scholarly journals Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns

2021 ◽  
Vol 17 (2) ◽  
pp. e1008713 ◽  
Author(s):  
Joshua Havumaki ◽  
Ted Cohen ◽  
Chengwei Zhai ◽  
Joel C. Miller ◽  
Seth D. Guikema ◽  
...  
Keyword(s):  
Population Level ◽  
Contact Tracing ◽  
Spatially Explicit Model ◽  
Household Transmission ◽  
Contact Patterns ◽  
Social Mixing ◽  
High Incidence ◽  
Community Transmission ◽  
The Impact ◽  
The Relationship

There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

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 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 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.

Situating ‘careful surveillance’

2021 ◽  
pp. 136787792199745
Author(s):  
Mark Andrejevic ◽  
Hugh Davies ◽  
Ruth DeSouza ◽  
Larissa Hjorth ◽  
Ingrid Richardson
Keyword(s):  
Public Health ◽  
Public Space ◽  
Social Care ◽  
Cultural Practices ◽  
Contact Tracing ◽  
Social Distancing ◽  
Health Measures ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

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

scholarly journals High Incidence of Preoperative Mild Cognitive Impairment in Elderly Surgical Patients

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniel Newman MSc, ◽  
Beth-Ann Cummings MD MSc ◽  
Howard Chertkow MD ◽  
Shannon Fraser MD MSc ◽  
Simon Bergman MD MSc
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Elderly Patients ◽  
Prospective Observational Study ◽  
Elective Surgery ◽  
Surgical Morbidity ◽  
Lengths Of Stay ◽  
High Incidence ◽  
The Impact ◽  
The Relationship

Post-operative delirium in elderly patients is associated with higher mortality and longer lengths of stay. This prospective observational study investigated the incidences of preoperative mild cognitive impairment (MCI) and post-operative delirium among elderly patients undergoing elective surgery at the authors’ institution, the relationship between MCI and delirium, and the impact of delirium on surgical morbidity and lengths of stay. The authors found that although MCI did not predict post-operative delirium, the high incidence of MCI in elective surgery patients warrants further study.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: A modelling study

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Population Level ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions

Background: Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods: We fit a metapopulation Susceptible-Exposed-Infectious-Recovered (SEIR) model to reported cases stratified by two groups to estimate the impact of a lockdown on the effective reproduction number (Re). We estimated the basic reproduction number (R0) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the lockdown. We estimated R­e values of both groups before and after the lockdown, simulated the effect of these values on epidemic curves and explored a range of cross-transmission scenarios. Results: We estimate R0 at 1·06 (95% CI: 1·05-1·28) for P1 and 1·83 (1·58-2·33) for P2. On March 22nd, Re for P1 and P2 are estimated at 1·13 (1·07-1·17) and 1·38 (1·25-1·63) respectively. After the curfew had taken effect, Re for P1 dropped modestly to 1·04 (1·02-1·06) but almost doubled for P2 to 2·47 (1·98-3·45). Our simulated epidemic trajectories show that the partial curfew measure modestly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission from P2 to P1 elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2.    Conclusion: Our results demonstrate that a lockdown can reduce SARS-CoV2 transmission in one subpopulation but accelerate it in another. At the population level, the consequences of lockdowns may vary across the socioeconomic spectrum. Any public health intervention needs to be sensitive to disparities within populations.

scholarly journals Digital Proximity Tracing in the COVID-19 Pandemic on Empirical Contact Networks

2020 ◽  
Author(s):  
Giulia Cencetti ◽  
Gabriele Santin ◽  
Antonio Longa ◽  
Emanuele Pigani ◽  
Alain Barrat ◽  
...  
Keyword(s):  
Disease Outbreaks ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Modeling Framework ◽  
Effective Measure ◽  
Epidemic Dynamics ◽  
Contact Patterns ◽  
Contact Data ◽  
High Level ◽  
The Impact

Abstract Digital contact tracing is increasingly considered as a tool to control infectious disease outbreaks. As part of a broader test, trace, isolate, and quarantine strategy, digital contract tracing apps have been proposed to alleviate lock-downs, and to return societies to a more normal situation in the ongoing COVID-19 crisis. Early work evaluating digital contact tracing did not consider important features and heterogeneities present in real-world contact patterns which impact epidemic dynamics. Here, we fill this gap by considering a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread of COVID-19 in realistic scenarios such as a university campus, a workplace, or a high school. We find that restrictive policies are more effective in confining the epidemics but come at the cost of quarantining a large part of the population. It is possible to avoid this effect by considering less strict policies, which only consider contacts with longer exposure and at shorter distance to be at risk. Our results also show that isolation and tracing can help keep re-emerging outbreaks under control provided that hygiene and social distancing measures limit the reproductive number to 1.5. Moreover, we confirm that a high level of app adoption is crucial to make digital contact tracing an effective measure. Our results may inform app-based contact tracing efforts currently being implemented across several countries worldwide.

scholarly journals Impact of public health interventions on the COVID-19 epidemic: a stochastic model based on data from an African island

2020 ◽  
Author(s):  
D. C. Nuckchady
Keyword(s):  
Stochastic Model ◽  
Population Surveillance ◽  
Health Interventions ◽  
Contact Tracing ◽  
Point Of Entry ◽  
Highly Sensitive ◽  
Travel Restrictions ◽  
Community Transmission ◽  
The Impact ◽  
Key Interventions

