scholarly journals A sub-national analysis of the rate of transmission of COVID-19 in Italy

2020 ◽  
Author(s):  
Michaela A. C. Vollmer ◽  
Swapnil Mishra ◽  
H Juliette T Unwin ◽  
Axel Gandy ◽  
Thomas A Mellan ◽  
...  
Keyword(s):  
Attack Rate ◽  
Herd Immunity ◽  
Transmission Intensity ◽  
Contact Tracing ◽  
Social Distancing ◽  
Italian Regions ◽  
Transmission Reduction ◽  
Using Data ◽  
National Analysis ◽  
Pharmaceutical Interventions

Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a second wave will not be immediately apparent from just monitoring of the daily number of deaths. Our results suggest that SARS-CoV-2 transmission as well as mobility should be closely monitored in the next weeks and months. To compensate for the increase in mobility that will occur due to the relaxation of the currently implemented NPIs, adherence to the recommended social distancing measures alongside enhanced community surveillance including swab testing, contact tracing and the early isolation of infections are of paramount importance to reduce the risk of resurgence in transmission.

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.

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 Human agency and infection rates: Implications for social distancing during epidemics

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243699
Author(s):  
Christopher Bronk Ramsey
Keyword(s):  
Theoretical Model ◽  
Infection Rate ◽  
Herd Immunity ◽  
Contact Tracing ◽  
Specific Level ◽  
Social Distancing ◽  
Long Run ◽  
Social Settings ◽  
Wide Range ◽  
Almost All

Social distancing is an important measure in controlling epidemics. This paper presents a simple theoretical model focussed on the implications of the wide range in interaction rates between individuals, both within the workplace and in social settings. The model is based on well-mixed populations and so is not intended for studying geographic spread. The model shows that epidemic growth rate is largely determined by the upper interactivity quantiles of society, implying that the most efficient methods of epidemic control are interaction capping approaches rather than overall reductions in interaction. The theoretical model can also be applied to look at aspects of the dynamics of epidemic progression under various scenarios. The theoretical model suggests that with no intervention herd immunity would be achieved with a lower overall infection rate than if variation in interaction rate is ignored, because by this stage almost all the most interactive members of society would have had the infection; however the overall mortality with such an approach is very high. Scenarios for mitigation and suppression suggest that, by using interactivity capping, it should be possible to control an epidemic without extreme sanctions on the majority of the population if R0 of the uncontrolled infection is 2.4. However to control the infection rate to a specific level will always require measures to be switched on and off and for this reason elimination is likely to be a less costly policy in the long run. While social distancing alone can be used for elimination, it would not on its own be an efficient mechanism to prevent reinfection. The use of robust testing, quarantining, and contact tracing would strengthen any social distancing measures, speed up elimination, and be a better tool for the prevention of infection or reinfection. Because the analysis presented here is theoretical, and not data-driven, it is intended to be a stimulus for further data-collection, particularly on individual interactivity levels, and for more comprehensive modelling which takes account of the type of heterogeneity discussed here. While there are some clear lessons from the simple model presented here, policy makers should have these tested and validated by epidemiological specialists before acting on them.

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 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, 1st 2021 and May, 23 2021.

scholarly journals Epidemiology and transmission of COVID-19 in cases and close contacts in Georgia in the first four months of the epidemic

2021 ◽  
Author(s):  
Josephine G. Walker ◽  
Irine Tskhomelidze ◽  
Adam Trickey ◽  
Vladimer Getia ◽  
Lia Gvinjilia ◽  
...  
Keyword(s):  
Attack Rate ◽  
Index Case ◽  
Family Members ◽  
Medical Personnel ◽  
Added Value ◽  
Contact Tracing ◽  
Routine Testing ◽  
Social Mixing ◽  
Successful Control ◽  
Pharmaceutical Interventions

