This document provides an introduction to epidemiology. It defines epidemiology as the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to control health problems. It discusses key epidemiological concepts such as disease frequency, distribution, and determinants. It also covers epidemiological study designs, measures of disease occurrence such as rates, ratios and proportions, and how epidemiology compares groups to identify risk factors and test hypotheses about disease causation.
Epidemiology lecture 2 measuring disease frequencyINAAMUL HAQ
This document discusses measuring disease frequency in epidemiology. It defines key terms like incidence, prevalence, population at risk, and rates. Incidence refers to new cases in a specified time period, while prevalence looks at total current cases. Prevalence can be point prevalence (at a point in time), period prevalence (over a specified time period), or lifetime prevalence. The document provides examples of calculating prevalence from population data and discusses how prevalence is used to understand disease burden and plan health services.
This document discusses epidemiology, which is the study of the distribution and determinants of health and disease in populations. It covers the components, characteristics, and types of epidemiology studies. Descriptive epidemiology involves studying disease distribution by person, place, and time variables. Analytic epidemiology uses epidemiologic methods to explain disease occurrence and identify causal mechanisms. Key topics include descriptive variables, temporal variations, community diagnosis, epidemics, and determination of disease etiology through descriptive and analytical studies.
This document discusses various measures used to quantify disease frequency in epidemiology. It describes measures of morbidity including incidence, prevalence, and disability rates. Incidence measures new cases over time while prevalence measures total current cases. Disability rates quantify limitations in activities. Measures of mortality are also presented, such as crude death rate, case fatality rate, and standardized mortality ratio. Standardization adjusts for differences in population characteristics to allow valid comparisons. Overall, the document provides an overview of key epidemiological metrics for quantifying disease burden and guiding public health efforts.
Introduction to epidemiology and it's measurementswrigveda
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in specified populations. It has three main components - distribution, determinants, and frequency. Measurement of disease frequency involves quantifying disease occurrence and is a prerequisite for epidemiological investigation. Rates, ratios, and proportions are key tools used to measure disease frequency and distribution. Incidence rates measure new cases over time while prevalence rates measure existing cases. These measurements are essential for describing disease patterns, formulating hypotheses, and evaluating prevention programs.
Epidemiology is the study and analysis of the patterns, causes, and effects of health and disease conditions in defined populations. It is the cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences
Descriptive epidemiology is the first phase of epidemiological investigation which aims to observe disease distribution in a population and identify characteristics associated with disease. It involves defining the population and disease, describing disease occurrence by time, place and person, measuring disease burden, comparing data to indices, and formulating hypotheses about potential causes. Key aspects include examining time trends, geographical variation, and characteristics of individuals with disease like age and sex. The goal is to understand basic features of a health problem and generate ideas about causal factors.
This lecture introduces epidemiology by discussing its importance through achievements like smallpox eradication. It defines epidemiology as the study of health-related states in populations to prevent and control health problems. The lecture describes John Snow's contribution by showing cholera is spread through contaminated water before germ theory. It outlines the epidemiological approach as asking questions to make comparisons, and aims of epidemiology as describing disease distribution, identifying causes, and providing data for prevention planning.
Attributable risk and population attributable riskAbino David
This document defines risk factors and describes methods for identifying and quantifying risk. It defines a risk factor as an attribute or exposure associated with disease development. Epidemiological studies help identify risk factors and estimate degree of risk. Relative risk compares incidence between exposed and unexposed groups, while attributable risk indicates how much disease can be attributed to exposure by comparing incidence rates. Two examples are given to illustrate these concepts and how attributable risk informs potential public health interventions.
Epidemiology lecture 2 measuring disease frequencyINAAMUL HAQ
This document discusses measuring disease frequency in epidemiology. It defines key terms like incidence, prevalence, population at risk, and rates. Incidence refers to new cases in a specified time period, while prevalence looks at total current cases. Prevalence can be point prevalence (at a point in time), period prevalence (over a specified time period), or lifetime prevalence. The document provides examples of calculating prevalence from population data and discusses how prevalence is used to understand disease burden and plan health services.
This document discusses epidemiology, which is the study of the distribution and determinants of health and disease in populations. It covers the components, characteristics, and types of epidemiology studies. Descriptive epidemiology involves studying disease distribution by person, place, and time variables. Analytic epidemiology uses epidemiologic methods to explain disease occurrence and identify causal mechanisms. Key topics include descriptive variables, temporal variations, community diagnosis, epidemics, and determination of disease etiology through descriptive and analytical studies.
