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A Dictionary of Epidemiology

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Miquel Porta at IMIM Hospital del Mar Medical Research Institute
Miquel Porta
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Abstract

The new edition of this classic text remains the definitive dictionary in epidemiology. In fact, it is more than a dictionary, with some reviewers remarking that if they had to limit their professional library to one volume, this would be the book they would choose. In the complex field of epidemiology, the definition and concise explanation of terms is a key to understanding epidemiologic concepts, and the dictionary goes beyond simple definitions, as it place each term firmly and clearly in its fuller epidemiologic context. The new edition sees Miguel Porta as editor, with the legendary John Last remaining as associate editor. There are a large number of new terms, and the new edition features new artwork and fresh, new, clean design. There is nothing else like it in epidemiology.
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in the implementation of the mandatory
intervention laws.
J Epidemiol Community Health 2006;60:652–
653.
doi: 10.1136/jech.2006.046300
Correspondence to: Dr C Vives-Cases, Alicante
University, Campus Sant Vicent Raspeig
Alicante, Spain 03080; carmen.vives@ua.es
REFERENCES
1Loewenberg S. Domestic Violence in Spain.
Lancet 2005;365:464.
2Vives-Cases C, Gil-Gonza´lez D, Carrasco-
Portin˜oM,et al. Gender based violence in the
Spanish parliamentary agenda (1979–2004).
Gac Sanit (in press).
3Vives-Cases C, Ruiz MT, A
´lvarez-Dardet C, et al.
Recent history of the news coverage of violence
against women in Spain, 1997–2001. Gac Sanit
2005;19:22–8.
4Vives-Cases C,A
´lvarez-Dardet C, Caballero P.
Intimate partner violence in Spain. Gac Sanit
2003;17:268–74.
5Vives-Cases C, Caballero P, A
´lvarez-Dardet C.
Temporal analysis of mortality due to intimate
partner violence in Spain. Gac Sanit
2004;18:346–50.
6Vives-Cases C,A
´lvarez-Dardet C, Colomer C,
et al. Health advocacy in violence against women:
an experience. Gac Sanit 2005;19:262–4.
7Garcı´a A, Ramos J, Sa´nchez J, et al. Evolucio´nde
la Vigilancia Epidemiolo´gica de la brucelosis en
Extremadura durante el an˜o 2000. Centro
Nacional de Epidemiologı´a 2002;10:261.
8Gracia E. Unreported cases of domestic
violence against women: towards an
epidemiology of social silence, tolerance and
inhibition. J Epidemiol Community Health
2004;58:536–7.
9Ruiz-Perez I, Plazaola-Castan˜o J, del Rio
Lozano M. How do women in Spain deal with an
abusive relationship?J Epidemiol Community
Health 2006;60:706–11.
Speaker’scorner
..............................................................................
A dictionary of epidemiology, 5th edition. A call for submissions
through an innovative wiki
The International Epidemiological Association (IEA) and
Oxford University Press (OUP) are pleased to announce
that work has begun on the 5th edition of A dictionary of
epidemiology, whose first four editions were edited by John
Last (Ottawa) and published by OUP. This new edition will
be edited under the leadership of Miquel Porta (Barcelona),
who was selected for such task by the IEA Council in 2000.
The tentative publication date is September of 2008, to
coincide with the IEA world congress of epidemiology in
Porto Alegre, Brazil.
Members of IEA and all other epidemiologists worldwide
are cordially invited to contribute to the work by submitting
to the editor amendments, corrections of existing definitions,
and new material. There is already a small file of suggested
amendments and possible additions to the new edition,
which John Last received and kindly guarded since publica-
tion of the 4th edition in 2001.
1
Further contributions, corrections, and comments are
warmly welcomed at our exciting new wiki: rather than
communicating via email, we have established a collaborative
web site—a wiki (http://tinyurl.com/h44w3)—where all
interested parties can participate in the creation of this new
edition. Unlike occasionally chaotic and often unstructured
email based discussions,
2
the wiki is designed to organise and
structure contributions from a great diversity of profes-
sionals. Please note that the wiki is the only way to make
your contribution.
