scholarly journals A model of COVID-19 propagation based on a gamma subordinated negative binomial branching process

2020 ◽  
Author(s):  
Jérôme Levesque ◽  
David W. Maybury ◽  
R. H. A. David Shaw
Keyword(s):  
Branching Process ◽  
Negative Binomial ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Bayesian Hierarchical ◽  
Disease Propagation ◽  
Work Spaces ◽  
Trade Offs ◽  
Case Count ◽  
Office Environments

AbstractWe build a parsimonious Crump-Mode-Jagers continuous time branching process of COVID-19 propagation based on a negative binomial process subordinated by a gamma subordinator. By focusing on the stochastic nature of the process in small populations, our model provides decision making insight into mitigation strategies as an outbreak begins. Our model accommodates contact tracing and isolation, allowing for comparisons between different types of intervention. We emphasize a physical interpretation of the disease propagation throughout which affords analytical results for comparison to simulations. Our model provides a basis for decision makers to understand the likely trade-offs and consequences between alternative outbreak mitigation strategies particularly in office environments and confined work-spaces. Combining the asymptotic limit of our model with Bayesian hierarchical techniques, we provide US county level inferences for the reproduction number from cumulative case count data over July and August of this year.

scholarly journals Engagement and adherence trade-offs for SARS-CoV-2 contact tracing

2020 ◽  
Author(s):  
Tim C D Lucas ◽  
Emma L Davis ◽  
Diepreye Ayabina ◽  
Anna Borlase ◽  
Thomas Crellen ◽  
...  
Keyword(s):  
Process Model ◽  
Branching Process ◽  
Reporting Rate ◽  
Self Report ◽  
Contact Tracing ◽  
Legal Enforcement ◽  
Trade Offs ◽  
Large Outbreak ◽  
The Cost ◽  
Reporting Rates

Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritised. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies that increase the verage duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided.

scholarly journals Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Setting-specific Transmission Rates: A Systematic Review and Meta-analysis

2021 ◽  
Author(s):  
Hayley A Thompson ◽  
Andria Mousa ◽  
Amy Dighe ◽  
Han Fu ◽  
Alberto Arnedo-Pena ◽  
...  
Keyword(s):  
Systematic Review ◽  
Severe Acute Respiratory Syndrome ◽  
Negative Binomial ◽  
Meta Analysis ◽  
Contact Tracing ◽  
Binomial Model ◽  
Transmission Potential ◽  
Transmission Rates ◽  
Symptom Status ◽  
Index Cases

Abstract Background Understanding the drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is crucial for control policies, but evidence of transmission rates in different settings remains limited. Methods We conducted a systematic review to estimate secondary attack rates (SARs) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a beta-binomial model to pool SARs across studies and a negative-binomial model to estimate Robs. Results Households showed the highest transmission rates, with a pooled SAR of 21.1% (95% confidence interval [CI]:17.4–24.8). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs 1.2%). Estimates of SARs and Robs for asymptomatic index cases were approximately one-seventh, and for presymptomatic two-thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals younger than 20 years of age in the household context, which is more limited when examining all settings. Conclusions Our results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies, such as contact tracing, testing, and rapid isolation of cases. There were limited data to explore transmission patterns in workplaces, schools, and care homes, highlighting the need for further research in such settings.

Reanalysis of Historical Mourning Dove Nest Data by Using a Bayesian Approach

2016 ◽  
Vol 7 (2) ◽  
pp. 292-303 ◽  
Author(s):  
John Snyder ◽  
Xiaoming Gao ◽  
John H. Schulz ◽  
Joshua J. Millspaugh
Keyword(s):  
Hierarchical Modeling ◽  
Nest Survival ◽  
Original Study ◽  
Egg Laying ◽  
Mourning Dove ◽  
Zenaida Macroura ◽  
Bayesian Hierarchical ◽  
Trade Offs ◽  
Original Dataset ◽  
Nest Height

