Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study

Background In countries with declining numbers of confirmed cases of COVID-19, lockdown measures are gradually being lifted. However, even if most physical distancing measures are continued, other public health measures will be needed to control the epidemic. Contact tracing via conventional methods or mobile app technology is central to control strategies during de-escalation of physical distancing. We aimed to identify key factors for a contact tracing strategy to be successful. Methods We evaluated the impact of timeliness and completeness in various steps of a contact tracing strategy using a stochastic mathematical model with explicit time delays between time of infection and symptom onset, and between symptom onset, diagnosis by testing, and isolation (testing delay). The model also includes tracing of close contacts (eg, household members) and casual contacts, followed by testing regardless of symptoms and isolation if testing positive, with different tracing delays and coverages. We computed effective reproduction numbers of a contact tracing strategy (RCTS) for a population with physical distancing measures and various scenarios for isolation of index cases and tracing and quarantine of their contacts. Findings For the most optimistic scenario (testing and tracing delays of 0 days and tracing coverage of 100%), and assuming that around 40% of transmissions occur before symptom onset, the model predicts that the estimated effective reproduction number of 1·2 (with physical distancing only) will be reduced to 0·8 (95% CI 0·7–0·9) by adding contact tracing. The model also shows that a similar reduction can be achieved when testing and tracing coverage is reduced to 80% (RCTS 0·8, 95% CI 0·7–1·0). A testing delay of more than 1 day requires the tracing delay to be at most 1 day or tracing coverage to be at least 80% to keep RCTS below 1. With a testing delay of 3 days or longer, even the most efficient strategy cannot reach RCTS values below 1. The effect of minimising tracing delay (eg, with app-based technology) declines with decreasing coverage of app use, but app-based tracing alone remains more effective than conventional tracing alone even with 20% coverage, reducing the reproduction number by 17·6% compared with 2·5%. The proportion of onward transmissions per index case that can be prevented depends on testing and tracing delays, and given a 0-day tracing delay, ranges from up to 79·9% with a 0-day testing delay to 41·8% with a 3-day testing delay and 4·9% with a 7-day testing delay. Interpretation In our model, minimising testing delay had the largest impact on reducing onward transmissions. Optimising testing and tracing coverage and minimising tracing delays, for instance with app-based technology, further enhanced contact tracing effectiveness, with the potential to prevent up to 80% of all transmissions. Access to testing should therefore be optimised, and mobile app technology might reduce delays in the contact tracing process and optimise contact tracing coverage. Funding ZonMw, Fundação para a Ciência e a Tecnologia, and EU Horizon 2020 RECOVER

Modeling human mobility responses to the large-scale spreading of infectious diseases

Current modeling of infectious diseases allows for the study of realistic scenarios that include population heterogeneity, social structures, and mobility processes down to the individual level. The advances in the realism of epidemic description call for the explicit modeling of individual behavioral responses to the presence of disease within modeling frameworks. Here we formulate and analyze a metapopulation model that incorporates several scenarios of self-initiated behavioral changes into the mobility patterns of individuals. We find that prevalence-based travel limitations do not alter the epidemic invasion threshold. Strikingly, we observe in both synthetic and data-driven numerical simulations that when travelers decide to avoid locations with high levels of prevalence, this self-initiated behavioral change may enhance disease spreading. Our results point out that the real-time availability of information on the disease and the ensuing behavioral changes in the population may produce a negative impact on disease containment and mitigation

Modelling the Costs and Effects of Selective and Universal Hospital Admission Screening for Methicillin-Resistant Staphylococcus aureus

Background: Screening at hospital admission for carriage of methicillin-resistant Staphylococcus aureus (MRSA) has been proposed as a strategy to reduce nosocomial infections. The objective of this study was to determine the long-term costs and health benefits of selective and universal screening for MRSA at hospital admission, using both PCR-based and chromogenic media-based tests in various settings. Methodology/Principal Findings: A simulation model of MRSA transmission was used to determine costs and effects over 15 years from a US healthcare perspective. We compared admission screening together with isolation of identified carriers against a baseline policy without screening or isolation. Strategies included selective screening of high risk patients or universal admission screening, with PCR-based or chromogenic media-based tests, in medium (5%) or high nosocomial prevalence (15%) settings. The costs of screening and isolation per averted MRSA infection were lowest using selective chromogenic-based screening in high and medium prevalence settings, at $4,100 and$10,300, respectively. Replacing the chromogenic-based test with a PCR-based test costs $13,000 and$36,200 per additional infection averted, and subsequent extension to universal screening with PCR would cost $131,000 and$232,700 per additional infection averted, in high and medium prevalence settings respectively. Assuming $17,645 benefit per infection averted, the most cost-saving strategies in high and medium prevalence settings were selective screening with PCR and selective screening with chromogenic, respectively. Conclusions/ Significance: Admission screening costs$4,100-$21,200 per infection averted, depending on strategy and setting. Including financial benefits from averted infections, screening could well be cost saving