If you would like to contribute to the 5th edition, for more
information, and for specific instructions, please visit http://
tinyurl.com/h44w3.
To submit a contribution, suggestion, or comment you do
not need to be a full time epidemiologist. Rather, I expect
that potential contributors will have one of at least three
broad types of professional relationships with epidemiology:
(1) a significant portion of contributors will have some to
extensive training in epidemiology and currently work or
have professional experience as an epidemiologist (they may
also have professional experience in other fields); (2) some
will consider that their main job is not as an epidemiologist,
but will often use epidemiological knowledge, methods or
reasoning in their work; and (3) still other potential
contributors will have little to no training in epidemiology,
and seldom or never use it in their work (their contribution is
nevertheless also welcomed).
34
Therefore, I shall do my best
to enable participation from a broad range of academic
cultures and for the dictionary to continue to enlighten the
many uses of epidemiology in contemporary science, teaching
and practice—within and outside public health and the other
health, life, and social sciences.
5–7
We look forward to your criticisms, comments, and
suggestions. Thank you all for your kind attention!
Miquel Porta
Institut Municipal d’Investigacio´Me`dica, Barcelona, Spain; School of
Medicine, Universitat Auto`noma de Barcelona, Spain; School of Public
Health, University of North Carolina at Chapel Hill, USA
Correspondence to: Professor M Porta, Clinical and Molecular
Epidemiology of Cancer Unit, Institut Municipal d’Investigacio´Me`dica
(IMIM), Universitat Auto`noma de Barcelona, Carrer del Dr. Aiguader
80, E-08003 Barcelona, Catalonia, Spain; mporta@imim.es
REFERENCES
1Last JM, ed. A dictionary of epidemiology. 4th ed. New York: Oxford
University Press, 2001.
2Porta M. Do we really need ‘real’epidemiological scientific meetings?
Eur J Epidemiol 2003;18:101–3.
3Bolu´mar F, Porta M. Epidemiologic methods: beyond clinical medicine,
beyond epidemiology. Eur J Epidemiol 2004;19:733–5.
4Porta M. Things that kept coming to mind while thinking through Susser’s
South African memoir. J Epidemiol Community Health 2006;60:559–61.
5Barros H, Porta M. Bridging worlds–the European congress of epidemiology.
J Epidemiol Community Health 2004;58(suppl 1):iii–v.
6Porta M,A
´lvarez-Dardet C. Epidemiology: bridges over (and across) roaring
levels. J Epidemiol Community Health 1998;52:605.
7Porta M. Epidemiologic plausibility. Am J Epidemiol 1999;150:217–18.
EDITORIALS 653
www.jech.com
... Incidence and mortality are flow variables, representing the number of new NCD cases and the number of NCD-related deaths occurring in a specific at-risk population over a defined period (e.g., one year). Prevalence is a stock variable, indicating the number of existing NCD cases in a specific population at a particular point in time (Porta, 2014). ...
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... " Epidemic, conversely, is "the occurrence in a community or region of cases or an illness, specific health-related behaviour, or other health-related events clearly in excess of normal expectancy. " 1 Though used earlier in the context of infectious disease, the word epidemic is also frequently used nowadays as a noun or adjective while discussing non-communicable diseases (NCDs). 2 Earlier discussants described the concept of diabetes endemicity instead of epidemicity. 2 The phenomenon of endemicity has also been applied to other NCDs like goitre or iodine deficiency disorders. ...
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... A methodological limitation could be seen in the results of the street surveys, which are based on random interviews and not on a representative sample. According to Scott (2014) and Porta (2014), samples are representative if the characteristics of the sample match those of the population from which the sample was drawn. From a population of approximately 13,000 residents of Wolfhagen, comparatively large samples of between 156 and 272 respondents participated in the surveys. ...
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... Autopilot -Tesla's brand name for its ADS AV -ADS-Equipped Vehicle operating in autonomous or transition mode bias -In epidemiology, a "systematic deviation of results or inferences from truth" (Porta, 2014, p. 21) [58]. It does not refer to personal biases or prejudices. ...