This document discusses various measures used to quantify disease frequency in epidemiology. It describes measures of morbidity including incidence, prevalence, and disability rates. Incidence measures new cases over time while prevalence measures total current cases. Disability rates quantify limitations in activities. Measures of mortality are also presented, such as crude death rate, case fatality rate, and standardized mortality ratio. Standardization adjusts for differences in population characteristics to allow valid comparisons. Overall, the document provides an overview of key epidemiological metrics for quantifying disease burden and guiding public health efforts.
Introduction to epidemiology and it's measurementswrigveda
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in specified populations. It has three main components - distribution, determinants, and frequency. Measurement of disease frequency involves quantifying disease occurrence and is a prerequisite for epidemiological investigation. Rates, ratios, and proportions are key tools used to measure disease frequency and distribution. Incidence rates measure new cases over time while prevalence rates measure existing cases. These measurements are essential for describing disease patterns, formulating hypotheses, and evaluating prevention programs.
Epidemiology is the study and analysis of the patterns, causes, and effects of health and disease conditions in defined populations. It is the cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences
Descriptive epidemiology is the first phase of epidemiological investigation which aims to observe disease distribution in a population and identify characteristics associated with disease. It involves defining the population and disease, describing disease occurrence by time, place and person, measuring disease burden, comparing data to indices, and formulating hypotheses about potential causes. Key aspects include examining time trends, geographical variation, and characteristics of individuals with disease like age and sex. The goal is to understand basic features of a health problem and generate ideas about causal factors.
This lecture introduces epidemiology by discussing its importance through achievements like smallpox eradication. It defines epidemiology as the study of health-related states in populations to prevent and control health problems. The lecture describes John Snow's contribution by showing cholera is spread through contaminated water before germ theory. It outlines the epidemiological approach as asking questions to make comparisons, and aims of epidemiology as describing disease distribution, identifying causes, and providing data for prevention planning.
Attributable risk and population attributable riskAbino David
This document defines risk factors and describes methods for identifying and quantifying risk. It defines a risk factor as an attribute or exposure associated with disease development. Epidemiological studies help identify risk factors and estimate degree of risk. Relative risk compares incidence between exposed and unexposed groups, while attributable risk indicates how much disease can be attributed to exposure by comparing incidence rates. Two examples are given to illustrate these concepts and how attributable risk informs potential public health interventions.
This document provides an introduction to the basic concepts of epidemiology. It defines epidemiology as the study of patterns, causes, and effects of health and disease conditions in populations. The aims of epidemiology are to describe disease distribution and frequency, identify risk factors, and provide data to prevent and control diseases. Epidemiologists make comparisons between groups with and without disease exposure to identify determinants and test hypotheses. Basic measurements in epidemiology include mortality, morbidity, disability, and the distribution of disease and risk factors. Rates, ratios, and proportions are key tools used to measure and express disease frequency in populations.
This document provides an introduction to biostatistics and key concepts. It defines biostatistics as the development and application of statistical techniques to scientific research relating to human life and health. Some key terms discussed include:
- Population, which is the totality of individuals of interest
- Sample, which is a subset of a population
- Variables, which can be qualitative (non-numerical) or quantitative (numerical)
- Levels of measurement for variables, including nominal, ordinal, interval, and ratio scales
- Descriptive methods for qualitative data, including frequency distributions
Biostatistics plays an important role in modern medicine, including determining disease burden, finding new drug treatments, planning resource allocation, and measuring
This document provides a history of epidemiology, covering its origins and key figures. It traces epidemiology back to ancient Greece and discusses its modern definition as the study of disease distribution and determinants in populations. Some important developments include John Graunt establishing demographic analysis in the 1600s, James Lind identifying citrus as preventing scurvy in 1747, Edward Jenner developing vaccination against smallpox in 1796, Ignaz Semmelweis reducing childbed fever mortality via handwashing in 1847, and John Snow linking cholera to contaminated water in 1854. These pioneers helped establish epidemiology's objectives of identifying disease causes and evaluating preventive measures.
