scholarly journals Non-pharmaceutical interventions for containment, mitigation and suppression of COVID-19 infection

2020 ◽  
pp. 1-25
Author(s):  
Daniel F. Patiño-Lugo ◽  
Marcela Velez ◽  
Pamela Velásquez Salazar ◽  
Claudia Yaneth Vera-Giraldo ◽  
Viviana Vélez ◽  
...  
Keyword(s):  
Health Care Services ◽  
Social Impact ◽  
Scientific Evidence ◽  
Policy Decision ◽  
Substantial Effect ◽  
Contact Tracing ◽  
Social Distancing ◽  
First Case ◽  
Travel Restrictions ◽  
Pharmaceutical Interventions

The best available scientific evidence is required to design effective non-pharmaceutical interventions (NPIs) to help policymakers to contain COVID-19 outbreaks. The aim of this review is to describe which NPIs used different countries and a when they use them. It also explores how NPIs impact the number of cases, the mortality, and the capacity of health systems. We consulted eight web pages of transnational organizations, 17 of international media, 99 of government institutions in the 19 countries included, and besides, we included nine studies (out of 34 identified) that met inclusion criteria. We found that some countries are focused on establishing travel restrictions, isolation of identified cases, and high-risk people. Others have a more intense combination of mandatory quarantine and other drastic social distancing measures. Some countries have implemented interventions in the first fifteen days after detecting the first case, while others have taken more than 30 days. The effectiveness of isolated NPIs may be limited, but combined interventions have shown to be effective in reducing the transmissibility of the disease, the collapse of health care services, and mortality. When the number of new cases has been controlled, it is necessary to maintain social distancing measures, self-isolation, and contact tracing for several months. The policy decision-making in this time should be aimed to optimize the opportunities of saving lives, reducing the collapse of health services, and minimizing the economic and social impact over the general population, but principally over the most vulnerable. The timing of implementing and lifting interventions is likely to have a substantial effect on those objectives.

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.

scholarly journals Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks

2020 ◽  
Author(s):  
Daniele Proverbio ◽  
Françoise Kemp ◽  
Stefano Magni ◽  
Andreas Husch ◽  
Atte Aalto ◽  
...  
Keyword(s):  
Decision Makers ◽  
Contact Tracing ◽  
Online Tool ◽  
Seir Model ◽  
Social Distancing ◽  
Quantitative Understanding ◽  
Cross Country ◽  
Pharmaceutical Interventions

AbstractAgainst the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to suppress it, but the efficacy of distinct measures is not yet well quantified. In this paper, we propose a novel tool to achieve this quantification. In fact, this paper develops a new extended epidemic SEIR model, informed by a socio-political classification of different interventions, to assess the value of several suppression approaches. First, we inquire the conceptual effect of suppression parameters on the infection curve. Then, we illustrate the potential of our model on data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lock-down is an effective pandemic suppression measure, a combination of social distancing and contact tracing can achieve similar suppression synergistically. This quantitative understanding will support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model.

scholarly journals Predictive Modeling on the Number of Covid-19 Death Toll in the United States Considering the Effects of Coronavirus-Related Changes and Covid-19 Recovered Cases

2020 ◽  
Vol 5 (6) ◽  
pp. 1140-1155 ◽  
Author(s):  
Hoang Pham
Keyword(s):  
United States ◽  
United Kingdom ◽  
Policy Decision ◽  
The United States ◽  
Social Distancing ◽  
Death Toll ◽  
The United Kingdom ◽  
First Case ◽  
Staying At Home ◽  
At Home

