgroundWith new cases of COVID-19 surging around the world, many countries have to prepare for moving beyond the containment phase. Prediction of the effectiveness of non-case-based interventions for mitigating, delaying or preventing the epidemic is urgent, especially for countries affected by the ongoing seasonal influenza activity.MethodsWe developed a transmission model to evaluate the impact of self-imposed prevention measures (handwashing, mask-wearing, and social distancing) due to the spread of COVID-19 awareness and of short-term government-imposed social distancing on the peak number of diagnoses, attack rate and time until the peak number of diagnoses.FindingsFor fast awareness spread in the population, self-imposed measures can significantly reduce the attack rate, diminish and postpone the peak number of diagnoses. A large epidemic can be prevented if the efficacy of these measures exceeds 50%. For slow awareness spread, self-imposed measures reduce the peak number of diagnoses and attack rate but do not affect the timing of the peak. Early implementation of short-term government interventions can only delay the peak (by at most 7 months for a 3-month intervention).InterpretationHandwashing, mask-wearing and social distancing as a reaction to information dissemination about COVID-19 can be effective strategies to mitigate and delay the epidemic. We stress the importance of rapidly spreading awareness on the use of these self-imposed prevention measures in the population. Early-initiated short-term government-imposed social distancing can buy time for healthcare systems to prepare for an increasing COVID-19 burden.FundingThis research was funded by ZonMw project 91216062, One Health EJP H2020 project 773830, Aidsfonds project P-29704.Research in contextEvidence before this studyEvidence to date suggests that containment of SARS-CoV-2 using quarantine, travel restrictions, isolation of symptomatic cases, and contact tracing may need to be supplemented by other interventions. Given its rapid spread across the world and immense implications for public health, it is urgent to understand whether non-case-based interventions can mitigate, delay or even prevent a COVID-19 epidemic. One such strategy is a broader-scale contact rate reduction enforced by governments which was used during previous outbreaks, e.g., the 1918 influenza pandemic and the 2009 influenza A/H1N1 pandemic in Mexico. Alternatively, governments and media may stimulate self-imposed prevention measures (handwashing, mask-wearing, and social distancing) by generating awareness about COVID-19, especially when economic and societal consequences are taken into account. Both of these strategies may have a significant impact on the outbreak dynamics. Currently, there are no comparative studies that investigate their viability for controlling a COVID-19 epidemic.Added value of this studyUsing a transmission model parameterized with current best estimates of epidemiological parameters, we evaluated the impact of handwashing, mask-wearing, and social distancing due to COVID-19 awareness and of government-imposed social distancing on the peak number of diagnoses, attack rate, and time until the peak number of diagnoses. We show that a short-term (1-3 months) government intervention initiated early into the outbreak can only delay the peak number of diagnoses but neither alters its magnitude nor the attack rate. Our analyses also highlight the importance of spreading awareness about COVID-19 in the population, as the impact of self-imposed measures is strongly dependent on it. When awareness spreads fast, simple self-imposed measures such as handwashing are more effective than short-term government intervention. Self-imposed measures do not only diminish and postpone the peak number of diagnoses, but they can prevent a large epidemic altogether when their efficacy is sufficiently high (above 50%). Qualitatively, these results will aid public health professionals to compare and select interventions for designing effective outbreak control policies.Implications of all available evidenceOur results highlight that dissemination of evidence-based information about effective prevention measures (hand-washing, mask-wearing, and self-imposed social distancing) can be a key strategy for mitigating and postponing a COVID-19 epidemic. Government interventions (e.g., closing schools and prohibiting mass gatherings) implemented early into the epidemic and lasting for a short-time can only buy time for healthcare systems to prepare for an increasing COVID-19 burden.

How did Autistic Children, and their Parents, Experience School Transition during the COVID-19 Pandemic?

2021 ◽  
Author(s):  
Aimee Code ◽  
Umar Toseeb ◽  
Kathryn Asbury ◽  
Laura Fox
Keyword(s):  
School Transition ◽  
School Closure ◽  
School Transitions ◽  
Autistic Children ◽  
Structured Interviews ◽  
School Closures ◽  
Social Distancing ◽  
New School ◽  
The Uk ◽  
The Impact

Due to the COVID-19 pandemic and resultant school closures, social distancing measures, and restrictions placed on routine activities, the start of the academic year in September 2020 was a unique time for those transitioning to a new school. This study aimed to explore the experiences of parents who supported autistic children making a school transition in 2020, and to examine what impact parents perceived the COVID-19 pandemic had on their child’s school transition. Emphasis was placed on identifying facilitating factors that had benefitted school transitions, and barriers, which had negatively impacted these experiences. Semi-structured interviews were carried out with 13 parents of autistic children in the UK. Reflexive thematic analysis was carried out to identify themes in interview data. Parents reported a variety of experiences, and factors that were perceived as facilitatory to some were observed to be barriers by others. For some parents, the COVID-19 pandemic negatively impacted aspects of school transitions. For example, school closure in March 2020, being unable to visit their child’s new school, and social distancing measures were discussed as being barriers to an easy transition. However, other parents identified these factors as being facilitatory for their child or reported that these circumstances created opportunities to approach the school transition in a unique, improved manner. This paper sheds light on the heterogeneity of experiences and perceptions of parents of autistic children, and highlights the need to examine the impact of COVID-19 on school transitions, including practices which may be advantageous to retain.