Abstract We reconstructed a historical mourning dove Zenaida macroura nesting dataset to estimate nest survival and investigate the effect of covariates by using a Bayesian hierarchical model. During 1979–1980, 106 study areas, across 27 states, were established to conduct weekly nest searches during February–October. We used roughly 11,000 data sheets to reconstruct the dataset containing 7,139 nests compared to 6,950 nests in the original study. Original and reconstructed nest survival estimates showed little difference by using the original analysis methodology, that is, the Mayfield method. Thus, we assumed we closely replicated the original dataset; distributions of nests found, birds hatched, and birds fledged also showed similar trends. After confirming the validity of the reconstructed dataset, we evaluated 10 different models by using a Bayesian hierarchical modeling approach; the final model contained variables for nest age or stage, nest height, region, but not habitat. The year 1980 had a higher probability of nest survival compared to 1979, and nest survival increased with nest height. The nest encounter probability increased at days 4 and 11 of the nesting cycle, providing some insight into the convenience sampling used in the original study. Our reanalysis with the use of covariates confirms previous hypotheses that mourning doves are habitat generalists, but it adds new information showing lower nest survival during nest initiation and egg laying and a decline when fledglings would be 4 or 5 d old. Regional differences in mourning dove nest survival confirm existing hypotheses about northern states demonstrating greater nest success compared to southern states where differences may reflect trade-offs associated with northern latitudes, weather differences, or food availability.

Sponsoring Early Day Motions in the British House of Commons as a Response to Electoral Vulnerability

2013 ◽  
Vol 1 (2) ◽  
pp. 263-280 ◽  
Author(s):  
Michael Kellermann
Keyword(s):  
Political Science ◽  
Negative Binomial ◽  
Hurdle Model ◽  
House Of Commons ◽  
Bayesian Hierarchical ◽  
The Past ◽  
Electoral Outcomes

While the importance of individual candidates in British elections has long been minimized, this article argues that early day motions (EDMs)—formal, non-binding expressions of opinion—allow backbench MPs to cultivate reputations with constituents. First, this article demonstrates that greater sponsorship of EDMs is associated with better electoral outcomes, which suggests that EDMs could help vulnerable MPs improve their electoral prospects. Secondly, a Bayesian hierarchical negative binomial hurdle model, which accounts for specific features of EDM sponsorship and is novel in political science, shows that members from electorally competitive constituencies are more likely to introduce EDMs, and introduce them more often, than members from less competitive constituencies. Moreover, this relationship has increased over the past 20 years.

scholarly journals Topological and Thermodynamic Entropy Measures for COVID-19 Pandemic through Graph Theory

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1992
Author(s):  
G. Kirithiga Nandini ◽  
R. Sundara Rajan ◽  
A. Arul Shantrinal ◽  
T. M. Rajalaxmi ◽  
Indra Rajasingh ◽  
...  
Keyword(s):  
Biological Evolution ◽  
Genetic Network ◽  
Topological Indices ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Topological Characterization ◽  
Christmas Trees ◽  
Global Pandemic ◽  
Mathematical Techniques ◽  
Underlying Mechanisms

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the global pandemic, coronavirus disease-2019 (COVID-19) which has resulted in 60.4 million infections and 1.42 million deaths worldwide. Mathematical models as an integral part of artificial intelligence are designed for contact tracing, genetic network analysis for uncovering the biological evolution of the virus, understanding the underlying mechanisms of the observed disease dynamics, evaluating mitigation strategies, and predicting the COVID-19 pandemic dynamics. This paper describes mathematical techniques to exploit and understand the progression of the pandemic through a topological characterization of underlying graphs. We have obtained several topological indices for various graphs of biological interest such as pandemic trees, Cayley trees, Christmas trees, and the corona product of Christmas trees and paths. We have also obtained an analytical expression for the thermodynamic entropies of pandemic trees as a function of R0, the reproduction number, and the level of spread, using the nested wreath product groups. Our plots of entropy and logarithms of topological indices of pandemic trees accentuate the underlying severity of COVID-19 over the 1918 Spanish flu pandemic.

scholarly journals Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks

2017 ◽  
Vol 7 (2) ◽  
pp. 82-101 ◽  
Author(s):  
Marianne Jahre
Keyword(s):  
Supply Chain ◽  
Case Studies ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Primary Data ◽  
Main Concern ◽  
Supply Chain Risk Management ◽  
Content Type ◽  
Trade Offs ◽  
Supply Chain Risks