COVID-19 is caused by a coronavirus called SARS-CoV-2. Many countries around the world implemented their own policies and restrictions designed to limit the spread of Covid-19 in recent months. Businesses and schools transitioned into working and learning remotely. In the United States, many states were under strict orders to stay home at least in the month of April. In recent weeks, there are some significant changes related restrictions include social-distancing, reopening states, and staying-at-home orders. The United States surpassed 2 million coronavirus cases on Monday, June 15, 2020 less than five months after the first case was confirmed in the country. The virus has killed at least 115,000 people in the United States as of Monday, June 15, 2020, according to data from Johns Hopkins University. With the recent easing of coronavirus-related restrictions and changes on business and social activity such as stay-at-home, social distancing since late May 2020 hoping to restore economic and business activities, new Covid-19 outbreaks are on the rise in many states across the country. Some researchers expressed concern that the process of easing restrictions and relaxing stay-at-home orders too soon could quickly surge the number of infected Covid-19 cases as well as the death toll in the United States. Some of these increases, however, could be due to more testing sites in the communities while others may be are the results of easing restrictions due to recent reopening and changed policies, though the number of daily death toll does not appear to be going down in recent days due to Covid-19 in the U.S. This raises the challenging question: • How can policy decision-makers and community leaders make the decision to implement public policies and restrictions and keep or lift staying-at-home orders of ongoing Covid-19 pandemic for their communities in a scientific way? In this study, we aim to develop models addressing the effects of recent Covid-19 related changes in the communities such as reopening states, practicing social-distancing, and staying-at-home orders. Our models account for the fact that changes to these policies which can lead to a surge of coronavirus cases and deaths, especially in the United States. Specifically, in this paper we develop a novel generalized mathematical model and several explicit models considering the effects of recent reopening states, staying-at-home orders and social-distancing practice of different communities along with a set of selected indicators such as the total number of coronavirus recovered and new cases that can estimate the daily death toll and total number of deaths in the United States related to Covid-19 virus. We compare the modeling results among the developed models based on several existing criteria. The model also can be used to predict the number of death toll in Italy and the United Kingdom (UK). The results show very encouraging predictability for the proposed models in this study. The model predicts that 128,500 to 140,100 people in the United States will have died of Covid-19 by July 4, 2020. The model also predicts that between 137,900 and 154,000 people will have died of Covid-19 by July 31, and 148,500 to 169,700 will have died by the end of August 2020, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the Covid-19 death data available on June 13, 2020. The model also predicts that 34,900 to 37,200 people in Italy will have died of Covid-19 by July 4, and 36,900 to 40,400 people will have died by the end of August based on the data available on June 13, 2020. The model also predicts that between 43,500 and 46,700 people in the United Kingdom will have died of Covid-19 by July 4, and 48,700 to 51,900 people will have died by the end of August, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the data available on June 13, 2020. The model can serve as a framework to help policy makers a scientific approach in quantifying decision-makings related to Covid-19 affairs.

scholarly journals COVID-19: Recent updates on SARS-CoV-2 and Preventing its Community Transmission in India by 21 Days Lockdown

2020 ◽  
Vol 14 (suppl 1) ◽  
pp. 921-929
Author(s):  
Satyajeet K. Pawar ◽  
Shivaji T. Mohite
Keyword(s):  
Hubei Province ◽  
Hand Washing ◽  
Contact Tracing ◽  
Wuhan City ◽  
Social Distancing ◽  
First Case ◽  
Rapid Spread ◽  
Community Transmission ◽  
Almost All

The current pandemic of COVID-19 has caused havoc all over world since its emergence and rapid spread. Within three months the virus SARS-CoV-2 which was isolated from pneumonia cases in Wuhan City, Hubei Province, China in late December 2019, has affected almost all countries. India reported its first case of COVID-19 from state of Kerala on January 30, 2020, a student returned from city of Wuhan. Till date in India the disease had affected 12759 patients with 420 deaths. With every passing day the mysterious virus is been uncovered with its unique characteristics enabling the researcher to unfold the various methods including hand washing and social distancing to curtail the pandemic. Measures like 21 days lockdown to certain extent are effective but considering asymptomatic spreaders, extended measured lockdowns will be useful in the long term war against COVID-19. Till the vaccine and therapeutic solutions are derived, answer to pandemic and SARS-CoV-2 lies in lockdown, social distancing, contact tracing and containment.

scholarly journals An evaluation of COVID-19 transmission control in Wenzhou using a modified SEIR model