AbstractBackgroundBetween February and June 2020, 917 COVID-19 cases and 14 COVID-19-related deaths were reported in Georgia. Early on, Georgia implemented non-pharmaceutical interventions (NPI) including extensive contact tracing and restrictions on movement.AimTo characterize the demographics of those tested and infected with COVID-19 in Georgia; to evaluate factors associated with transmission between cases and their contacts; and to determine how transmission varied due to NPI up to 24 June 2020.MethodsWe use data gathered by the Georgian National Center for Disease Control on all polymerase chain reaction tests conducted (among symptomatic patients, through routine testing and contact tracing); hospitalization data for confirmed cases, and contact tracing data. We calculated the number of contacts per index case, the secondary attack rate (% contacts infected), and effective R number (new cases per index case), and used logistic regression to estimate how age, gender, and contact type affected transmission.ResultsMost contacts and transmission events were between family members. Contacts <40 years were less likely to be infected, while infected individuals >50 were more likely to die than younger patients. Contact tracing identified 917 index cases with mean 3.1 contacts tested per case, primarily family members. The overall secondary attack rate was 28% (95% confidence interval [CI]: 26-29%) and effective R number was 0.87 (95%CI 0.81-0.93), peaking at 1.1 (95%CI 0.98-1.2) during the period with strongest restrictions.ConclusionGeorgia effectively controlled the COVID-19 epidemic in its early stages, although evidence does not suggest transmission was reduced during the strict lockdown period.Research in ContextEvidence before this studyWe searched PubMed and MedRxiv for papers reporting research using contact tracing data to evaluate the characteristics of the COVID-19 epidemic in any country. A number of analyses were identified from Asia, including China, Taiwan, Maldives, Thailand, South Korea, and India, but none from other regions other than one previous analysis conducted in Europe, focusing on the first two months of the COVID-19 epidemic in Cyprus. Studies evaluated number of contacts and different contact types, secondary attack rate, and effective R number. However, none of these studies compared characteristics between different time periods or under varied levels of non-pharmaceutical interventions or restrictions on social mixing.Added value of this studyIn this study, we use contact tracing data from Georgia from all cases identified in the first four months of the epidemic, as well as testing and hospitalization data, to evaluate the number and type of contacts, effective R number (new cases per index case), and secondary attack rate (proportion of contacts infected) in this population, and whether these measures changed before, during, and after the lockdown period. We also evaluated how the chance of transmission varied by type of index case and contact. Our results indicate that number of contacts remained relatively low throughout the study period, so although the secondary attack rate was relatively high (28%) compared to that seen in studies in Asia (10-15%), the effective R number was less than one overall, peaking at 1.1 (0.98-1.2) during the strictest lockdown period, with easing of restrictions corresponding to a lower effective R of 0.87 (0.77-0.97). Most transmission occurred between family members with transmission very low between co-workers, friends, neighbours, and medical personnel, indicating that the restrictions on social mixing were effective at keeping the epidemic under control during this period.Implications of all the available evidenceOur study presents the first analysis of the successful control of a COVID-19 epidemic in a European country, indicating that despite a high secondary attack rate, reduction in contacts outside the home, and a well-timed lockdown, were able to keep transmission under control.

scholarly journals A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities

2021 ◽  
Vol 18 (181) ◽  
pp. 20210112
Author(s):  
Ling Yin ◽  
Hao Zhang ◽  
Yuan Li ◽  
Kang Liu ◽  
Tianmu Chen ◽  
...  
Keyword(s):  
Census Data ◽  
Herd Immunity ◽  
Risk Tolerance ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
Shenzhen City ◽  
Other World ◽  
Work Class ◽  
Pharmaceutical Interventions

Before herd immunity against Coronavirus disease 2019 (COVID-19) is achieved by mass vaccination, science-based guidelines for non-pharmaceutical interventions are urgently needed to reopen megacities. This study integrated massive mobile phone tracking records, census data and building characteristics into a spatially explicit agent-based model to simulate COVID-19 spread among 11.2 million individuals living in Shenzhen City, China. After validation by local epidemiological observations, the model was used to assess the probability of COVID-19 resurgence if sporadic cases occurred in a fully reopened city. Combined scenarios of three critical non-pharmaceutical interventions (contact tracing, mask wearing and prompt testing) were assessed at various levels of public compliance. Our results show a greater than 50% chance of disease resurgence if the city reopened without contact tracing. However, tracing household contacts, in combination with mandatory mask use and prompt testing, could suppress the probability of resurgence under 5% within four weeks. If household contact tracing could be expanded to work/class group members, the COVID resurgence could be avoided if 80% of the population wear facemasks and 40% comply with prompt testing. Our assessment, including modelling for different scenarios, helps public health practitioners tailor interventions within Shenzhen City and other world megacities under a variety of suppression timelines, risk tolerance, healthcare capacity and public compliance.

scholarly journals Self-Burnout – A New Path to the End of COVID-19

2020 ◽  
Author(s):  
B Shayak ◽  
Richard H Rand
Keyword(s):  
Social Mobility ◽  
Herd Immunity ◽  
The Self ◽  
Contact Tracing ◽  
Actual Number ◽  
Social Distancing ◽  
First Order ◽  
The Social ◽  
Linear Delay ◽  
Delay Differential

ABSTRACTIn this work we use mathematical modeling to describe a possible route to the end of COVID-19, which does not feature either vaccination or herd immunity. We call this route self-burnout. We consider a region with (a) no influx of corona cases from the outside, (b) extensive social distancing, though not necessarily a full lockdown, and (c) high testing capacity relative to the actual number of new cases per day. These conditions can make it possible for the region to initiate the endgame phase of epidemic management, wherein the disease is slowly made to burn itself out through a combination of social distancing, sanitization, contact tracing and preventive testing. The dynamics of the case trajectories in this regime are governed by a single-variable first order linear delay differential equation, whose stability criterion can be obtained analytically. Basis this criterion, we conclude that the social mobility restrictions should be such as to ensure that on the average, one person interacts closely (from the transmission viewpoint) with at most one other person over a 4-5 day period. If the endgame can be played out for a long enough time, we claim that the Coronavirus can eventually get completely contained without affecting a significant fraction of the region’s population. We present estimates of the duration for which the epidemic is expected to last, finding an interval of approximately 5-15 weeks after the self-burnout phase is initiated. South Korea, Austria, Australia, New Zealand and the states of Goa, Kerala and Odisha in India appear to be well on the way towards containing COVID by this method.

