scholarly journals Using next generation matrices to estimate the proportion of cases that are not detected in an outbreak

2021 ◽  
Author(s):  
H Juliette T Unwin ◽  
Anne Cori ◽  
Natsuko Imai ◽  
Katy A M Gaythorpe ◽  
Sangeeta Bhatia ◽  
...  
Keyword(s):  
New Zealand ◽  
Disease Outbreaks ◽  
Credible Interval ◽  
Contact Tracing ◽  
Surveillance Systems ◽  
Next Generation ◽  
Outbreak Response ◽  
Disease Response ◽  
Infectious Disease Outbreaks ◽  
Novel Method

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for many infectious disease outbreaks, such as Ebola and SARS-CoV-2. Unfortunately, these systems are not fully effective, and cases can still go undetected as people may not know or remember all of their contacts or contacts may not be able to be traced. A large proportion of undetected cases suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a novel method for estimating the proportion of cases that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing and case line-lists. We use this method to investigate the proportion of undetected cases in two case studies: the SARS-CoV-2 outbreak in New Zealand during 2020 and the West African Ebola outbreak in Guinea during 2014. We estimate that only 6% of SARS-CoV-2 cases were not detected in New Zealand (95% credible interval: 1.31 - 16.7%), but over 60% of Ebola cases were not detected in Guinea (95% credible interval: 15 - 90%).

scholarly journals Surveillance System Evaluations Provide Evidence to Improve Public Health Practice

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Beverley J. Paterson ◽  
David N. Durrheim
Keyword(s):  
Public Health ◽  
Public Health Practice ◽  
Disease Outbreaks ◽  
Surveillance Systems ◽  
Health Practice ◽  
Outbreak Response ◽  
Local Public Health ◽  
Infectious Disease Outbreaks ◽  
The Pacific ◽  
Surveillance Practice

Surveillance evaluations of surveillance systems should provide evidence to improve public health practice. In response to surveillance evaluation findings amongst Pacific Island Countries and Territories that identified a critical need to better equip local public health officials with skills to rapidly appropriately respond to suspected infectious disease outbreaks across the Pacific, the RAPID (Response and Analysis for Pacific Infectious Diseases) project was implemented to strengthen capacity in surveillance, epidemiology and outbreak response. The RAPID project is a notable example of how evidence gathered through a surveillance evaluation can be used to improve public health surveillance practice.

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 Evaluation of the Nipah epidemic containment and multisectoral involvement in Kerala using an appropriate management framework

2020 ◽  
Vol 7 (7) ◽  
pp. 2813
Author(s):  
Asma A. Rahim ◽  
Sujina C. Muthukutty ◽  
Sabitha R. Jacob ◽  
Rini Ravindran ◽  
Jayakrishnan Thayyil ◽  
...  
Keyword(s):  
Health Personnel ◽  
Viral Infections ◽  
Nipah Virus ◽  
Disease Outbreaks ◽  
State Level ◽  
The State ◽  
Contact Tracing ◽  
Outbreak Response ◽  
Management Framework ◽  
The Government

Kozhikode district of North Kerala, India witnessed an outbreak of Nipah virus (NiV) in the month of May 2018. Two adjacent districts were affected leaving 17 patients dead out of the 19 confirmed. United Nations and WHO lauded the expeditious response of the state’s health system in the diagnosis and containment of the outbreak which was unprecedented. The authors being in the contact tracing and surveillance operation district team, had kept a record of timeline of events and actions at the state level, compiled the news clippings and tracked events. In the absence of an end‑of‑epidemic report for reference, these records served as a valuable tool for the present review. We used the Management science for health frame work tool (MSH framework) to evaluate the district and state coordinated actions which helped in curbing the outbreak. Though NiV outbreak in South India (2018) had similar epidemiological features to previous disease outbreaks, it stands out as the one to be detected and contained in a short span of time. As health personnel working in the government medical college of an affected district and directly involved in contact tracing operations and containment measures, exploring and sharing, what worked and how, in the context of multidisciplinary response and recovery attempts of the outbreak in the state may be beneficial to public health personnel and policy makers. This management framework may be replicated in the national and international context, particularly in South East Asian region under threat of emerging viral infections like COVID-19, lacking specific epidemic management frameworks for outbreak response and containment.

scholarly journals Ethics of instantaneous contact tracing using mobile phone apps in the control of the COVID-19 pandemic

2020 ◽  
Vol 46 (7) ◽  
pp. 427-431 ◽  
Author(s):  
Michael J Parker ◽  
Christophe Fraser ◽  
Lucie Abeler-Dörner ◽  
David Bonsall
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Mobile Phone ◽  
Public Health Practice ◽  
Disease Outbreaks ◽  
Contact Tracing ◽  
Mobile Phone Data ◽  
Public Health Response ◽  
Infectious Disease Outbreaks ◽  
Ethical Implications