Effective, Robust Design of Community Mitigation for Pandemic Influenza: A Systematic Examination of Proposed US Guidance

BACKGROUND: The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? METHODS AND FINDINGS: We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. CONCLUSIONS: Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic

Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)

Here we present a review of the literature of influenza modeling studies, and discuss how these models can provide insights into the future of the currently circulating novel strain of influenza A (H1N1), formerly known as swine flu. We discuss how the feasibility of controlling an epidemic critically depends on the value of the Basic Reproduction Number (R0). The R0 for novel influenza A (H1N1) has recently been estimated to be between 1.4 and 1.6. This value is below values of R0 estimated for the 1918–1919 pandemic strain (mean R0~2: range 1.4 to 2.8) and is comparable to R0 values estimated for seasonal strains of influenza (mean R0 1.3: range 0.9 to 2.1). By reviewing results from previous modeling studies we conclude it is theoretically possible that a pandemic of H1N1 could be contained. However it may not be feasible, even in resource-rich countries, to achieve the necessary levels of vaccination and treatment for control. As a recent modeling study has shown, a global cooperative strategy will be essential in order to control a pandemic. This strategy will require resource-rich countries to share their vaccines and antivirals with resource-constrained and resource-poor countries. We conclude our review by discussing the necessity of developing new biologically complex models. We suggest that these models should simultaneously track the transmission dynamics of multiple strains of influenza in bird, pig and human populations. Such models could be critical for identifying effective new interventions, and informing pandemic preparedness planning. Finally, we show that by modeling cross-species transmission it may be possible to predict the emergence of pandemic strains of influenza

Quantifying Type-Specific Reproduction Numbers for Nosocomial Pathogens: Evidence for Heightened Transmission of an Asian Sequence Type 239 MRSA Clone

An important determinant of a pathogen's success is the rate at which it is transmitted from infected to susceptible hosts. Although there are anecdotal reports that methicillin-resistant Staphylococcus aureus (MRSA) clones vary in their transmissibility in hospital settings, attempts to quantify such variation are lacking for common subtypes, as are methods for addressing this question using routinely-collected MRSA screening data in endemic settings. Here we present a method to quantify the time-varying transmissibility of different subtypes of common bacterial nosocomial pathogens using routine surveillance data. The method adapts approaches for estimating reproduction numbers based on the probabilistic reconstruction of epidemic trees, but uses relative hazards rather than serial intervals to assign probabilities to different sources for observed transmission events. The method is applied to data collected as part of a retrospective observational study of a concurrent MRSA outbreak in the United Kingdom with dominant endemic MRSA clones (ST22 and ST36) and an Asian ST239 MRSA strain (ST239-TW) in two linked adult intensive care units, and compared with an approach based on a fully parametric transmission model. The results provide support for the hypothesis that the clones responded differently to an infection control measure based on the use of topical antiseptics, which was more effective at reducing transmission of endemic clones. They also suggest that in one of the two ICUs patients colonized or infected with the ST239-TW MRSA clone had consistently higher risks of transmitting MRSA to patients free of MRSA. These findings represent some of the first quantitative evidence of enhanced transmissibility of a pandemic MRSA lineage, and highlight the potential value of tailoring hospital infection control measures to specific pathogen subtypes

Transmission Dynamics of Methicillin-Resistant Staphylococcus aureus in a Medical Intensive Care Unit in India

Background: Methicillin-resistant Staphylococcus aureus (MRSA) is a global pathogen and an important but seldom investigated cause of morbidity and mortality in lower and middle-income countries where it can place a major burden on limited resources. Quantifying nosocomial transmission in resource-poor settings is difficult because molecular typing methods are prohibitively expensive. Mechanistic statistical models can overcome this problem with minimal cost. We analyse the transmission dynamics of MRSA in a hospital in south India using one such approach and provide conservative estimates of the organism's economic burden. Methods and Findings: Fifty months of MRSA infection data were collected retrospectively from a Medical Intensive Care Unit (MICU) in a tertiary hospital in Vellore, south India. Data were analysed using a previously described structured hidden Markov model. Seventy-two patients developed MRSA infections and, of these, 49 (68%) died in the MICU. We estimated that 4.2% (95%CI 1.0, 19.0) of patients were MRSA-positive when admitted, that there were 0.39 MRSA infections per colonized patient month (0.06, 0.73), and that the ward-level reproduction number for MRSA was 0.42 (0.08, 2.04). Anti-MRSA antibiotic treatment costs alone averaged $124/patient, over three times the monthly income of more than 40% of the Indian population. Conclusions: Our analysis of routine data provides the first estimate of the nosocomial transmission potential of MRSA in India. The high levels of transmission estimated underline the need for cost-effective interventions to reduce MRSA transmission in hospital settings in low and middle income countries. © 2011 Christopher et al

Quantitative gait analysis under dual-task in older people with mild cognitive impairment: a reliability study

