Information

12.2: Disease and Epidemiology - Biology

12.2: Disease and Epidemiology - Biology


We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

12.2: Disease and Epidemiology

Lesson 1: Introduction to Epidemiology

Students of journalism are taught that a good news story, whether it be about a bank robbery, dramatic rescue, or presidential candidate&rsquos speech, must include the 5 W&rsquos: what, who, where, when and why (sometimes cited as why/how). The 5 W&rsquos are the essential components of a news story because if any of the five are missing, the story is incomplete.

The same is true in characterizing epidemiologic events, whether it be an outbreak of norovirus among cruise ship passengers or the use of mammograms to detect early breast cancer. The difference is that epidemiologists tend to use synonyms for the 5 W&rsquos: diagnosis or health event (what), person (who), place (where), time (when), and causes, risk factors, and modes of transmission (why/how).

The word epidemiology comes from the Greek words epi, meaning on or upon, demos, meaning people, and logos, meaning the study of. In other words, the word epidemiology has its roots in the study of what befalls a population. Many definitions have been proposed, but the following definition captures the underlying principles and public health spirit of epidemiology:

Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems (1).

Key terms in this definition reflect some of the important principles of epidemiology.

Study

Epidemiology is a scientific discipline with sound methods of scientific inquiry at its foundation. Epidemiology is data-driven and relies on a systematic and unbiased approach to the collection, analysis, and interpretation of data. Basic epidemiologic methods tend to rely on careful observation and use of valid comparison groups to assess whether what was observed, such as the number of cases of disease in a particular area during a particular time period or the frequency of an exposure among persons with disease, differs from what might be expected. However, epidemiology also draws on methods from other scientific fields, including biostatistics and informatics, with biologic, economic, social, and behavioral sciences.

In fact, epidemiology is often described as the basic science of public health, and for good reason. First, epidemiology is a quantitative discipline that relies on a working knowledge of probability, statistics, and sound research methods. Second, epidemiology is a method of causal reasoning based on developing and testing hypotheses grounded in such scientific fields as biology, behavioral sciences, physics, and ergonomics to explain health-related behaviors, states, and events. However, epidemiology is not just a research activity but an integral component of public health, providing the foundation for directing practical and appropriate public health action based on this science and causal reasoning.(2)

Distribution

Epidemiology is concerned with the frequency and pattern of health events in a population:

Frequency refers not only to the number of health events such as the number of cases of meningitis or diabetes in a population, but also to the relationship of that number to the size of the population. The resulting rate allows epidemiologists to compare disease occurrence across different populations.

Pattern refers to the occurrence of health-related events by time, place, and person. Time patterns may be annual, seasonal, weekly, daily, hourly, weekday versus weekend, or any other breakdown of time that may influence disease or injury occurrence. Place patterns include geographic variation, urban/rural differences, and location of work sites or schools. Personal characteristics include demographic factors which may be related to risk of illness, injury, or disability such as age, sex, marital status, and socioeconomic status, as well as behaviors and environmental exposures.

Characterizing health events by time, place, and person are activities of descriptive epidemiology, discussed in more detail later in this lesson.

Determinants

Determinant: any factor, whether event, characteristic, or other definable entity, that brings about a change in a health condition or other defined characteristic.

Epidemiology is also used to search for determinants, which are the causes and other factors that influence the occurrence of disease and other health-related events. Epidemiologists assume that illness does not occur randomly in a population, but happens only when the right accumulation of risk factors or determinants exists in an individual. To search for these determinants, epidemiologists use analytic epidemiology or epidemiologic studies to provide the &ldquoWhy&rdquo and &ldquoHow&rdquo of such events. They assess whether groups with different rates of disease differ in their demographic characteristics, genetic or immunologic make-up, behaviors, environmental exposures, or other so-called potential risk factors. Ideally, the findings provide sufficient evidence to direct prompt and effective public health control and prevention measures.