In this paper we discuss ethical implications of the use of mobile phone apps in the control of the COVID-19 pandemic. Contact tracing is a well-established feature of public health practice during infectious disease outbreaks and epidemics. However, the high proportion of pre-symptomatic transmission in COVID-19 means that standard contact tracing methods are too slow to stop the progression of infection through the population. To address this problem, many countries around the world have deployed or are developing mobile phone apps capable of supporting instantaneous contact tracing. Informed by the on-going mapping of ‘proximity events’ these apps are intended both to inform public health policy and to provide alerts to individuals who have been in contact with a person with the infection. The proposed use of mobile phone data for ‘intelligent physical distancing’ in such contexts raises a number of important ethical questions. In our paper, we outline some ethical considerations that need to be addressed in any deployment of this kind of approach as part of a multidimensional public health response. We also, briefly, explore the implications for its use in future infectious disease outbreaks.

scholarly journals Comparison of Statistical Algorithms for the Detection of Infectious Disease Outbreaks in Large Multiple Surveillance Systems

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0160759 ◽  
Author(s):  
Doyo G. Enki ◽  
Paul H. Garthwaite ◽  
C. Paddy Farrington ◽  
Angela Noufaily ◽  
Nick J. Andrews ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Outbreaks ◽  
Surveillance Systems ◽  
Infectious Disease Outbreaks ◽  
Statistical Algorithms

scholarly journals Outbreak analytics: a developing data science for informing the response to emerging pathogens

2019 ◽  
Vol 374 (1776) ◽  
pp. 20180276 ◽  
Author(s):  
Jonathan A. Polonsky ◽  
Amrish Baidjoe ◽  
Zhian N. Kamvar ◽  
Anne Cori ◽  
Kara Durski ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Data Science ◽  
Disease Outbreaks ◽  
Health Concern ◽  
Emerging Pathogens ◽  
Outbreak Response ◽  
Theme Issue ◽  
Effective Response ◽  
Infectious Disease Outbreaks ◽  
Challenges And Opportunities

Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics , an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control‘. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

scholarly journals Characterizing risk of Ebola transmission based on frequency and type of case–contact exposures

2017 ◽  
Vol 372 (1721) ◽  
pp. 20160301 ◽  
Author(s):  
Laura A. Skrip ◽  
Mosoka P. Fallah ◽  
Stephen G. Gaffney ◽  
Rami Yaari ◽  
Dan Yamin ◽  
...  
Keyword(s):  
West Africa ◽  
Disease Outbreaks ◽  
West African ◽  
Contact Tracing ◽  
Transmission Potential ◽  
Infectious Disease Outbreaks ◽  
High Transmission ◽  
Increased Risk ◽  
Source Case ◽  
Risk Of Exposure

During the initial months of the 2013–2016 Ebola epidemic, rapid geographical dissemination and intense transmission challenged response efforts across West Africa. Contextual behaviours associated with increased risk of exposure included travel to high-transmission settings, caring for sick and preparing the deceased for traditional funerals. Although such behaviours are widespread in West Africa, high-transmission pockets were observed. Superspreading and clustering are typical phenomena in infectious disease outbreaks, as a relatively small number of transmission chains are often responsible for the majority of events. Determining the characteristics of contacts at greatest risk of developing disease and of cases with greatest transmission potential could therefore help curb propagation of infection. Our analysis of contact tracing data from Montserrado County, Liberia, suggested that the probability of transmission was 4.5 times higher for individuals who were reported as having contact with multiple cases. The probability of individuals developing disease was not significantly associated with age or sex of their source case but was higher when they were in the same household as the infectious case. Surveillance efforts for rapidly identifying symptomatic individuals and effectively messaged campaigns encouraging household members to bring the sick to designated treatment centres without administration of home care could mitigate transmission. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

scholarly journals Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases

2019 ◽  
Vol 374 (1775) ◽  
pp. 20180258 ◽  
Author(s):  
M. Alamil ◽  
J. Hughes ◽  
K. Berthier ◽  
C. Desbiez ◽  
G. Thébaud ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Statistical Learning ◽  
Sequence Data ◽  
Disease Outbreaks ◽  
Plant Diseases ◽  
Training Data ◽  
Contact Tracing ◽  
Sequencing Data ◽  
Theme Issue ◽  
Infectious Disease Outbreaks