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Engineering reliability models from RAND, MobilEye, and Volvo concluded that billions of miles of on-road data were required to validate that the real-world fatality rate of an "Automated Driving System-equipped vehicle" (AV) fleet for an improvement over human-driven conventional vehicles (CV). RAND said 5 billion miles for 20%, MobileEye 30 billion for 99.9%, and Volvo 5 billion for 50% improvement. All these models used the Gaussian distribution , which is inaccurate for low crash numbers. The current study proposes a new epidemiologic method and criterion to validate real-world AV data with 95% confidence for zero to ten fatal crashes. The upper confidence limit (UL) of the AV fatal crash rate has to be lower than the CV fatal crash rate with 95% confidence. That criterion is met if the UL of the AV fatal crash incidence rate ratio estimate is below one. That UL was estimated using the mid-P exact method for calculating confidence limits for a dual Poisson process, using a one-tailed 95% confidence level. The required AV mileage was adjusted by trial and error until the UL was just below 1. The method was applied to the real-world fatal crash and mileage data from California (Waymo and GM Cruise), U.S. (Uber and Tesla), China (Tesla), and Sweden (Volvo) to calculate the AV miles required to validate a "Vision Zero" AV fatal crash objective with 95% confidence. For AV fleets in California, U.S., and China, the AV miles required are only in the millions. In Sweden, 1.9 billion AV miles are required because its CV fatal crash rates are already so low. In conclusion, epidemiologic analysis of real-world data finds that only millions of real-world AV data are typically required to validate AV safety with 95% confidence to a "Vision Zero" fatal crash criterion.
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... Based on methods developed by Young [10], Equation 1 predicts the RR as a function of ρ, the ratio of in-car to out-ofcar call rates, as follows: (1) The predicted RR in Equation 1 depends only on ρ, not on call duration in the billing records, nor on sampling window duration. Therefore, ρ predicts RR for any call or window duration. ...
Young 2014 An Unbiased Estimate of the Relative Crash Risk of Cell Phone Conversation while Driving an Automobile [article]
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A key aim of research into cell phone tasks is to obtain an unbiased estimate of their relative risk (RR) for crashes. This paper re-examines five RR estimates of cell phone conversation in automobiles. The Toronto and Australian studies estimated an RR near 4, but used subjective estimates of driving and crash times. The OnStar, 100-Car, and a recent naturalistic study used objective measures of driving and crash times and estimated an RR near 1, not 4 - a major discrepancy. Analysis of data from GPS trip studies shows that people were in the car only 20% of the time on any given prior day at the same clock time they were in the car on a later day. Hence, the Toronto estimate of driving time during control windows must be reduced from 10 to 2 min. Given a cell phone call rate about 7 times higher when in-car than out-of-car, and correcting for misclassification of some post-crash calls as pre-crash, the final required downward adjustment of the Toronto and Australian RR estimates is about 7 times. The Toronto adjusted RR is 0.61 and the Australian adjusted RR is 0.64, which now agree with the OnStar RR estimate of 0.62. All five adjusted RR estimates for cellular conversation while driving in automobiles are near 1, with a pooled RR of 0.61 (95% confidence interval 0.51 to 0.74). Talking on a cell phone while driving an automobile does not increase crash risk relative to not talking.
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... The foundations of this definition were first established by Hippocrates, who emphasised the importance of observing the individual, population, contributing factors, aetiology, and the context in which diseases occur, particularly in the case of mass outbreaks. The International Epidemiological Association (IEA) presents a definition by the Canadian epidemiologist John M. Last, which states that "epidemiology is the medical discipline concerned with the study of the distribution and determinants, conditions and phenomena associated with health in specified populations, and also with the application of the results of this study to the control of health problems" [3,4]. ...
