scholarly journals Using contact data to model the impact of contact tracing and physical distancing to control the SARS-CoV-2 outbreak in Kenya

2020 ◽  
Vol 5 ◽  
pp. 212
Author(s):  
Moritz Wagner ◽  
Ivy K. Kombe ◽  
Moses Chapa Kiti ◽  
Rabia Aziza ◽  
Edwine Barasa ◽  
...  
Keyword(s):  
Process Model ◽  
Contact Tracing ◽  
Short Delay ◽  
Household Contacts ◽  
Age Related ◽  
Containment Measures ◽  
Contact Data ◽  
General Physical ◽  
The Impact ◽  
Pharmaceutical Interventions

Background: Across the African continent, other than South Africa, COVID-19 cases have remained relatively low. Nevertheless, in Kenya, despite early implementation of containment measures and restrictions, cases have consistently been increasing. Contact tracing forms one of the key strategies in Kenya, but may become infeasible as the caseload grows. Here we explore different contact tracing strategies by distinguishing between household and non-household contacts and how these may be combined with other non-pharmaceutical interventions. Methods: We extend a previously developed branching process model for contact tracing to include realistic contact data from Kenya. Using the contact data, we generate a synthetic population of individuals and their contacts categorised by age and household membership. We simulate the initial spread of SARS-CoV-2 through this population and look at the effectiveness of a number of non-pharmaceutical interventions with a particular focus on different contact tracing strategies and the potential effort involved in these. Results: General physical distancing and avoiding large group gatherings combined with contact tracing, where all contacts are isolated immediately, can be effective in slowing down the outbreak, but were, under our base assumptions, not enough to control it without implementing extreme stay at home policies. Under optimistic assumptions with a highly overdispersed R0 and a short delay from symptom onset to isolation, control was possible with less stringent physical distancing and by isolating household contacts only. Conclusions: Without strong physical distancing measures, controlling the spread of SARS-CoV-2 is difficult. With limited resources, physical distancing combined with the isolation of households of detected cases can form a moderately effective strategy, and control is possible under optimistic assumptions. More data are needed to understand transmission in Kenya, in particular by studying the settings that lead to larger transmission events, which may allow for more targeted responses, and collection of representative age-related contact data.

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 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 Initial Assessment of the Impact of the Emergency State Lockdown Measures on the 1st Wave of the COVID-19 Epidemic in Portugal

2020 ◽  
Vol 33 (11) ◽  
pp. 733
Author(s):  
Vasco Ricoca Peixoto ◽  
André Vieira ◽  
Pedro Aguiar ◽  
Carlos Carvalho ◽  
Daniel Rhys Thomas ◽  
...  
Keyword(s):  
Intensive Care ◽  
Arima Model ◽  
Control Measures ◽  
Contact Tracing ◽  
Initial Assessment ◽  
Early Action ◽  
Containment Measures ◽  
Prevention And Control Measures ◽  
Care Capacity ◽  
The Impact

Introduction: Portugal took early action to control the COVID-19 epidemic, initiating lockdown measures on March 16th when it recorded only 62 cases of COVID-19 per million inhabitants and reported no deaths. The Portuguese public complied quickly, reducing their overall mobility by 80%. The aim of this study was to estimate the initial impact of the lockdown in Portugal in terms of the reduction of the burden on the healthcare system.Material and Methods: We forecasted epidemic curves for: Cases, hospital inpatients (overall and in intensive care), and deaths without lockdown, assuming that the impact of containment measures would start 14 days after initial lockdown was implemented. We used exponential smoothing models for deaths, intensive care and hospitalizations and an ARIMA model for number of cases. Models were selected considering fitness to the observed data up to the 31st March 2020. We then compared observed (with intervention) and forecasted curves (without intervention).Results: Between April 1st and April 15th, there were 146 fewer deaths (-25%), 5568 fewer cases (-23%) and, as of April 15th, there were 519 fewer intensive care inpatients (-69%) than forecasted without the lockdown. On April 15th, the number of intensive care inpatients could have reached 748, three times higher than the observed value (229) if the intervention had been delayed.Discussion: If the lockdown had not been implemented in mid-March, Portugal intensive care capacity (528 beds) would have likely been breached during the first half of April. The lockdown seems to have been effective in reducing transmission of SARS-CoV-2, serious COVID-19 disease, and associated mortality, thus decreasing demand on health services.Conclusion: An early lockdown allowed time for the National Health Service to mobilize resources and acquire personal protective equipment, increase testing, contact tracing and hospital and intensive care capacity and to promote broad prevention and control measures. When lifting more stringent measures, strong surveillance and communication strategies that mobilize individual prevention efforts are necessary.