Health-related states or events

Epidemiology was originally focused exclusively on epidemics of communicable diseases (3) but was subsequently expanded to address endemic communicable diseases and non-communicable infectious diseases. By the middle of the 20th Century, additional epidemiologic methods had been developed and applied to chronic diseases, injuries, birth defects, maternal-child health, occupational health, and environmental health. Then epidemiologists began to look at behaviors related to health and well-being, such as amount of exercise and seat belt use. Now, with the recent explosion in molecular methods, epidemiologists can make important strides in examining genetic markers of disease risk. Indeed, the term health-related states or events may be seen as anything that affects the well-being of a population. Nonetheless, many epidemiologists still use the term &ldquodisease&rdquo as shorthand for the wide range of health-related states and events that are studied.

Specified populations

Although epidemiologists and direct health-care providers (clinicians) are both concerned with occurrence and control of disease, they differ greatly in how they view &ldquothe patient.&rdquo The clinician is concerned about the health of an individual the epidemiologist is concerned about the collective health of the people in a community or population. In other words, the clinician&rsquos &ldquopatient&rdquo is the individual the epidemiologist&rsquos &ldquopatient&rdquo is the community. Therefore, the clinician and the epidemiologist have different responsibilities when faced with a person with illness. For example, when a patient with diarrheal disease presents, both are interested in establishing the correct diagnosis. However, while the clinician usually focuses on treating and caring for the individual, the epidemiologist focuses on identifying the exposure or source that caused the illness the number of other persons who may have been similarly exposed the potential for further spread in the community and interventions to prevent additional cases or recurrences.

Application

Epidemiology is not just &ldquothe study of&rdquo health in a population it also involves applying the knowledge gained by the studies to community-based practice. Like the practice of medicine, the practice of epidemiology is both a science and an art. To make the proper diagnosis and prescribe appropriate treatment for a patient, the clinician combines medical (scientific) knowledge with experience, clinical judgment, and understanding of the patient. Similarly, the epidemiologist uses the scientific methods of descriptive and analytic epidemiology as well as experience, epidemiologic judgment, and understanding of local conditions in &ldquodiagnosing&rdquo the health of a community and proposing appropriate, practical, and acceptable public health interventions to control and prevent disease in the community.

Summary

Epidemiology is the study (scientific, systematic, data-driven) of the distribution (frequency, pattern) and determinants (causes, risk factors) of health-related states and events (not just diseases) in specified populations (patient is community, individuals viewed collectively), and the application of (since epidemiology is a discipline within public health) this study to the control of health problems.

Exercise 1.1

Below are three key terms taken from the definition of epidemiology, followed by a list of activities that an epidemiologist might perform. Match the term to the activity that best describes it. You should match only one term per activity.


A metabolomic profile is associated with the risk of incident coronary heart disease

Background: Metabolomics, defined as the comprehensive identification and quantification of low-molecular-weight metabolites to be found in a biological sample, has been put forward as a potential tool for classifying individuals according to their risk of coronary heart disease (CHD). Here, we investigated whether a single-point blood measurement of the metabolome is associated with and predictive for the risk of CHD.

Methods and results: We obtained proton nuclear magnetic resonance spectra in 79 cases who developed CHD during follow-up (median 8.1 years) and in 565 randomly selected individuals. In these spectra, 100 signals representing 36 metabolites were identified. Applying least absolute shrinkage and selection operator regression, we defined a weighted metabolite score consisting of 13 proton nuclear magnetic resonance signals that optimally predicted CHD. This metabolite score, including signals representing a lipid fraction, glucose, valine, ornithine, glutamate, creatinine, glycoproteins, citrate, and 1.5-anhydrosorbitol, was associated with the incidence of CHD independent of traditional risk factors (TRFs) (hazard ratio 1.50, 95% CI 1.12-2.01). Predictive performance of this metabolite score on its own was moderate (C-index 0.75, 95% CI 0.70-0.80), but after adding age and sex, the C-index was only modestly lower than that of TRFs (C-index 0.81, 95% CI 0.77-0.85 and C-index 0.82, 95% CI 0.78-0.87, respectively). The metabolite score was also associated with prevalent CHD independent of TRFs (odds ratio 1.59, 95% CI 1.19-2.13).

Conclusion: A metabolite score derived from a single-point metabolome measurement is associated with CHD, and metabolomics may be a promising tool for refining and improving the prediction of CHD.