Purpose The purpose of this paper is to link humanitarian logistics (HL) and supply chain risk management (SCRM) to provide an understanding of risk mitigation strategies that humanitarian organisations use, or could use, to improve their logistics preparedness. Design/methodology/approach Based on systematic reviews of RMS in SCRM and supply chain strategies (SCS) in HL literature, a framework is developed and used to review published case studies in HL. Findings The study finds that humanitarian actors use a number of the strategies proposed in the framework, particularly those related to strategic stocks, postponement, and collaboration. Strategies related to sourcing and procurement, however, especially those on supplier relationships, seem to be lacking in both research and practice. Research limitations/implications The study is based on secondary data and could be further developed through case studies based on primary data. Future studies should explore the generalisability of the findings. Practical implications Practitioners can use the framework to identify potential new SCS and how strategies can be combined. Findings can help them to understand the abnormal risks of main concern, how they may impact normal risks, and provide ideas on how to tackle trade-offs between different risks. Social implications The results can support improvements in humanitarian supply chains, which will provide affected people with rapid, cost-efficient, and better-adapted responses. Originality/value The paper connects SCRM and HL to develop a framework and suggests propositions on how humanitarian actors can mitigate supply chain risks. Questioning the focus on strategic stock it suggests complementary or alternative strategies for improving logistics preparedness.

scholarly journals Environmental co-benefits and trade-offs of climate mitigation strategies applied to net-zero-emission neighbourhoods

2021 ◽  
Author(s):  
Carine Lausselet ◽  
Helge Brattebø
Keyword(s):  
Mitigation Strategies ◽  
Environmental Benefits ◽  
Value Chains ◽  
Climate Mitigation ◽  
Mobility Patterns ◽  
Passenger Cars ◽  
Trade Offs ◽  
Net Zero ◽  
Zero Emission ◽  
The Impact

Abstract Main purpose To limit global warming at a safe level of 1.5 °C, deep emission reductions in all sectors combined with rapid, far-reaching, and unprecedented changes in all aspects of society are required. The ongoing climate urgency has led to greenhouse gas (GHG) emissions to be the most often inventoried life-cycle indicators. But, to draw comprehensive climate mitigation strategies (CMS), adverse potential environmental side-effects and trade-offs should be assessed as well. Methods LCA is used to assess the potential environmental co-benefits and trade-offs of a net-zero-emission neighbourhood (nZEN) in the early planning stages. CMS are designed to test for the effect of (1) mobility patterns less based on the use of passenger cars, (2) a better material use by decreasing the size of the dwellings and increasing the passenger loads, (3) increased lifetimes of buildings and passenger cars, and (4) their combination. Results Across the impact categories, environmental benefits of 5–20% are shown for single CMS and of 22–42% when combined. Interestingly, the highest environmental co-benefits are found for Metal Depletion, highlighting the close interconnection of CMS and decreased pressure on resource use. The use of several climate metrics has shed light on the use of fossil fuels in the production value chains of the materials used to provide the mobility services and shelters to the inhabitants of the nZEN under study. A combination of climate metrics with short- and long-time horizon should be used to give the importance that short-lived GHG such as methane deserve in the climate debate. Conclusion To best mitigate climate change along with environmental co-benefits on a nZEN level, measures should be taken at different points in time. At the early planning stages, incentives should be in place that promote dwellings of reasonable sizes (measured per inhabitant) along with incentives to decarbonize the materials value chains, in- and out-land. Over time, a culture of car- and ride-sharing will have positive environmental benefits. When renovating, incentives that promote the reshaping of dwellings into dwellings of smaller sizes will help to shift the sole focus on nZEB standards to multi-layers strategies.

scholarly journals Bayesian hierarchical models for disease mapping applied to contagious pathologies

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0222898
Author(s):  
Sylvain Coly ◽  
Myriam Garrido ◽  
David Abrial ◽  
Anne-Françoise Yao
Keyword(s):  
Infectious Diseases ◽  
Bovine Tuberculosis ◽  
Hierarchical Models ◽  
Negative Binomial ◽  
Disease Risk ◽  
Disease Mapping ◽  
Real Data ◽  
Bayesian Hierarchical Models ◽  
Bayesian Hierarchical ◽  
Temporal Dependencies