scholarly journals An imperfect tool: COVID-19 ‘test & trace’ success relies on minimising the impact of false negatives and continuation of physical distancing

2020 ◽  
Author(s):  
Emma L. Davis ◽  
Tim C. D. Lucas ◽  
Anna Borlase ◽  
Timothy M Pollington ◽  
Sam Abbot ◽  
...  
Keyword(s):  
Process Model ◽  
Diagnostic Testing ◽  
False Negative ◽  
Contact Tracing ◽  
Parameter Estimates ◽  
Sensitivity Testing ◽  
Test Sensitivity ◽  
Negative Results ◽  
The Impact

AbstractBackgroundFollowing a consistent decline in COVID-19-related deaths in the UK throughout May 2020, it is recognised that contact tracing will be vital to relaxing physical distancing measures. The increasingly evident role of asymptomatic and pre-symptomatic transmission means testing is central to control, but test sensitivity estimates are as low as 65%.MethodsWe extend an existing UK-focused branching process model for contact tracing, adding diagnostic testing and refining parameter estimates to demonstrate the impact of poor test sensitivity and suggest mitigation methods. We also investigate the role of super-spreading events, providing estimates of the relationship between infections, cases detected and hospitalisations, and consider how tracing coverage and speed affects outbreak risk.FindingsIncorporating poor sensitivity testing into tracing protocols could reduce efficacy, due to false negative results impacting isolation duration. However, a 7-day isolation period for all negative-testing individuals could mitigate this effect. Similarly, reducing delays to testing following exposure has a negligible impact on the risk of future outbreaks, but could undermine control if negative-testing individuals immediately cease isolating. Even 100% tracing of contacts will miss cases, which could prompt large localised outbreaks if physical distancing measures are relaxed prematurely.InterpretationIt is imperative that test results are interpreted with caution due to high false-negative rates and that contact tracing is used in combination with physical distancing measures. If the risks associated with imperfect test sensitivity are mitigated, we find that contact tracing can facilitate control when the reproduction number with physical distancing, RS, is less than 1·5.

scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang Liu ◽  
◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity. Conclusion Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

scholarly journals Isolation and Contact Tracing Can Tip the Scale to Containment of COVID-19 in Populations With Social Distancing

2021 ◽  
Vol 8 ◽  
Author(s):  
Mirjam E. Kretzschmar ◽  
Ganna Rozhnova ◽  
Michiel van Boven
Keyword(s):  
Growth Rates ◽  
Process Model ◽  
Reproduction Number ◽  
Health Care Systems ◽  
Contact Tracing ◽  
Explicit Calculation ◽  
Social Distancing ◽  
Household Contacts ◽  
Care Systems ◽  
Doubling Times

SARS-CoV-2 has established itself in all parts of the world, and many countries have implemented social distancing as a measure to prevent overburdening of health care systems. Here we evaluate whether and under which conditions containment of SARS-CoV-2 is possible by isolation and contact tracing in settings with various levels of social distancing. To this end we use a branching process model in which every person generates novel infections according to a probability distribution that is affected by the incubation period distribution, distribution of the latent period, and infectivity. The model distinguishes between household and non-household contacts. Social distancing may affect the numbers of the two types of contacts differently, for example while work and school contacts are reduced, household contacts may remain unchanged. The model allows for an explicit calculation of the basic and effective reproduction numbers, and of exponential growth rates and doubling times. Our findings indicate that if the proportion of asymptomatic infections in the model is larger than 30%, contact tracing and isolation cannot achieve containment for a basic reproduction number (ℛ0) of 2.5. Achieving containment by social distancing requires a reduction of numbers of non-household contacts by around 90%. If containment is not possible, at least a reduction of epidemic growth rate and an increase in doubling time may be possible. We show for various parameter combinations how growth rates can be reduced and doubling times increased by contact tracing. 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. In a situation with social distancing, contact tracing can act synergistically to tip the scale toward containment. These measures can therefore be a tool for controlling COVID-19 epidemics as part of an exit strategy from lock-down measures or for preventing secondary waves of COVID-19.

scholarly journals Discontinuous epidemic transition due to limited testing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Davide Scarselli ◽  
Nazmi Burak Budanur ◽  
Marc Timme ◽  
Björn Hof
Keyword(s):  
Exponential Growth ◽  
Growth Period ◽  
High Impact ◽  
Contact Tracing ◽  
Epidemic Dynamics ◽  
Slowing Down ◽  
Containment Measures ◽  
Second Wave ◽  
Limited Testing ◽  
Pharmaceutical Interventions

