The Ecology of Parasitism
Eric S. Loker, Bruce V. Hofkin in Parasitology, 2015
The disciplines of epidemiology and ecology have much in common. Both seek to understand patterns in the distribution and abundance of organisms (such as a particular parasite species that causes a human disease), and both are interested in revealing the processes (determinants) that underlie the patterns. The goal of epidemiology is often to identify risk factors and to anticipate and prevent disease outbreaks. Epidemiological studies are often undertaken in the context of human public health, but epidemiologists also study disease outbreaks in different kinds of hosts, ranging from oak trees to honeybees to horses. For example, the term epizootiology refers to the study of the distribution and determinants of disease in animals. Epidemiologists are interested in a triad of factors (host, parasite, and environment) and how they intersect to create the opportunity for disease transmission.
What Is Special about Infectious Disease Epidemiology?
Johan Giesecke in Modern Infectious Disease Epidemiology, 2017
For influenza, however, my risk of disease during the coming winter will be greatly affected by the number of influenza patients around, and if many of the people I meet have been vaccinated, my risk of contracting influenza will decrease even if I myself have not been vaccinated. Treatment of a tuberculosis case will dramatically lessen the risk of disease in members of the patient's family. For many of the infectious diseases, someone who is a case will at the same time be a risk factor for disease in other people. The clear distinction between the two categories ‘risk factor’ and ‘case’ becomes blurred. The fact that a case may be a source of disease in others also means that contact patterns in society – Who meets whom? How? How often? – become very important issues if we want to understand the epidemiology of infectious diseases.
Introduction
Leonhard Held, Niel Hens, Philip O’Neill, Jacco Wallinga in Handbook of Infectious Disease Data Analysis, 2019
Rather than introducing concepts chapter by chapter, we will provide in each chapter a different perspective on the same basic concepts. First, we take a biological perspective to see how the dependencies in the data arise. We provide an epidemiological background on the infectious disease data, how they are collected, and typical data types and data structures. We introduce the key variables in infectious disease analysis that are familiar from statistical epidemiology, such as incidence, prevalence, and hazard rates. We introduce the key variables in infectious disease data analysis that are familiar from demography and population biology, such as the reproduction number, the generation interval, contact rates, the epidemiological growth rate, and the required control effort. Once these concepts are in place, we offer a basic outline of the epidemic models that describe the dependency structure inherent to the infectious disease data. Throughout, the objective of Part II is to reveal the coherence of the basic concepts.
Extinction and persistence of a stochastic delayed Covid-19 epidemic model
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Amir Khan, Rukhsar Ikram, Anwar Saeed, Mostafa Zahri, Taza Gul, Usa Wannasingha Humphries
Epidemiology is the study of the determinants, occurrence, and distribution of health and disease in a defined population. The importance of this field can be seen in the fact that its interest is growing day by day. Therefore, many mathematical models have been created in the past, such as SI, SIR, H1N1, HBV, SIS model, SARS, SIER model, H5N1, etc., as you can see in Kermack et al. (1927), Billard and Dayananda (2014), and Pongsumpun and Tang (2014). All these problems have been formulated mathematically to make realistic predictions and provide information to society about the diseases which are helpful for a stable society and stable health (Upadhyay et al. 2008; Naheed et al. 2014; Din et al. 2020). The stability and prevention of various diseases in human population societies are important and necessary issues. After the first attempt of Mckendrick and Kermack (Kermack et al. 1932; Khan et al. 2021), the mentioned models for the control of various diseases were analyzed in detail. Based on this approach and the basic concepts, different researchers have modified and developed the epidemic models by including vaccine class and time delay (Edmunds et al. 1996; Atangana and Koca 2016; Ullah et al. 2018; Danane et al. 2020; Din et al. 2020; Khan et al. 2021).
Toward a science-based testing strategy to identify maternal thyroid hormone imbalance and neurodevelopmental effects in the progeny – part I: which parameters from human studies are most relevant for toxicological assessments?
Published in Critical Reviews in Toxicology, 2020
Ursula G. Sauer, Alex Asiimwe, Philip A. Botham, Alex Charlton, Nina Hallmark, Sylvia Jacobi, Sue Marty, Stephanie Melching-Kollmuss, Joana A. Palha, Volker Strauss, Bennard van Ravenzwaay, Gerard Swaen
Epidemiology is the discipline addressing the distribution of disease among human populations thereby aiming at identifying its causes and contributory factors (Hajat 2011). The scientific methodologies available in epidemiology are fundamentally different from those available for toxicological assessments. Toxicologists assessing chemical-induced effects can apply experimental study designs and testing strategies using a broad spectrum of test methods, many of which are standardised and adopted as internationally agreed formal guidance. By contrast, epidemiologists, when evaluating human health effects potentially caused by chemical exposure, are nearly always limited to non-experimental, observational study designs (WHO IPCS 2004), and the types of health parameter measurements that can be made are much more restricted than e.g. in regulatory toxicology.
Cystic fibrosis in Canada: A historical perspective
Published in Canadian Journal of Respiratory, Critical Care, and Sleep Medicine, 2021
Tania N. Petruzziello-Pellegrini, Alphonse Jeanneret, Mark Montgomery, Georges Rivard, Elizabeth Tullis, André M. Cantin
With increasing concern over BCC, David Speert established the Canadian Burkholderia cepacia Complex Research and Referral Repository (CBCCRRR) in Vancouver in 1994 to collect samples isolated from CF patients across Canada. CF Canada has provided continuous financial support to the CBCCRRR since 2001. The aims were to aid in the taxonomy of this highly complex group of organisms and to better understand its epidemiology which, in turn, helped to inform infection control practices.40 In the process, CBCCRRR researchers developed B. cepacia selective agar, a medium now commonly used around the world to isolate BCC from patient samples.41 With a wealth of expertise and approximately 2,400 BCC isolates banked, the Repository continues to contribute to the identification of novel BCC species, offers identification services to CF clinics across Canada, and provides BCC isolates to the research community.42,43
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