12.2: Disease and Epidemiology - Biology

Principles of Disease and Epidemiology

Epidemiology is the study of the frequency, distribution and causes of diseases in a given population.

  • Infection: the growth of a pathogen in a host organism. Infection depends on exposure to the pathogen and host susceptibility.
  • Disease: the response by a host to an infection, which when bad evokes a recognizable pattern of clinical symptoms.
  • Incidence is the number of new cases divided by time.
  • Incidence rate is the number of new cases divided by the total population at risk.
  • Prevalence is the number of cases existing at any moment in time.
  • Prevalence rat is the number of cases divided by the total population at risk.
  • Etiology: study of disease causing pathogen.
  • Symbiosis: interactive relationship between two species.
  • Residents: colonizing microbes.
  • Transients: temporary microbes.
  • Opportunists: normal flora which become pathogenic under certain circumstances.
  • Pathogens: disease causing microbes.
  • Immuno compromised: a organism with a weakened immunity.
  • Commensalism: the interaction of two organisms in which one benefits and the other is neither harmed nor helped by the interaction.
  • Mutualism: relationship where both the host and microbe are metabolically dependent on each other e.g. lichen have a symbiotic association with a fungus.
  • Parasitism: the interaction of two (or more) organisms where one is benefited and the other harmed by the relationship.
  • Disease Severity: Acute: short duration, Chronic: lasts for a longer time period, Sub-acute: duration between acute and chronic, Latent: causative agent lies dormant within the body and suddenly become active resulting in disease.
  • Reservoir: Also known as an asymptomatic infection carrier it is an organisms that carries and spreads the pathogen but is unharmed itself.
  • Descriptive Epidemiology
  • Analytical Epidemiology
  • Retrospective Epidemiology
  • Prospective epidemiology
  • Experimental Epidemiology
  • Serological Epidemiology

Application of Epidemiology

  • Tracking of health problems occurring in a community.
  • Establish the clinical picture of the disease or health problem in a community.
  • Estimating risk of specific diseases or syndromes.
  • Identify syndromes, precursors and treatments for diseases.
  • Investigate epidemiology of unknown etiology.
  • Establish the history of a disease in a defined population.

Koch’s Postulates & Exceptions

  • Pathogen must be present in every instance of disease.
  • Pathogen must be grown in pure culture.
  • Pathogen must be capable of being re-isolated from an inoculated animal expressing the disease.
  • Exception: Some bacteria and viruses cannot be grown in the laboratory.
  • Exception: Some diseases are caused by several microbes.
  • Exception: Some pathogens are responsible for causing different diseases.
  • Exception: Some pathogens can not be grown in animals and exist only in humans.
  • Sporadic: Few cases
  • Endemic: Cases in a local region or area.
  • Epidemic: Wide spread outbreak of a disease in excess of what is normally expected. disease like syndrome.
  • Pandemic: Spreading throughout the globe.
  • Disease is an interaction between a Host, Pathogen (agent of infection) and Environment.
  • Classification of Disease: Communicable Diseases, Contagious Diseases and non-Communicable Diseases.
  • Stages of Disease Development:
    • Incubation period: pathogen is multiplying.
    • Prodromal period: symptoms being to appear
    • Illness: visible signs of disease.
    • Period of decline: pathogen is under control
    • Period of convalescence: patient begins to recover.

    Iceberg Concept of Infection

    • Cell Response: Exposure no cell entry®Incomplete viral maturation®Cell transformation®Cytophatic effect®Fatal
    • Host Response: Exposure but no infections®Infections with no clinical illness®Mild illness®Severe disease®Fatal
    • Mechanisms of Transmission : Aerosolizing, touch, insect bite, animal bite fomites.
    • Ecological factors of infections : altered environment, changes in food production, deforestation, global warming, increased use of antibiotics and bacteria in the air.