2021 ◽  
Vol 149 ◽  
Author(s):  
Wenning Li ◽  
Jianhua Gong ◽  
Jieping Zhou ◽  
Lihui Zhang ◽  
Dongchuan Wang ◽  
...  
Keyword(s):  
Emergency Preparedness ◽  
Close Contact ◽  
Control Measures ◽  
Contact Tracing ◽  
Seir Model ◽  
Social Distancing ◽  
Infected People ◽  
Travel Restrictions ◽  
Developmental Characteristics ◽  
Novel Coronavirus

Abstract In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.

scholarly journals Modeling the evolution of SARS-CoV-2 under non-pharmaceutical interventions

2021 ◽  
Author(s):  
Yael Gurevich ◽  
Yoav Ram ◽  
Lilach Hadany
Keyword(s):  
Data Analysis ◽  
Diagnostic Tests ◽  
Viral Strain ◽  
Epidemiological Models ◽  
Social Distancing ◽  
Testing Rate ◽  
Travel Restrictions ◽  
Evolutionary Trajectories ◽  
Pharmaceutical Interventions

AbstractSocial and behavioral non-pharmaceutical interventions (NPIs), such as mask-wearing, social distancing, and travel restrictions, as well as diagnostic tests, have been broadly implemented in response to the COVID-19 pandemic. Epidemiological models and data analysis affirm that wide adoption of NPIs helps to control the pandemic. However, SARS-CoV-2 has extensively demonstrated its ability to evolve. Therefore, it is crucial to examine how NPIs may affect the evolution of the virus. Such evolution could have important effects on the spread and impact of the pandemic.We used evo-epidemiological models to examine the effect of non-pharmaceutical interventions and testing on two evolutionary trajectories for SARS-CoV-2: attenuation and test evasion. Our results show that when stronger measures are taken, selection may act to reduce virulence. Additionally, the timely application of NPIs could significantly affect the competition between viral strains, favoring reduced virulence. Furthermore, a higher testing rate can select for a test-evasive viral strain, even if that strain is less infectious than the detectable competing strain. Importantly, if a less detectable strain evolves, epidemiological metrics such as confirmed daily cases may distort our assessment of the pandemic. Our results highlight the important implications NPIs can have on the evolution of SARS-CoV-2.

scholarly journals Factors Associated with the Implementation of Non-Pharmaceutical Interventions for Reducing Coronavirus Disease 2019 (COVID-19): A Systematic Review

2021 ◽  
Vol 18 (8) ◽  
pp. 4274
Author(s):  
Krishna Regmi ◽  
Cho Mar Lwin
Keyword(s):  
Public Health ◽  
Positive Impact ◽  
Health Impact ◽  
Social Distancing ◽  
Factors Associated ◽  
Unpublished Studies ◽  
Travel Restrictions ◽  
Context Specific ◽  
Effective Public Health ◽  
Pharmaceutical Interventions

There has been much discussion recently about the importance of implementing non-pharmaceutical interventions (NPIs) to protect the public from coronavirus disease 2019 (COVID-19) infection. Different governments across the world have adopted NPIs (e.g., social distancing, quarantine, isolation, lockdowns, curfews, travel restrictions, closures of schools and colleges). Two fundamental strategies, namely a strict containment strategy—also called suppression strategy—and a mitigation strategy have been adopted in different countries, mainly to reduce the reproduction number (R0) to below one and hence to reduce case numbers to low levels or eliminate human-to-human transmission, as well as to use NPIs to interrupt transmission completely and to reduce the health impact of epidemics, respectively. However, the adoption of these NPI strategies is varied and the factors impacting NPI are inconsistent and unclear. This study, therefore, aimed to review the factors associated with the implementation of NPIs (social distancing, social isolation and quarantine) for reducing COVID-19. Following PRISMA guidelines, we searched for published and unpublished studies, undertaking a systematic search of: MEDLINE, EMBASE, Allied and Complementary Medicine, COVID-19 Research, WHO database on COVID-19, and Google Scholar. Thirty-three studies were included in the study. Seven descriptive themes emerged on enablers and barriers to NPIs: the positive impact of NPIs, effective public health interventions, positive change in people’s behaviour and concerns about COVID-19, the role of mass media, physical and psychological impacts, and ethnicity/age associated with COVID-19. This study has highlighted that the effectiveness of NPIs in isolation is likely to be limited, therefore, a combination of multiple measures e.g., SD, isolation and quarantine, and workplace distancing appeared more effective in reducing COVID-19. Studies suggest that targeted approaches alongside social distancing might be the way forward, and more acceptable. Further research to promote country- and context-specific adoption of NPIs to deliver public health measures is needed. Studies comparing the effectiveness of interventions and strategies will help provide more evidence for future pandemics.