THE ORIGINS AND DEVELOPMENT OF THE USE OF COMPUTER TECHNOLOGY IN THE FIELD OF EPIDEMIOLOGY IN THE SLOVAK REPUBLIC POČIATKY A ROZVOJ VYUŽITIA VÝPOČTOVEJ TECHNIKY V OBLASTI EPIDEMIOLÓGIE V SLOVENSKEJ REPUBLIKE
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The discipline of epidemiology is concerned with the study of the occurrence and distribution of health-related conditions and phenomena in specified populations. This includes an investigation of the determinants of these phenomena and the application of this knowledge in the control of health problems. The fundamental methodology employed in epidemiological research is epidemiological surveillance. This can be defined as "the continuous, systematic collection, analysis, and interpretation of health-related data and their timely dissemination to the concerned entities authorised to act on the matter". One of the key objectives of an epidemiological surveillance system is to facilitate the rapid utilisation of the information collected for the purpose of early warning of an epidemic, thereby enabling effective and rapid control of an outbreak. In this regard, the monitoring of communicable diseases constitutes a national responsibility within the health system. The necessity for extensive epidemiological data collection for the purpose of quality surveillance, coupled with the requirement to archive and process said data for analytical purposes, renders this practically impossible without the use of computer technology and information technology. In the Slovak Republic, the initial electronic registry that collected and recorded epidemiological data on communicable diseases (ISPO, Information System of Com-municable Diseases) was implemented in 1975. Since 1991, it has been superseded by a new database system, EPIS (Epide-miological Information System). In addition to this system, the ISID (Information System for Immunization of Children) was employed at the local level for the purpose of recording childhood vaccinations. In Slovakia, the utilisation of information technology in public health, including epidemiology, does not align with the prevailing trends in big data processing. Furthermore , the available epidemiological data are not being employed in an optimal and meaningful manner. Despite the availability of data, the utilisation of artificial intelligence (AI) in epidemiological data processing remains minimal. In the Slo-vak Republic's health system, numerous electronic registries and systems are in operation across various health organisations , including the Public Health Office SR (UVZ SR), health insurance companies, and the National Centre for Health Information (NCZI), among others. These systems are oriented towards the collection, recording, and evaluation of data and information on a range of diseases and conditions, or groups of diseases. However, it is not uncommon for data to be collected in multiple instances, resulting in potential duplication and inconsistencies. The registries are not interlinked, which precludes the possibility of reusing information that has already been collected. In the current situation, artificial intelligence appears to be an effective solution in public health and the protection of public health. It can be used to process and analyse large datasets from health registries and systems, and to produce a solution design and prognosis of the evolution. ABSTRAKT Disciplína epidemiológia sa zaoberá štúdiom výskytu a distri-búcie stavov a javov súvisiacich so zdravím v špecifikovaných populáciách. To zahŕňa skúmanie determinantov týchto javov a aplikáciu týchto poznatkov pri kontrole zdravotných problé-mov. Základnou metodikou používanou v epidemiologickom výskume je epidemiologický dohľad. Možno ho definovať ako "nepretržitý, systematický zber, analýzu a interpretáciu údajov týkajúcich sa zdravia a ich včasné rozširovanie dotknutým sub-jektom oprávneným v danej veci konať". Jedným z kľúčových cieľov systému epidemiologického dohľadu je uľahčiť rýchle využitie informácií zozbieraných na účely včasného varovania pred epidémiou, čím sa umožní účinná a rýchla kontrola pre-puknutia choroby. V tomto ohľade predstavuje monitorovanie prenosných chorôb národnú zodpovednosť v rámci zdravot-ného systému. Nevyhnutnosť rozsiahleho zberu epidemiologic-kých údajov na účely kvalitného dozoru spolu s požiadavkou