    Factors Influencing Outbreaks and Disease Spread

    • Factors effecting outbreak: presence of an infected host, adequate number of potential hosts and an effective methods of transmission by contact.
    • Factors affecting spread: stability of virus within it’s the environment, number of virion particles releases, virulence and invasiveness of pathogen, availability of proper vector or medium for spread.
    • Can be residents or transients. Resident population remains constant and prevents invagination by pathogens and raises overall immunity. Residents can in rare situations become opportunists and cause infections. Transient population number varies.
    • In the body normal biota can inhabit: skin, respiratory tract, intestine, mouth, nose, throat and vagina.
    • Benefits of Normal Flora include: resistance to some pathogens, release of bacteriocins and colicins, production of vitamin K, continued antigenic stimulation from commensals.
    • Disadvantages of Normal Flora: commensal bacteria may cause localized infections, can become pathogenic if they acquire virulence factors or are introduced to sterile sties, contribute to body odor.

    The body has millions of microorganism that are part of the normal flora. Normal flora and the human body are in a relationship known as symbiosis. Symbiosis is a situation were both organisms benefit from the relationship. Normal flora is typically classified as either: resident, transients or opportunistic. Opportunists cause disease when the “opportunity” becomes available.

    Epidemiology is the study of the distribution, frequency and determinants that result in disease. It is important for the prediction of future disease, its impact and duration.

    • Significance and impact of natural microbiota are described.
    • The Iceberg concept of infection is presented.
    • Koch’s postulates are described.
    • Organ systems involved in preventing infections are examined.
    • Epidemiology as a concept, its tools and significance are outlined.
    • Concept map showing inter-connections of concepts.
    • Definition slides of important terms are introduced.
    • Examples given throughout to illustrate how the concepts apply.
    • A concise summary is given at the conclusion of the tutorial.

    Natural microbiota inhabit the body in a symbiotic relationships.
    Disease patterns, progression and predisposing factors.
    The Iceberg concept of infection is presented.
    Koch’s postulates are described.
    Symbiosis and the impact that it has on the body and its natural biota are examined.
    Both the harmful and beneficial role of microbes are detailed.
    Important terms in epidemiology are defined.

    See all 24 lessons in Anatomy and Physiology, including concept tutorials, problem drills and cheat sheets: Teach Yourself Microbiology Visually in 24 Hours


    Molecular Tools and Infectious Disease Epidemiology

    Molecular Tools and Infectious Disease Epidemiology examines the opportunities and methodologic challenges in the application of modern molecular genetic and biologic techniques to infectious disease epidemiology.

    The application of these techniques dramatically improves the measurement of disease and putative risk factors, increasing our ability to detect and track outbreaks, identify risk factors and detect new infectious agents. However, integration of these techniques into epidemiologic studies also poses new challenges in the design, conduct, and analysis. This book presents the key points of consideration when integrating molecular biology and epidemiology discusses how using molecular tools in epidemiologic research affects program design and conduct considers the ethical concerns that arise in molecular epidemiologic studies and provides a context for understanding and interpreting scientific literature as a foundation for subsequent practical experience in the laboratory and in the field.

    The book is recommended for graduate and advanced undergraduate students studying infectious disease epidemiology and molecular epidemiology and for the epidemiologist wishing to integrate molecular techniques into his or her studies.

    Molecular Tools and Infectious Disease Epidemiology examines the opportunities and methodologic challenges in the application of modern molecular genetic and biologic techniques to infectious disease epidemiology.

    The application of these techniques dramatically improves the measurement of disease and putative risk factors, increasing our ability to detect and track outbreaks, identify risk factors and detect new infectious agents. However, integration of these techniques into epidemiologic studies also poses new challenges in the design, conduct, and analysis. This book presents the key points of consideration when integrating molecular biology and epidemiology discusses how using molecular tools in epidemiologic research affects program design and conduct considers the ethical concerns that arise in molecular epidemiologic studies and provides a context for understanding and interpreting scientific literature as a foundation for subsequent practical experience in the laboratory and in the field.

    The book is recommended for graduate and advanced undergraduate students studying infectious disease epidemiology and molecular epidemiology and for the epidemiologist wishing to integrate molecular techniques into his or her studies.