<p>Abstract</p> <p>Background</p> <p>Reliability of quantitative gait assessment while dual-tasking (walking while doing a secondary task such as talking) in people with cognitive impairment is unknown. Dual-tasking gait assessment is becoming highly important for mobility research with older adults since better reflects their performance in the basic activities of daily living. Our purpose was to establish the test-retest reliability of assessing quantitative gait variables using an electronic walkway in older adults with mild cognitive impairment (MCI) under single and dual-task conditions.</p> <p>Methods</p> <p>The gait performance of 11 elderly individuals with MCI was evaluated using an electronic walkway (GAITRite^®System) in two sessions, one week apart. Six gait parameters (gait velocity, step length, stride length, step time, stride time, and double support time) were assessed under two conditions: single-task (sG: usual walking) and dual-task (dG: counting backwards from 100 while walking). Test-retest reliability was determined using intra-class correlation coefficient (ICC). Gait variability was measured using coefficient of variation (CoV).</p> <p>Results</p> <p>Eleven participants (average age = 76.6 years, SD = 7.3) were assessed. They were high functioning (Clinical Dementia Rating Score = 0.5) with a mean Mini-Mental Status Exam (MMSE) score of 28 (SD = 1.56), and a mean Montreal Cognitive Assessment (MoCA) score of 22.8 (SD = 1.23). Under dual-task conditions, mean gait velocity (GV) decreased significantly (sGV = 119.11 ± 20.20 cm/s; dGV = 110.88 ± 19.76 cm/s; p = 0.005). Additionally, under dual-task conditions, higher gait variability was found on stride time, step time, and double support time. Test-retest reliability was high (ICC>0.85) for the six parameters evaluated under both conditions.</p> <p>Conclusion</p> <p>In older people with MCI, variability of time-related gait parameters increased with dual-tasking suggesting cognitive control of gait performance. Assessment of quantitative gait variables using an electronic walkway is highly reliable under single and dual-task conditions. The presence of cognitive impairment did not preclude performance of dual-tasking in our sample supporting that this methodology can be reliably used in cognitive impaired older individuals.</p

Membrane anchoring stabilizes and favors secretion of New Delhi metallo-β-lactamase

Carbapenems, 'last-resort' β-lactam antibiotics, are inactivated by zinc-dependent metallo-β-lactamases (MBLs). The host innate immune response withholds nutrient metal ions from microbial pathogens by releasing metal-chelating proteins such as calprotectin. We show that metal sequestration is detrimental for the accumulation of MBLs in the bacterial periplasm, because those enzymes are readily degraded in their nonmetallated form. However, the New Delhi metallo-β-lactamase (NDM-1) can persist under conditions of metal depletion. NDM-1 is a lipidated protein that anchors to the outer membrane of Gram-negative bacteria. Membrane anchoring contributes to the unusual stability of NDM-1 and favors secretion of this enzyme in outer-membrane vesicles (OMVs). OMVs containing NDM-1 can protect nearby populations of bacteria from otherwise lethal antibiotic levels, and OMVs from clinical pathogens expressing NDM-1 can carry this MBL and the bla[subscript NDM] gene. We show that protein export into OMVs can be targeted, providing possibilities of new antibacterial therapeutic strategies.Kinship Foundation. Searle Scholars ProgramMassachusetts Institute of Technology. Department of Chemistr

Predictive factors of urinary tract infections among the oldest old in the general population. a population-based prospective follow-up study

<p>Abstract</p> <p>Background</p> <p>Urinary tract infections (UTI) are common among the oldest old and may lead to a few days of illness, delirium or even to death. We studied the incidence and predictive factors of UTI among the oldest old in the general population.</p> <p>Methods</p> <p>The Leiden 85-plus Study is a population-based prospective follow-up study of 86-year-old subjects in Leiden, The Netherlands. Information on the diagnosis of UTI was obtained annually during four years of follow-up from the medical records and interviews of treating physicians. A total of 157 men and 322 women aged 86 years participated in the study. Possible predictive factors were collected at baseline, including history of UTI between the age of 85 and 86 years, aspects of functioning (cognitive impairment (Mini-Mental State Examination (MMSE) < 19), presence of depressive symptoms (Geriatric Depression Scale (GDS) > 4), disability in activities of daily living (ADL)), and co-morbidities.</p> <p>Results</p> <p>The incidence of UTI from age 86 through 90 years was 11.2 (95% confidence interval (CI) 9.4, 13.1) per 100 person-years at risk. Multivariate analysis showed that history of UTI between the age of 85 and 86 years (hazard ratio (HR) 3.4 (95% CI 2.4, 5.0)), impaired cognitive function (HR 1.9 (95% CI 1.3, 2.9)), disability in daily living (HR 1.7 (95% CI 1.1, 2.5)) and urine incontinence (HR 1.5 (95% CI 1.0, 2.1)) were independent predictors of an increased incidence of UTI from age 86 onwards.</p> <p>Conclusions</p> <p>Within the oldest old, a history of UTI between the age of 85 and 86 years, cognitive impairment, ADL disability and urine incontinence are independent predictors of developing UTI. These predictive factors could be used to target preventive measures to the oldest old at high risk of UTI.</p