Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Hindcasting trends of infection using crossectional test data

Infectious diseases are a major threat to the wellbeing of humans, livestock, and wildlife. However, there is often a paucity of information for responding to these threats, and thus a need to make efficient use of existing data. This thesis shows how to use Bayesian analysis to maximise the information gained from already collected diagnostic test data. First, the commonly used latent class analysis of multiple binary diagnostic tests is ex- tended to account for vaccinated individuals, and used to estimate the effect of study size on sensitivity and specificity estimates of DIVA (”Distinguishing Infected and Vaccinated Animals”) tests for bovine Tuberculosis. It is then shown how quantitative test responses can be used as clocks indicating the time since infection to “hindcast” historic trends of disease incidence using cross-sectional data. This is used to determine whether an endemic disease is increasing or decreasing up to the time of sampling, enabling the tracking of trends in populations where routine surveillance data is not available. It is further demonstrated how to hindcast the rise and fall of disease outbreaks. Using the 2007 UK Bluetongue virus outbreak and a whooping cough outbreak as examples, it is shown that hindcasting can be used to determine whether an outbreak is increasing or past its peak at the time of sampling, thus informing potential outbreak responses. In the light of these methods for analysing quantitative test data, the challenges of generating data on test kinetics are discussed. Suggestions are given for how to improve on current methods by modelling the development of paired diagnostic tests as a dynamic host-pathogen system. This thesis demonstrates that multiple quantitative tests can be used to recover disease trends in a population. These methods have far-reaching consequences for the design and practice of disease surveillance in all contexts

Multi-host disease management: the why and the how to include wildlife

<p>In recent years, outbreaks caused by multi-host pathogens (MHP) have posed a serious challenge to public and animal health authorities. The frequent implication of wildlife in such disease systems and a lack of guidelines for mitigating these diseases within wild animal populations partially explain why the outbreaks are particularly challenging. To face these challenges, the French Ministry of Agriculture launched a multi-disciplinary group of experts that set out to discuss the main wildlife specific concepts in the management of MHP disease outbreaks and how to integrate wildlife in the disease management process. This position paper structures the primary specific concepts of wildlife disease management, as identified by the working group. It is designed to lay out these concepts for a wide audience of public and/or animal health officers who are not necessarily familiar with wildlife diseases. The group's discussions generated a possible roadmap for the management of MHP diseases. This roadmap is presented as a cycle for which the main successive step are: step 1-descriptive studies and monitoring; step 2-risk assessment; step 3-management goals; step 4-management actions and step 5-assessment of the management plan. In order to help choose the most adapted management actions for all involved epidemiological units, we integrated a decision-making framework (presented as a spreadsheet). This tool and the corresponding guidelines for disease management are designed to be used by public and health authorities when facing MHP disease outbreaks. These proposals are meant as an initial step towards a harmonized transboundary outbreak response framework that integrates current scientific understanding adapted to practical intervention.</p

Climate information for public health : a curriculum for best practices : putting principles to work

The mission of the IRI is to enhance society’s capability to understand, anticipate and manage the impacts of climate in order to improve human welfare and the environment, especially in developing countries. The IRI conducts this mission through strategic and applied research, education, capacity building, and by providing forecasts and information products with an emphasis on practical and verifiable utility and partnership

Prospects for Schistosomiasis Elimination

Current efforts to limit the ravages of schistosomiasis are pushing the world closer to eliminating a chronic infection that has been associated with human life in the tropics since time immemorial. This notwithstanding, the disease remains a scourge for large populations in sub-Saharan Africa, Latin America, and Southeast Asia, and the main part of this book is made up by papers dealing with its current distribution, discussing ways and means to establish and implement improved control approaches. While chemotherapy limits the symptoms caused by schistosomiasis, the number of infected people will not decrease until the parasite's life cycle is interrupted. To that end, some papers focus on the intermediate snail host, which is notoriously difficult to control, while others discuss human hygiene and sanitation. The latter approach not only prevents infection through avoiding people being infected from the snail, but more importantly, also stops people infecting the snail by leaving contagious feces and urine in nature. With morbidity reduced by chemotherapy, the immediate target now is the interruption of transmission to be achieved by new tools, such as the novel chemotherapies, improved diagnostics (for humans, animals, and snails), and vaccines discussed in several of the papers. As made clear in this book, a complex infection requires new tools as well as work on many fronts, above all; however, a clear idea is needed as to how to skillfully combine the tools available and sustain implemented control activities

Tsunami - Analysis of a Hazard

This book, the third in the InTech Tsunami series, has been published in order to deepen efforts towards the understanding of tsunami dynamics that seems to be never enough. As the previous books in this series, "The Tsunami Threat - Research and Technology" (January 2011) and "Tsunami - A Growing Disaster" (December 2011), this multi-disciplinary volume compiles a collection of scientific papers showing the state-of-the-art of tsunami research at different levels. The various contributions cover an array of themes that span from geological evidence to post-trauma human care, encompassing pre-tsunami analyses and modeling to post-tsunami management and preparedness techniques. As its counterparts, "Tsunami - Analysis of a Hazard: from physical interpretation to human impact" continues to present evidence and case studies from different regions of the World: from the isolated Hawaiian Islands and Northern Indian Ocean, to the edges of the Atlantic and Eastern Mediterranean

Applied epidemiology of COVID-19 and other respiratory diseases, Victoria, 2020-2021

This thesis demonstrates achievement of the competency requirements of the Australian National University's Master of Philosophy in Applied Epidemiology (MAE). My MAE placement was at the WHO Collaborating Centre for Reference & Research on Influenza in Melbourne from March 2020 to October 2021. I participated in four projects fulfilling the four major competencies of the MAE program, including: 1) an early epidemiologic study of the spectrum of COVID-19 describing a high attack rate and low symptomatic fraction in a cohort of adults exposed to SARS-CoV-2 on an Antarctic cruise; 2) investigation and contact tracing of multiple COVID-19 outbreaks affecting health care workers at a major Melbourne hospital, from which one in ten close contacts tested positive for SARS-CoV-2 while in quarantine; 3) an investigation of the short-term effects of ambient fine particulate matter on healthcare encounters for respiratory illness in Melbourne; and 4) an evaluation of two systems for COVID-19 surveillance in residential aged care in Victoria, aimed at informing ongoing respiratory outbreak surveillance efforts. I present each project together with reflective discussion of relevant population health implications and lessons learned. I address achievement of all minor MAE competencies at various points throughout the thesis

Non-communicable Diseases, Big Data and Artificial Intelligence

This reprint includes 15 articles in the field of non-communicable Diseases, big data, and artificial intelligence, overviewing the most recent advances in the field of AI and their application potential in 3P medicine

Student Spotlight on Research and Outreach Proceedings

ESF\u27s annual Spotlight Symposium is a dynamic forum where graduate and undergraduate students share the results of their research and community service projects. The Spotlight is a student poster session highlighting scholarly efforts