    Abstract

    Despite long-standing vaccination programs, substantial increases in reported cases of pertussis have been described in several countries during the last 5 years. Cases among very young infants who are at greatest risk of pertussis-related hospitalizations and mortality are the most alarming. Multiple hypotheses including but not limited to the availability of more sensitive diagnostic tests, greater awareness, and waning vaccine-induced immunity over time have been posited for the current challenges with pertussis. The conference “Pertussis: biology, epidemiology and prevention” held in Annecy-France (November 11–13, 2015) brought together experts and interested individuals to examine these issues and to formulate recommendations for optimal use of current vaccines, with a particular focus on strategies to minimize severe morbidity and mortality among infants during the first months of life. The expert panel concluded that improving vaccination strategies with current vaccines and development of new highly immunogenic and efficacious pertussis vaccines that have acceptable adverse event profiles are currently the two main areas of investigation for the control of pertussis. Some possible pathways forward to address these main challenges are discussed in this report.


    Epidemiology of low-proteinuric chronic kidney disease in renal clinics

    CKD patients with low-grade proteinuria (LP) are common in nephrology clinics. However, prevalence, characteristics, and the competing risks of ESRD and death as the specific determinants, are still unknown. We analyzed epidemiological features of LP status in a prospective cohort of 2,340 patients with CKD stage III-V referred from ≥6 months in 40 nephrology clinics in Italy. LP status was defined as proteinuria <0.5 g/24h according to current KDIGO guidelines. Patients with higher proteinuria constituted the control group (CON). LP patients were 54.5% of the whole cohort. As compared to CON, LP were older (70.0±12.1 vs 65.4±14.1 y), and less likely to be male (55.8 vs 62.0%) and diabetic (27.6 vs 34.1%), and had hypertension as the most common cause of CKD (39.8%). They had higher eGFR (34.8±13.5 vs 26.8±13.2 mL/min/1.73m2) and hemoglobin (12.7±1.7 vs 12.3±1.7 g/dL), while systolic blood pressure (137±18 vs 140±18 mmHg) and serum phosphorus (3.7±0.8 vs 3.9±0.8 mg/dL) were lower [P<0.001 for all comparisons]. Over a median follow-up of 48 months, an inverse relative risk of ESRD and death was observed in LP (death>>ESRD P = 0.002) versus CON (ESRD>>death P<0.0001). Modifiable risk factors were also different in LP, with smoking, lower hemoglobin, and proteinuria being associated with higher mortality risk while lower BMI and higher phosphorus predicting ESRD at multivariable Cox analyses [P<0.05 for all]. Therefore, in nephrology clinics, LP patients are the majority and show distinctive basal features. More important, they are more exposed to death than ESRD and do present specific modifiable determinants of either outcome indeed, in LP, while smoking plays a role for mortality, lower BMI and higher phosphorus levels -even if in the normal range- are predictors of ESRD. These data support the need to further study the low proteinuric CKD population to guide management.

    Conflict of interest statement

    Competing Interests: The authors have declared that no competing interests exist.

    Figures

    Fig 1. Flow chart of the study.

    Fig 1. Flow chart of the study.

    Fig 2. Cumulative incidence probability of ESRD…

    Fig 2. Cumulative incidence probability of ESRD and all-cause death before ESRD, by competing risk…

    Fig 3. Cumulative incidence probability of ESRD…

    Fig 3. Cumulative incidence probability of ESRD and all-cause death before ESRD, by competing risk…

    Fig 4. Adjusted hazard ratios (solid line)…

    Fig 4. Adjusted hazard ratios (solid line) and 95% confidence intervals (dashed lines) of one-unit…


    12.2: Disease and Epidemiology - Biology

    Supported in part by National Institute of Arthritis and Musculoskeletal and Skin Diseases grants K24AR064310 (Dr Gelfand), T32AR00746532 (Ms Grewal), K23AR063764 (Dr Ogdie), and K23AR068433 (Dr Takeshita), a Dermatology Foundation Career Development Award (Dr Takeshita), the Intramural Research Program at the National Institutes of Health grant ZIAHL006193-02 (Mehta), and a National Institute for Health Research Clinician Scientist Fellowship (grant NIHR/CS/010/014 to Dr Langan). The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the UK Department of Health.