scholarly journals Recapping The Latest Vaccine Developments

2021 ◽  
Vol 15 (1) ◽  
pp. 4
Author(s):  
Atikaran Krishnamoorthy
Keyword(s):  
Contact Tracing ◽  
Virus Spread ◽  
Phase 3 ◽  
Social Distancing ◽  
First Case

Since the first case was identified in Wuhan, China in November 2019, there have been 84.5 million cases of COVID-19 and 1.8 million deaths from this virus globally as of January 5, 20211. To combat this virus’ spread, various strategies have been employed, such as mask mandates, social distancing, increased COVID-19 testing, and contact tracing. Since December 2020, another strategy has been made available: vaccines. This is because three vaccines that showed promising Phase 3 results are currently in use to help curb COVID-19.

scholarly journals Fundamental limitations of contact tracing for COVID-19

FACETS ◽  
2021 ◽  
Vol 6 ◽  
pp. 1993-2001
Author(s):  
Paul Tupper ◽  
Sarah P. Otto ◽  
Caroline Colijn
Keyword(s):  
High Risk ◽  
Exponential Growth ◽  
Contact Tracing ◽  
Loss Of Control ◽  
Social Distancing ◽  
Pooled Testing ◽  
Fundamental Limitations ◽  
Travel Restrictions

Contact tracing has played a central role in COVID-19 control in many jurisdictions and is often used in conjunction with other measures such as travel restrictions and social distancing mandates. Contact tracing is made ineffective, however, by delays in testing, calling, and isolating. Even if delays are minimized, contact tracing triggered by testing of symptomatic individuals can only prevent a fraction of onward transmissions from contacts. Without other measures in place, contact tracing alone is insufficient to prevent exponential growth in the number of cases in a population with little immunity. Even when used effectively with other measures, occasional bursts in call loads can overwhelm contact tracing systems and lead to a loss of control. We propose embracing approaches to COVID-19 contact tracing that broadly test individuals without symptoms, in whatever way is economically feasible—either with fast and cheap tests that can be deployed widely, with pooled testing, or with screening of judiciously chosen groups of high-risk individuals. These considerations are important both in regions where widespread vaccination has been deployed and in those where few residents have been immunized.

scholarly journals Five approaches to the suppression of SARS-CoV-2 without intensive social distancing

2021 ◽  
Vol 288 (1949) ◽  
Author(s):  
John M. Drake ◽  
Kyle Dahlin ◽  
Pejman Rohani ◽  
Andreas Handel
Keyword(s):  
Narrow Range ◽  
Case Finding ◽  
Contact Tracing ◽  
Active Case Finding ◽  
Protective Measures ◽  
Social Distancing ◽  
Targeted Interventions ◽  
Wide Range ◽  
Alternative Approaches ◽  
Pharmaceutical Interventions

Initial efforts to mitigate transmission of SARS-CoV-2 relied on intensive social distancing measures such as school and workplace closures, shelter-in-place orders and prohibitions on the gathering of people. Other non-pharmaceutical interventions for suppressing transmission include active case finding, contact tracing, quarantine, immunity or health certification, and a wide range of personal protective measures. Here we investigate the potential effectiveness of these alternative approaches to suppression. We introduce a conceptual framework represented by two mathematical models that differ in strategy. We find both strategies may be effective, although both require extensive testing and work within a relatively narrow range of conditions. Generalized protective measures such as wearing face masks, improved hygiene and local reductions in density are found to significantly increase the effectiveness of targeted interventions.

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