Pathogen sequence data have been exploited to infer who infected whom, by using empirical and model-based approaches. Most of these approaches exploit one pathogen sequence per infected host (e.g. individual, household, field). However, modern sequencing techniques can reveal the polymorphic nature of within-host populations of pathogens. Thus, these techniques provide a subsample of the pathogen variants that were present in the host at the sampling time. Such data are expected to give more insight on epidemiological links than a single sequence per host. In general, a mechanistic viewpoint to transmission and micro-evolution has been followed to infer epidemiological links from these data. Here, we investigate an alternative approach grounded on statistical learning. The idea consists of learning the structure of epidemiological links with a pseudo-evolutionary model applied to training data obtained from contact tracing, for example, and using this initial stage to infer links for the whole dataset. Such an approach has the potential to be particularly valuable in the case of a risk of erroneous mechanistic assumptions, it is sufficiently parsimonious to allow the handling of big datasets in the future, and it is versatile enough to be applied to very different contexts from animal, human and plant epidemiology. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

scholarly journals Trends in Antimicrobial Resistance Patterns in Neisseria Gonorrhoeae in Australia and New Zealand: A Meta-analysis and Systematic Review

Antibiotics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 191
Author(s):  
Fletcher-Lartey ◽  
Dronavalli ◽  
Alexander ◽  
Ghosh ◽  
Boonwaat ◽  
...  
Keyword(s):  
New Zealand ◽  
Neisseria Gonorrhoeae ◽  
Meta Analysis ◽  
Contact Tracing ◽  
Surveillance Systems ◽  
Development Of Resistance ◽  
Resistance Patterns ◽  
Susceptibility Patterns ◽  
Over Time

(1) Background: The widespread development of resistance among Neisseria gonorrhoeae (NG) clinical isolates has been reported by surveillance systems around the world. This meta-analysis estimated the changes in susceptibility patterns among antibiotics under surveillance in Australia and New Zealand. (2) Methods: Articles published in English from 1980–2018, from Australia or New Zealand, that met the selection criteria were included. The meta-analysis was carried out using the R statistical software. (3) Results: In Australia, there has been decreasing susceptibility of gonococcal isolates to selected antimicrobials over time. Azithromycin (Odds Ratio (OR): 0.73; 95% Confidence Interval (CI) 0.64–0.82) and ceftriaxone (OR: 0.69; 95% CI 0.59–0.80) showed decreasing levels of susceptibility each year. Western Australia (OR: 0.76; 95% CI 0.60–0.96) and Victoria (OR: 0.74; 95% CI 0.60–0.90) also had decreasing levels of susceptibility to ceftriaxone over time compared with other states and territories. (4) Conclusions: The results highlight the need for the development of new approaches for managing cases of gonorrhoea. Improved antimicrobial stewardship, enhanced surveillance and contact tracing are needed to identify and respond to changes in antibiotic resistance in a timely manner. Increasing awareness and public health follow-up of cases can help to interrupt the cycle of infection and limit transmission.

scholarly journals De-escalation strategies for non-pharmaceutical interventions following infectious disease outbreaks: a rapid review and a proposed dynamic de-escalation framework

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Charbel El Bcheraoui ◽  
Sophie Alice Müller ◽  
Eleanor C Vaughan ◽  
Andreas Jansen ◽  
Robert Cook ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Grey Literature ◽  
Disease Outbreaks ◽  
Final Analysis ◽  
Control Measures ◽  
System Capacity ◽  
Contact Tracing ◽  
Rapid Review ◽  
Infectious Disease Outbreaks ◽  
Pharmaceutical Interventions

Abstract Background The severity of COVID-19, as well as the speed and scale of its spread, has posed a global challenge. Countries around the world have implemented stringent non-pharmaceutical interventions (NPI) to control transmission and prevent health systems from being overwhelmed. These NPI have had profound negative social and economic impacts. With the timeline to worldwide vaccine roll-out being uncertain, governments need to consider to what extent they need to implement and how to de-escalate these NPI. This rapid review collates de-escalation criteria reported in the literature to provide a guide to criteria that could be used as part of de-escalation strategies globally. Methods We reviewed literature published since 2000 relating to pandemics and infectious disease outbreaks. The searches included Embase.com (includes Embase and Medline), LitCovid, grey literature searching, reference harvesting and citation tracking. Over 1,700 documents were reviewed, with 39 documents reporting de-escalation criteria included in the final analysis. Concepts retrieved through a thematic analysis of the included documents were interlinked to build a conceptual dynamic de-escalation framework. Results We identified 52 de-escalation criteria, the most common of which were clustered under surveillance (cited by 43 documents, 10 criteria e.g. ability to actively monitor confirmed cases and contact tracing), health system capacity (cited by 30 documents, 11 criteria, e.g. ability to treat all patients within normal capacity) and epidemiology (cited by 28 documents, 7 criteria, e.g. number or changes in case numbers). De-escalation is a gradual and bi-directional process, and resurgence of infections or emergence of variants of concerns can lead to partial or full re-escalation(s) of response and control measures in place. Hence, it is crucial to rely on a robust public health surveillance system. Conclusions This rapid review focusing on de-escalation within the context of COVID-19 provides a conceptual framework and a guide to criteria that countries can use to formulate de-escalation plans.

Sign in / Sign up

Export Citation Format

Share Document