Disease mapping aims to determine the underlying disease risk from scattered epidemiological data and to represent it on a smoothed colored map. This methodology is based on Bayesian inference and is classically dedicated to non-infectious diseases whose incidence is low and whose cases distribution is spatially (and eventually temporally) structured. Over the last decades, disease mapping has received many major improvements to extend its scope of application: integrating the temporal dimension, dealing with missing data, taking into account various a prioris (environmental and population covariates, assumptions concerning the repartition and the evolution of the risk), dealing with overdispersion, etc. We aim to adapt this approach to model rare infectious diseases proposing specific and generic variants of this methodology. In the context of a contagious disease, the outcome of a primary case can in addition generate secondary occurrences of the pathology in a close spatial and temporal neighborhood; this can result in local overdispersion and in higher spatial and temporal dependencies due to direct and/or indirect transmission. In consequence, we test models including a Negative Binomial distribution (instead of the usual Poisson distribution) to deal with local overdispersion. We also use a specific spatio-temporal link in order to better model the stronger spatial and temporal dependencies due to the transmission of the disease. We have proposed and tested 60 Bayesian hierarchical models on 400 simulated datasets and bovine tuberculosis real data. This analysis shows the relevance of the CAR (Conditional AutoRegressive) processes to deal with the structure of the risk. We can also conclude that the negative binomial models outperform the Poisson models with a Gaussian noise to handle overdispersion. In addition our study provided relevant maps which are congruent with the real risk (simulated data) and with the knowledge concerning bovine tuberculosis (real data).

scholarly journals “Scuola Sicura”: a school screening program to prevent the spread of COVID-19 among students in Piedmont, Italy

2021 ◽  
Author(s):  
Elena Farina ◽  
Ilenia Eboli ◽  
Teresa Spadea ◽  
Carlo Saugo ◽  
Lorenzo Richiardi ◽  
...  
Keyword(s):  
Secondary Schools ◽  
Large Scale ◽  
Screening Program ◽  
Transmission Rate ◽  
Outcome Evaluation ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Local Health ◽  
Regional Government ◽  
School Screening

Abstract ObjectivesThe regional government of Piedmont approved an experimental screening testing program entitled “Scuola Sicura” with the aim to: rapidly contain thes spread of COVID-19 in the school population together with general mitigation strategies such as contact tracing, and case isolation, and to monitor the transmission rate in this population. In this paper we report the initial process and outcome evaluation results and the criticalities encountered during program rollout.DesignDescriptive study of the trend in the period Janaury-March 2021.The evaluation of the preventive capacity of the program is limited to the period of in-class learning. The data sources used are the COVID-19 platform Piedmont, the archives of the local health Departments and the CedAP-SDO archive. Setting and participantsThe screening program targeted second and third grade students in first level secondary schools throughout Piedmont. Each class was subdivided into four groups; one group each week underwent screening, yielding one test per student per month.Main outcome measuresThe following indices were calculated with a 95% confidence interval: 1. number of positive cases detected vs. total number of students tested in the “Scuola Sicura” program;2. number of positive cases detected outside the “Scuola Sicura” program vs total number of students enrolled in the 2nd and 3rd grades of first-level secondary schools in Piedmont.To evaluate the preventive capacity, quarantines were detected. In order to investigate the spread of COVID-19 in households, the mother-child pair was tracked and cases of positivity among mothers were identified. Results69% of schools in Piedmont participated in the program; the actual participation was 19.5% of the total number of students enrolled in second and third grades of first-level secondary schools. SS detected 114 positives cases for SARS-CoV-2, yielding a prevalence of 0.52% (95%CI 0.42-0.61) when calculated for the total number of students tested by the program. Starting from 08.03.2021, the target classes have started distance learning: 69 of the 114 positive students were identified before that date, leading to the activation of 67 quarantine measures. For 61 of the 69 cases (88%) identified by SS before 8 March, the mother-child couple was reconstruncted through record linkage between the CedAP and SDO archives. Forty-six mothers perfomed a swab test after that of the child with a positive result in 24% of cases (n=11). Asymptomatic cases identified at screening accounted for 26.5% of the total number of cases occurred in the participating classes.ConclusionsThis is one of the few studies (and the first in Italy) to describe the functioning and predictive capacity of school screening testing for COVID-19 in a real-world situation. Our findings provide data-driven suggestions for government agencies when planning large-scale school screening testing programs. When well organized and implemented jointly with other transmission prevention measures and contact tracing, school screening may be a viable strategy to keep schools open when high levels of the virus are circulating in the community.

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