na archiváciu a spracovanie uvedených údajov na analytické účely to prakticky znemožňuje bez použitia výpočtovej techniky a in-formačných technológií. V Slovenskej republike bol prvý elek-tronický register, ktorý zbieral a zaznamenával epidemiolo-gické údaje o prenosných ochoreniach (ISPO, Informačný sys-tém prenosných ochorení) zavedený v roku 1975. Od roku 1991 ho nahradil nový databázový systém EPIS (Epidemiologický informačný systém). Okrem tohto systému sa na lokálnej úrovni využíval ISID (Informačný systém pre očkovanie detí) na účely evidencie očkovania detí. Využitie informačných technológií vo verejnom zdravotníctve, vrátane epidemiológie, na Sloven-sku nezodpovedá prevládajúcim trendom v spracovaní veľkých dát. Okrem toho dostupné epidemiologické údaje sa nevyuží-vajú optimálnym a zmysluplným spôsobom. Napriek dostup-nosti údajov zostáva využitie umelej inteligencie (AI) pri spra-covaní epidemiologických údajov minimálne. V zdravotníctve Slovenskej republiky je v prevádzke množstvo elektronických registrov a systémov naprieč rôznymi zdravotníckymi organi-záciami vrátane Úradu verejného zdravotníctva SR (ÚVZ SR), zdravotných poisťovní a Národného centra zdravotníckych in-formácií (NCZI). Tieto systémy sú orientované na zber, zazna-menávanie a vyhodnocovanie údajov a informácií o celom rade chorôb a stavov alebo skupín chorôb. Nie je však nezvyčajné, Zdravotnícke listy, Ročník 12, Číslo 4, 2024 ISSN 2644-4909 LISTY REDAKCII / LETTERS TO THE EDITORS 71 že sa údaje zbierajú vo viacerých prípadoch, čo vedie k možnej duplicite a nezrovnalostiam. Registre nie sú prepojené, čo vy-lučuje možnosť opätovného použitia už zhromaždených infor-mácií. Umelá inteligencia sa v súčasnej situácii javí ako efek-tívne riešenie v oblasti verejného zdravia a ochrany verejného zdravia. Môže sa použiť na spracovanie a analýzu veľkých sú-borov údajov zo zdravotných registrov a systémov a na vytvo-renie návrhu riešenia a prognózy vývoja. Kľúčové slová: Epidemiológia. Verejné zdravotníctvo. Regis-tre. Informačné systémy. Umelá inteligencia. INTRODUCTION Epidemiology (from the Greek words 'epi' and 'demos', meaning 'on' and 'people' respectively, and 'logos', meaning 'science') is a discipline of public health that is generally defined as a medical discipline that studies the distribution of health and disease in a population for the purpose of solving health problems in that population [1]. The natural empirical progression of thought from observation to the systematic placing of one phenomenon to another, their careful recording, counting, and finally logical reasoning that places facts in such a context as to explain the causes, occurrence , and associations of the diseases under observation this is epidemiological thinking, the epidemiological approach to diseases of their occurrence and their causes, regardless of etiology [2]. The foundations of this definition were first established by Hippocrates, who emphasised the importance of observing the individual, population, contributing factors, aetiology, and the context in which diseases occur, particularly in the case of mass outbreaks. The International Epidemiological Association (IEA) presents a definition by the Cana-dian epidemiologist John M. Last, which states that "epidemiology is the medical discipline concerned with the study of the distribution and determinants, conditions and phenomena associated with health in specified populations, and also with the application of the results of this study to the control of health problems" [3, 4]. Classical epidemiology is founded upon the capacity to synthesise information and knowledge from the full spectrum of medical disciplines and non-medical specialities. The fundamental tenets of the epidemiological method are observation, descriptive analysis, data analysis, interpretation of results , design and evaluation of measures. Clinical epidemiology is the application of epidemiological principles and methods to clinical practice. The focus is on populations of patients
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... Prevalence surveys are prone to selection and information biases (Buitrago-Garcia et al., 2022). Selection bias may be present if the survey subjects were poorly representative of the source population and information bias results from the misclassification of subjects (Porta, 2016). ...