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

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.

scholarly journals Reactive school closure weakens the network of social interactions and reduces the spread of influenza

2019 ◽  
Vol 116 (27) ◽  
pp. 13174-13181 ◽  
Author(s):  
Maria Litvinova ◽  
Quan-Hui Liu ◽  
Evgeny S. Kulikov ◽  
Marco Ajelli
Keyword(s):  
Social Interactions ◽  
Influenza Season ◽  
School Closure ◽  
Transmission Model ◽  
Modeling Framework ◽  
School Closures ◽  
Student Absenteeism ◽  
Contact Survey ◽  
Closure Policy ◽  
The Impact

School-closure policies are considered one of the most promising nonpharmaceutical interventions for mitigating seasonal and pandemic influenza. However, their effectiveness is still debated, primarily due to the lack of empirical evidence about the behavior of the population during the implementation of the policy. Over the course of the 2015 to 2016 influenza season in Russia, we performed a diary-based contact survey to estimate the patterns of social interactions before and during the implementation of reactive school-closure strategies. We develop an innovative hybrid survey-modeling framework to estimate the time-varying network of human social interactions. By integrating this network with an infection transmission model, we reduce the uncertainty surrounding the impact of school-closure policies in mitigating the spread of influenza. When the school-closure policy is in place, we measure a significant reduction in the number of contacts made by students (14.2 vs. 6.5 contacts per day) and workers (11.2 vs. 8.7 contacts per day). This reduction is not offset by the measured increase in the number of contacts between students and nonhousehold relatives. Model simulations suggest that gradual reactive school-closure policies based on monitoring student absenteeism rates are capable of mitigating influenza spread. We estimate that without the implemented reactive strategies the attack rate of the 2015 to 2016 influenza season would have been 33% larger. Our study sheds light on the social mixing patterns of the population during the implementation of reactive school closures and provides key instruments for future cost-effectiveness analyses of school-closure policies.

scholarly journals Impact of the Health Transformation Plan on the Number of Surgical Operations and Their Cancelation

2019 ◽  
Vol 56 ◽  
pp. 004695801984638
Author(s):  
MahmoodReza Miri Bonjar ◽  
Mohammad Khammarnia ◽  
Mahdie Bakhshi ◽  
Alireza Ansari-Moghaddam ◽  
Hassan Okati–Aliabad ◽  
...  
Keyword(s):  
Health Insurance ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Outpatient Service ◽  
Public Hospitals ◽  
Inpatient Service ◽  
Treatment Needs ◽  
Study Population ◽  
The Impact ◽  
Surgical Operations

Operation cancelations are a serious problem with undesirable consequences. The Health Transformation Plan was launched in the health system of Iran on May 5, 2014, to enhance the efficiency and quality of services in public hospitals. Comprehensive coverage of patients’ basic treatment needs and reduction of patients’ out-of-pocket expenditures through insurance for all are other objectives of Health Transformation Plan as well. Then, the present study aimed to determine the impact of the Health Transformation Plan on the number of surgical operations and the cancelation of elective surgeries within public hospitals of Iran. This retrospective comparative study was conducted in 2017 within 2 tertiary public hospitals in the South-East of Iran. Using systematic random sampling method and census, 8138 scheduled surgical files and all canceled operations files were reviewed from April 2012 to March 2017, respectively. A standard checklist was used for data collection. The data were analyzed using χ2 test and a logistic regression model in SPSS, version 21. The study population was 8138 patients with mean age of 33 ± 19 years. Female patients comprised about 51% of the study population (n = 4115), and nearly two-third of them were married (n = 5192 [63.79%]). Coverage by Iranian health insurance was reported in more than half of patients (n = 4415 [54.79%]). The common reason for surgeries was injury and poisoning (n = 2814 [34.52%]) followed by delivery (n = 1747 [21.46%]). The number of operations increased from 26 677 before Health Transformation Plan (cancelation rate = 1.5%) to 33 190 after Health Transformation Plan (cancelation rate = 2.0%). The cancelation rate had a significant relationship with age (odds ratio = 1.009; confidence interval: 1.00-1.01), health insurance status (odds ratio = 2.12; confidence interval: 1.33-3.38), outpatient service referrals (odds ratio = 0.5; confidence interval: 0.43-0.62), inpatient service referrals (odds ratio = 1.5; confidence interval: 1.36-1.77), and surgical types ( P < .05). In general, the Health Transformation Plan was markedly associated with a rise in the number of surgeries and cancelation rate in the public hospitals. The information obtained in the present study concerning the causes of operation cancelations can be used to decrease the number of future cancelations.

Sign in / Sign up

Export Citation Format

Share Document