AbstractA stochastic model was created to simulate the impact of various healthcare measures on the COVID-19 epidemic. Travel restrictions and point of entry or exit screening help to delay the onset of the outbreak by a few weeks. Population surveillance is critical to detect the start of community transmission early and to avoid a surge in cases. Contact reduction and contact tracing are key interventions that can help to control the outbreak. To promptly curb the number of new cases, countries should diagnose patients using a highly sensitive test.

scholarly journals On the relationship between serial interval, infectiousness profile and generation time

2021 ◽  
Vol 18 (174) ◽  
pp. 20200756
Author(s):  
Sonja Lehtinen ◽  
Peter Ashcroft ◽  
Sebastian Bonhoeffer
Keyword(s):  
Symptom Onset ◽  
Generation Time ◽  
Time Distribution ◽  
Contact Tracing ◽  
Time Interval ◽  
Single Individual ◽  
Generation Times ◽  
Serial Interval ◽  
The Impact ◽  
The Relationship

The timing of transmission plays a key role in the dynamics and controllability of an epidemic. However, observing generation times—the time interval between the infection of an infector and an infectee in a transmission pair—requires data on infection times, which are generally unknown. The timing of symptom onset is more easily observed; generation times are therefore often estimated based on serial intervals—the time interval between symptom onset of an infector and an infectee. This estimation follows one of two approaches: (i) approximating the generation time distribution by the serial interval distribution or (ii) deriving the generation time distribution from the serial interval and incubation period—the time interval between infection and symptom onset in a single individual—distributions. These two approaches make different—and not always explicitly stated—assumptions about the relationship between infectiousness and symptoms, resulting in different generation time distributions with the same mean but unequal variances. Here, we clarify the assumptions that each approach makes and show that neither set of assumptions is plausible for most pathogens. However, the variances of the generation time distribution derived under each assumption can reasonably be considered as upper (approximation with serial interval) and lower (derivation from serial interval) bounds. Thus, we suggest a pragmatic solution is to use both approaches and treat these as edge cases in downstream analysis. We discuss the impact of the variance of the generation time distribution on the controllability of an epidemic through strategies based on contact tracing, and we show that underestimating this variance is likely to overestimate controllability.

scholarly journals A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200376 ◽  
Author(s):  
Richard O. J. H. Stutt ◽  
Renata Retkute ◽  
Michael Bradley ◽  
Christopher A. Gilligan ◽  
John Colvin
Keyword(s):  
Mobile Apps ◽  
Population Level ◽  
Disease Spread ◽  
Contact Tracing ◽  
Lower Efficiency ◽  
The Public ◽  
Molecular Tests ◽  
Modelling Framework ◽  
Increased Risk ◽  
The Impact

COVID-19 is characterized by an infectious pre-symptomatic period, when newly infected individuals can unwittingly infect others. We are interested in what benefits facemasks could offer as a non-pharmaceutical intervention, especially in the settings where high-technology interventions, such as contact tracing using mobile apps or rapid case detection via molecular tests, are not sustainable. Here, we report the results of two mathematical models and show that facemask use by the public could make a major contribution to reducing the impact of the COVID-19 pandemic. Our intention is to provide a simple modelling framework to examine the dynamics of COVID-19 epidemics when facemasks are worn by the public, with or without imposed ‘lock-down’ periods. Our results are illustrated for a number of plausible values for parameter ranges describing epidemiological processes and mechanistic properties of facemasks, in the absence of current measurements for these values. We show that, when facemasks are used by the public all the time (not just from when symptoms first appear), the effective reproduction number, R e , can be decreased below 1, leading to the mitigation of epidemic spread. Under certain conditions, when lock-down periods are implemented in combination with 100% facemask use, there is vastly less disease spread, secondary and tertiary waves are flattened and the epidemic is brought under control. The effect occurs even when it is assumed that facemasks are only 50% effective at capturing exhaled virus inoculum with an equal or lower efficiency on inhalation. Facemask use by the public has been suggested to be ineffective because wearers may touch their faces more often, thus increasing the probability of contracting COVID-19. For completeness, our models show that facemask adoption provides population-level benefits, even in circumstances where wearers are placed at increased risk. At the time of writing, facemask use by the public has not been recommended in many countries, but a recommendation for wearing face-coverings has just been announced for Scotland. Even if facemask use began after the start of the first lock-down period, our results show that benefits could still accrue by reducing the risk of the occurrence of further COVID-19 waves. We examine the effects of different rates of facemask adoption without lock-down periods and show that, even at lower levels of adoption, benefits accrue to the facemask wearers. These analyses may explain why some countries, where adoption of facemask use by the public is around 100%, have experienced significantly lower rates of COVID-19 spread and associated deaths. We conclude that facemask use by the public, when used in combination with physical distancing or periods of lock-down, may provide an acceptable way of managing the COVID-19 pandemic and re-opening economic activity. These results are relevant to the developed as well as the developing world, where large numbers of people are resource poor, but fabrication of home-made, effective facemasks is possible. A key message from our analyses to aid the widespread adoption of facemasks would be: ‘my mask protects you, your mask protects me’.

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