scholarly journals Estimating Household Transmission of SARS-CoV-2

2020 ◽  
Author(s):  
Mihaela Curmei ◽  
Andrew Ilyas ◽  
Owain Evans ◽  
Jacob Steinhardt
Keyword(s):  
Attack Rate ◽  
False Negative ◽  
Policy Implications ◽  
Contact Tracing ◽  
Reliable Estimate ◽  
False Negatives ◽  
Social Distancing ◽  
Household Transmission ◽  
Contact Patterns ◽  
Community Transmission

Introduction and GoalsSARS-CoV-2 is transmitted both in the community and within households. Social distancing and lockdowns reduce community transmission but do not directly address household transmission. We provide quantitative measures of household transmission based on empirical data, and estimate the contribution of households to overall spread. We highlight policy implications from our analysis of household transmission, and more generally, of changes in contact patterns under social distancing.MethodsWe investigate the household secondary attack rate (SAR) for SARS-CoV-2, as well as Rh, which is the average number of within-household infections caused by a single index case. We identify previous works that estimated the SAR. We correct these estimates based on the false-negative rate of PCR testing and the failure to test asymptomatics. Results are pooled by a hierarchical Bayesian random-effects model to provide a meta-analysis estimate of the SAR. We estimate Rh using results from population testing in Vo’, Italy and contact tracing data that we curate from Singapore. The code and data behind our analysis are publicly available1.ResultsWe identified nine studies of the household secondary attack rate. Our modeling suggests the SAR is heterogeneous across studies. The pooled central estimate of the SAR is 30% but with a posterior 95% credible interval of (0%, 67%) reflecting this heterogeneity. This corresponds to a posterior mean for the SAR of 30% (18%, 43%) and a standard deviation of 15% (9%, 27%). If results are not corrected for false negatives and asymptomatics, the pooled central estimate for the SAR is 20% (0%, 43%). From the same nine studies, we estimate Rh to be 0.47 (0.13, 0.77). Using contact tracing data from Singapore, we infer an Rh value of 0.32 (0.22, 0.42). Population testing data from Vo’ yields an Rh estimate of 0.37 (0.34, 0.40) after correcting for false negatives and asymptomatics.InterpretationOur estimates of Rh suggest that household transmission was a small fraction (5%-35%) of R before social distancing but a large fraction after (30%-55%). This suggests that household transmission may be an effective target for interventions. A remaining uncertainty is whether household infections actually contribute to further community transmission or are contained within households. This can be estimated given high-quality contact tracing data.More broadly, our study points to emerging contact patterns (i.e., increased time at home relative to the community) playing a role in transmission of SARS-CoV-2. We briefly highlight another instance of this phenomenon (differences in contact between essential workers and the rest of the population), provide coarse estimates of its effect on transmission, and discuss how future data could enable a more reliable estimate.

scholarly journals Using Non-Pharmaceutical Interventions and High Isolation of Asymptomatic Carriers to Contain the Spread of SARS-CoV-2 in Nursing Homes

2021 ◽  
Author(s):  
Alec J. Schmidt ◽  
Yury García ◽  
Diego Pinheiro ◽  
Tom Reichert ◽  
Miriam A. Nuño
Keyword(s):  
Attack Rate ◽  
Group Living ◽  
Daily Basis ◽  
Contact Tracing ◽  
Term Care ◽  
Care Facilities ◽  
Degree Of Control ◽  
Antigen Tests ◽  
Pharmaceutical Interventions

ABSTRACTObjectiveUsing a pandemic influenza model modified for COVID-19, this study investigated the degree of control over pre-symptomatic transmission that common non-pharmaceutical interventions (NPIs) would require to reduce the spread in long-term care facilities.MethodsWe created a stochastic compartmental SEIR model with Poisson-distributed transition states that compared the effect of R0, common NPIs, and isolation rates of pre-symptomatic carriers primarily on attack rate, peak cases, and timing in a 200-resident nursing home. Model sensitivity was assessed with 1st order Sobol’ indices.ResultsThe most rigorous NPIs decreased the peak number of infections by 4.3 and delayed the peak by 9.7 days in the absence of pre-symptomatic controls. Reductions in attack rate were not likely, even with rigorous application of all defined NPIs, unless pre-symptomatic carriers were identified and isolated at rates exceeding 76%. Attack rate was most sensitive to the pre-symptomatic isolation rate (Sobol’ index > 0.7) and secondarily to R0.ConclusionsCommon NPIs delayed and reduced epidemic peaks. Reducing attack rates ultimately required efficient isolation of pre-symptomatic cases, including rapid antigen tests on a nearly daily basis. This must be accounted for in testing and contact tracing plans for group living settings.

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