AbstractHigh impact epidemics constitute one of the largest threats humanity is facing in the 21st century. In the absence of pharmaceutical interventions, physical distancing together with testing, contact tracing and quarantining are crucial in slowing down epidemic dynamics. Yet, here we show that if testing capacities are limited, containment may fail dramatically because such combined countermeasures drastically change the rules of the epidemic transition: Instead of continuous, the response to countermeasures becomes discontinuous. Rather than following the conventional exponential growth, the outbreak that is initially strongly suppressed eventually accelerates and scales faster than exponential during an explosive growth period. As a consequence, containment measures either suffice to stop the outbreak at low total case numbers or fail catastrophically if marginally too weak, thus implying large uncertainties in reliably estimating overall epidemic dynamics, both during initial phases and during second wave scenarios.

scholarly journals Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study

2021 ◽  
Author(s):  
Francesca A. Lovell-Read ◽  
Silvia Shen ◽  
Robin N. Thompson
Keyword(s):  
Process Model ◽  
Host Population ◽  
Structured Populations ◽  
School Closures ◽  
Related Factors ◽  
Social Distancing ◽  
Modelling Framework ◽  
Age Related ◽  
Pharmaceutical Interventions

AbstractDuring the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) including school closures, workplace closures and social distancing policies have been employed worldwide to reduce transmission and prevent local outbreaks. However, transmission and the effectiveness of NPIs depend strongly on age-related factors including heterogeneities in contact patterns and pathophysiology. Here, using SARS-CoV-2 as a case study, we develop a branching process model for assessing the risk that an infectious case arriving in a new location will initiate a local outbreak, accounting for the age-stratification of the host population. We show that the risk of a local outbreak depends on the age of the index case, and we explore the effects of NPIs targeting individuals of different ages. Social distancing policies that reduce contacts outside of schools and workplaces and target individuals of all ages are predicted to reduce local outbreak risks substantially, whereas school closures have a more limited impact. When different NPIs are used in combination, the risk of local outbreaks can be eliminated. We also show that heightened surveillance of infectious individuals reduces the level of NPIs required to prevent local outbreaks, particularly if enhanced surveillance of symptomatic cases is combined with efforts to find and isolate nonsymptomatic infected individuals. Our results reflect real-world experience of the COVID-19 pandemic, during which combinations of intense NPIs have reduced transmission and the risk of local outbreaks. The general modelling framework that we present can be used to estimate local outbreak risks during future epidemics of a range of pathogens, accounting fully for age-related factors.

scholarly journals Aging with multiple sclerosis: A longitudinal study of physical function, mental health, and memory in two cohorts of US women

2021 ◽  
pp. 135245852110077
Author(s):  
Marianna Cortese ◽  
Kjetil Bjornevik ◽  
Tanuja Chitnis ◽  
Alberto Ascherio ◽  
Kassandra L Munger
Keyword(s):  
Mental Health ◽  
Multiple Sclerosis ◽  
Physical Function ◽  
Short Form ◽  
Health Study ◽  
Age Related ◽  
Aging Women ◽  
Physical Function Score ◽  
General Physical ◽  
The Impact

Background: It is unknown how individuals with multiple sclerosis (MS) age compared to unaffected peers. Objectives: The objective of the study is to describe the impact of MS on health and functioning in aging women. Methods: We used 10-item Physical Functioning Scale (PF10) scores (from the Short Form-36 (SF-36)) and other indicators of general, physical, mental health, and memory collected repeatedly over 25 years with self-administered questionnaires among participants in the Nurses’ Health Study ( n = 121,700 recruited at ages 30–55) and Nurses’ Health Study II ( n = 116,429 recruited at ages 25–42) to compare women with MS ( n = 733) to unaffected peers in their health and disability, and describe/quantify the burden of aging with MS. Results: Women with MS had a consistently lower PF10 by 0.9–1.7 standard deviations with greater overall variability than unaffected women. PF10-scores gradually decreased with increasing age in both groups, but MS cases declined 3–4 times faster in midlife, while decline was similar in old age. The physical function score of 45-year-old women with MS was comparable to that of 75-year-old unaffected women; 70-year-old women with MS scored similarly to 85-year-old unaffected women. MS cases also reported worse health/more disability throughout adulthood on the other indicators. Conclusion: The age-related decline in physical health is accelerated by 15–30 years in MS patients compared to unaffected peers.

scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

2020 ◽  
Author(s):  
Yang Liu ◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
Mark Jit ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.

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