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  • Apr 2025
  • PREV VET MED
Reports of Dirofilaria immitis infection vary by location in the USA and Europe, with an occurrence gradient increasing towards the equator and warmer climates. In Australia, heartworm preventative guidelines are not climate specific, implying homogenous risk of infection across the continent. We systematically reviewed the published literature to assess if the distribution of D. immitis infection varies in Australia. We sourced 41 relevant publications by searching multiple bibliographic databases and the citations of key articles. From those, we extracted the data from a total of 106 individual surveys of variable size and quality. The reported prevalences ranged from 0.0 % to 100.0 % and we meta-analysed the observed heterogeneity using survey location’s latitude, climate zone or temperature/humidity zone. Crude heterogeneity between surveys was partly explained (approximately 30 %) by temperature/humidity zone, and the quality of the surveys did not affect the proportional explanation of heterogeneity. There was significantly higher pooled prevalence in humid summer zones (18.7 %, 95 %CI: 10.9–30.1 %) compared to cool winter zones (2.1 %, 95 %CI: 1.0–4.3 %). Historical reports of D. immitis infection in Australia concur with the strong association to warmer climates observed in other continents. The current blanket recommendation for dirofilariosis preventative usage does not reflect the important variability of infection risk to canids across locations of Australia.
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The present study aims to characterize the emergence and evolution of leprosy in Palmas, capital of the state of Tocantins, until the year 2000, when the first cases were monitored, and from 2001 to 2018, already in an environment with hyperendemicity. It is an epidemiological analysis, anchored in the systematization of publicly available secondary data, followed by a qualitative examination, both about the emergence and evolution of the endemic in that capital. In Palmas, as well as in the Tocantins, leprosy has hyper-endemic indexes. The state of Tocantins is the newest Brazilian federative unit, established, together with its capital, in 1989, when the division of the state of Goiás and the political emancipation of the former North Goiano, with its insertion in the North region of the country, where the leprosy was already a relevant health problem. Despite the few data up to 2000, rates are evident, aggravated by the flaws in the control policy and by the expressive demographic growth of Palmas, which starts to attract migrant populations from the Tocantins itself and other states of the federation, especially from the Northeast, Midwest regions and North, which had the highest leprosy rates in the country, contributing to the increase in allochthonous cases in that capital. Such facts resulted in the evolution and maintenance of the leprosy transmission chain in Palmas, conforming to the degree of endemicity of this environment, with persistent transmission since its creation, despite the therapeutic cure protocol, with public access. It is, therefore, the social production of the endemic, which persists as a serious public health problem in Palmas and Tocantins.
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The aim of this study is to reveal the economic effects of historical epidemics and pandemics, and to give an idea about the possible course of epidemic processes. Hence, epidemics, pandemics emerging since 1347 and the economic consequences of these outbreaks are tried to be presented as a literature review. The results of the research made according to historical sources are given to materialize the effects of the epidemics. It is concluded that epidemics and pandemics have caused economic recessions across the world, decreases in production, labor and productivity, and economic infrastructure problems that should be overcome. In addition, it is also concluded that epidemic diseases may recur because of pollution and destruction of vital resources such as water, air and soil, and the economy will inevitably be affected by this process.
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Sensitivity Analysis and External Adjustment for Unmeasured Confounders in Epidemiologic Database Studies of Therapeutics
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Full-text available
  • May 2006
  • PHARMACOEPIDEM DR S
Background Large health care utilization databases are frequently used to analyze unintended effects of prescription drugs and biologics. Confounders that require detailed information on clinical parameters, lifestyle, or over-the-counter medications are often not measured in such datasets, causing residual confounding bias.Objective This paper provides a systematic approach to sensitivity analyses to investigate the impact of residual confounding in pharmacoepidemiologic studies that use health care utilization databases.Methods Four basic approaches to sensitivity analysis were identified: (1) sensitivity analyses based on an array of informed assumptions; (2) analyses to identify the strength of residual confounding that would be necessary to explain an observed drug-outcome association; (3) external adjustment of a drug-outcome association given additional information on single binary confounders from survey data using algebraic solutions; (4) external adjustment considering the joint distribution of multiple confounders of any distribution from external sources of information using propensity score calibration.Conclusion Sensitivity analyses and external adjustments can improve our understanding of the effects of drugs and biologics in epidemiologic database studies. With the availability of easy-to-apply techniques, sensitivity analyses should be used more frequently, substituting qualitative discussions of residual confounding. Copyright © 2006 John Wiley & Sons, Ltd.