    Dr Takeshita has received a research grant (to the Trustees of the University of Pennsylvania) from Pfizer Inc and payment for continuing medical education work related to psoriasis. Dr Mehta is a full-time employee of the US Government. Dr Ogdie receives research grants from AbbVie (to the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis [GRAPPA]), Celgene (to GRAPPA), and Pfizer Inc (to the Trustees of the University of Pennsylvania and GRAPPA), and has served as a consultant for Novartis, receiving honoraria. Dr Van Voorhees has served as a consultant for AbbVie, Amgen, Aqua, AstraZeneca, Celgene, Corrona, Dermira, Janssen, Leo, Novartis, and Pfizer, receiving honoraria received a research grant from AbbVie and has other relationship with Merck. Dr Gelfand has served as a consultant for AbbVie, AstraZeneca, Celgene Corp, Coherus, Eli Lilly, Janssen Biologics (formerly Centocor), Sanofi, Merck, Novartis Corp, Endo, and Pfizer Inc, receiving honoraria receives research grants (to the Trustees of the University of Pennsylvania) from AbbVie, Amgen, Eli Lilly, Janssen, Novartis Corp, Regeneron, and Pfizer Inc and received payment for continuing medical education work related to psoriasis. Dr Gelfand is a co–patent holder of resiquimod for treatment of cutaneous T-cell lymphoma. No other potential conflicts of interest were declared by the authors.


    Disaster Epidemiology

    Disaster epidemiology assesses the short- and long-term adverse health effects of disasters to help guide emergency response and recovery efforts and predict consequences of future disasters. It provides situational awareness that is, information that helps us understand what the needs are, plan the response, and gather the appropriate resources. The main objectives of disaster epidemiology are to

    • prevent or reduce the number of deaths, illnesses, and injuries caused by disasters,
    • provide timely and accurate health information for decision-makers,
    • improve prevention and mitigation strategies for future disasters by collecting information for future response preparation.

    NCEH provides expertise in morbidity and mortality surveillance, rapid needs assessments such as the Community Assessment for Public Health Emergency Response (CASPER), and disaster epidemiologic studies. For more information on disaster epidemiology and response, see the Frequently Asked Questions (FAQS).

    This short eLearning provides an overview of disaster epidemiology including the potential public health impacts of disasters, difference between direct and indirect effects of a disaster, and the role of a disaster epidemiologist.

    During a disaster, it is important to conduct morbidity and mortality surveillance to determine the extent and scope of the health effects on the affected populations. Surveillance is the systematic collection, analysis, and interpretation of death, injury, and illness data that enables public health to identify adverse health effects in the community. It allows us to assess the human health impacts of a disaster and evaluate potential problems related to planning and prevention.

    The Community Assessment for Public Health Emergency Response (CASPER) is a type of rapid needs assessment (RNA) designed to provide public health leaders and emergency managers with household-based information about a community. It is quick, reliable, relatively inexpensive, and flexible. CASPER uses valid statistical methods to gather information and can be conducted throughout the disaster cycle (preparedness, response, recovery, mitigation) and in non-disaster situations. The information generated can be used to initiate public health action identify information gaps facilitate disaster planning, response, and recovery activities allocate resources and assess new or changing needs in the community.

    Public health disaster studies helps identify associations between disaster-related exposures and mortality or morbidity. It can also help evaluate specific programs or response techniques to yield decisions and assess the successfulness of the program or response. NCEH conducts epidemiologic studies and research on various disaster-related topics. Our SMEs also provide technical assistance to partners in conducting their own research.


    Twitter

    Neil McRoberts:
    RT @EnvPolicyCenter: Social sciences are the hard sciences. Prediction and explanation in social systems https://t.co/2hLFllCl9l Posted 5 days ago Neil McRoberts:
    @rlmcelreath Rachel licking her lips at the thought of specifying the prior for our next decision problem https://t.co/VnpnRil3L1 Posted 7 days ago
    The Long Narrow Swale: Thoughts on interdisciplinary research
    The Rumsfeld filter

    It is well over a year since the first post on this blog. I had intended it to be monthly or maybe happen once every two months. Ah well, most of the time that I wasn't spending writing blogs I was sciencing, so I'll let myself off the.


    Watch the video: Microbiology and Epidemiology of Infectious Disease (May 2022).