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Causal Inference Using Potential Outcomes
Article
  • Mar 2005
Causal effects are defined as comparisons of potential outcomes under different treatments on a common set of units. Observed values of the potential outcomes are revealed by the assignment mechanism-a probabilistic model for the treatment each unit receives as a function of covariates and potential outcomes. Fisher made tremendous contributions to causal inference through his work on the design of randomized experiments, but the potential outcomes perspective applies to other complex experiments and nonrandomized studies as well. As noted by Kempthorne in his 1976 discussion of Savage's Fisher lecture, Fisher never bridged his work on experimental design and his work on parametric modeling, a bridge that appears nearly automatic with an appropriate view of the potential outcomes framework, where the potential outcomes and covariates are given a Bayesian distribution to complete the model specification. Also, this framework crisply separates scientific inference for causal effects and decisions based on such inference, a distinction evident in Fisher's discussion of tests of significance versus tests in an accept/reject framework. But Fisher never used the potential outcomes framework, originally proposed by Neyman in the context of randomized experiments, and as a result he provided generally flawed advice concerning the use of the analysis of covariance to adjust for posttreatment concomitants in randomized trials.
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Marginal Structural Models and Causal Inference in Epidemiology
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  • Oct 2000
In observational studies with exposures or treatments that vary over time, standard approaches for adjustment of confounding are biased when there exist time-dependent confounders that are also affected by previous treatment. This paper introduces marginal structural models, a new class of causal models that allow for improved adjustment of confounding in those situations. The parameters of a marginal structural model can be consistently estimated using a new class of estimators, the inverse-probability-of-treatment weighted estimators.
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A Dictionary of Epidemiology /
Article
  • Jun 1986
2nd Ed Bibliogr. s. 139-141
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Should We Use a Case-Crossover Design?
Article
  • Feb 2000
The first decade of experience with case-crossover studies has shown that the design applies best if the exposure is intermittent, the effect on risk is immediate and transient, and the outcome is abrupt. However, this design has been used to study single changes in exposure level, gradual effects on risk, and outcomes with insidious onsets. To estimate relative risk, the exposure frequency during a window just before outcome onset is compared with exposure frequencies during control times rather than in control persons. One or more control times are supplied by each of the cases themselves, to control for confounding by constant characteristics and self-confounding between the trigger's acute and chronic effects. This review of published case-crossover studies is designed to help the reader prepare a better research proposal by understanding triggers and deterrents, target person times, alternative study bases, crossover cohorts, induction times, effect and hazard periods, exposure windows, the exposure opportunity fallacy, a general likelihood formula, and control crossover analysis.
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Ethics in epidemiology and public health I. Technical terms
Article
  • Jan 2002
Ethics in epidemiology and public health has emerged from several sources: most obvious is the discipline of bioethics, with its theories, methods, case studies, and familiar textbooks. Bioethics has primarily been focused upon medical ethics and research ethics and only recently has turned its attention to public health. Another source of scholarship is philosophical ethics. Here the sourcebooks are the writings of Aristotle, Kant, Mill, Rawls, and many others, the so called “high ground” philosophers of the past 2000 years.1 Philosophical ethics provides a rich lode from which to mine theories and concepts and to observe intellectual trends. A third source for ethics in epidemiology and public health is closer to home and is not so closely connected to bioethics nor philosophical ethics. Public health practitioners and scholars have written about the ethical problems that underlie professional practice. Advocacy, coercion, and scientific misconduct are a few representative examples, but there are many others, including privacy, conflicts of interest, and the rights of vulnerable communities. Given the scope and connectedness of these sources, a vast number of words and phrases could be included in a glossary on ethics in epidemiology and public health. To organise what could be a very long list, we identify two categories of terms. There are the more technical terms of ethics, such as casuistry, communitarian ethics, obligations, and virtues. These we define below in the first installment of the glossary. There are also more applied terms—equipoise, informed consent, privacy and the precautionary principle—representing important practical issues with significant …
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