Screening tests aim to identify unrecognized disease in apparently healthy individuals. They differ from diagnostic tests in that they are applied to groups rather than individuals, use a single criterion, and are less accurate. Validity refers to a test's accuracy while reliability is its precision on repeat tests. Sensitivity measures a test's ability to identify true positives, and specificity measures its ability to identify true negatives. Screening programs must consider factors like disease burden, test characteristics, and whether early detection improves outcomes.
This document discusses different types of error and bias that can occur in epidemiological studies. It defines random error as occurring due to chance and resulting in imprecise measures, while systematic error or bias results in invalid measures that are not true. Types of bias discussed include selection bias, information bias, and confounding. Selection bias can arise from how cases and controls are selected, while information bias occurs when exposure or disease status is incorrectly classified. The document emphasizes the importance of reducing both random and systematic errors to obtain valid study results.
Standardization is a process used to make rates such as mortality rates comparable between populations with different age distributions. There are two main methods: direct standardization which applies the age-specific rates of the populations to a standard population, and indirect standardization which calculates a standardized mortality ratio by taking the ratio of observed to expected deaths based on a standard population's rates. Standardization allows unbiased comparison of health outcomes between groups after removing the effect of differences in age composition.
The 10-step approach to outbreak investigations involves:
1) Identifying an investigation team and resources.
2) Establishing the existence of an outbreak.
3) Verifying the diagnosis, constructing a case definition, and finding cases systematically.
Descriptive epidemiology is then used to develop hypotheses, which are evaluated through additional studies if needed, before implementing control measures, communicating findings, and maintaining surveillance to confirm the outbreak has ended. Being systematic and following these steps is key to determining the source and controlling outbreaks.
Here are the key points to compare the different research methods:
Cross-sectional study:
- Advantages: Quick, easy, low cost, can study multiple factors at once
- Disadvantages: Cannot determine temporal sequence, prone to biases
- Requirements: Representative sample, standardized data collection
Case-control study:
- Advantages: Efficient to study rare diseases, can study multiple exposures
- Disadvantages: Prone to selection and recall biases, uncertain temporal sequence
- Requirements: Clear case definition, appropriate controls matched to cases
Cohort study:
- Advantages: Directly measures risk, establishes temporal sequence
- Disadvantages: Expensive, long follow up needed
Standardization of rates by Dr. Basil TumainiBasil Tumaini
Standardization of rates by Dr. Basil Tumaini, presented during the residency at Muhimbili University of Health and Allied Sciences, Epidemiology class
1. Effect modification and confounding are two aspects to consider when examining the relationship between an exposure and outcome. Effect modification provides useful information about how a third variable impacts the relationship, while confounding can distort the observed effect.
2. Stratifying the data and calculating stratum-specific odds ratios is a way to check for effect modification and confounding. Effect modification is present if the odds ratios differ substantially between strata. Confounding is present if the crude odds ratio differs from the stratified odds ratios.
3. It is important to measure potential confounding factors so they can be controlled for through stratification or multivariate analysis. This prevents confounding from distorting the observed effect between the exposure and outcome.
As per John M. Last (1988) 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.
This document discusses epidemiological methods for studying the distribution and determinants of health events and applying that knowledge to disease control. It defines descriptive epidemiology as the study of disease occurrence, distribution, and patterns in populations. Descriptive methods are observational and can be cross-sectional or longitudinal. Descriptive epidemiology provides insights into disease frequency, trends, and risk factors to inform public health planning and resource allocation.
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in populations and the application of this study to control health problems. It uses a systematic and unbiased approach to collect, analyze, and interpret data. Some core functions of epidemiology include public health surveillance, field investigations, analytic studies, evaluation of public health programs and services, linkages with other disciplines, and policy development. Epidemiology provides an evidence base for effective public health action and disease prevention.
This document provides an outline for a lesson on measures of association in epidemiology. It begins with introducing the key concepts of association versus causation and how measures of association are used to quantify the strength and direction of relationships between exposures and outcomes. It then discusses the different scales that measures can be calculated on, including relative and absolute scales. Examples of specific relative measures like risk ratio, prevalence ratio, and odds ratio are provided. Absolute measures like attributable risk and population attributable risk are also introduced. The document aims to explain the appropriate interpretation and calculation of various epidemiologic measures of association.
This document discusses hospital outbreak investigations. It defines endemic and epidemic infections in hospitals. Common source and propagated epidemics are described. Steps in investigating outbreaks in hospitals and communities are provided, including forming an investigation team, developing a case definition, conducting epidemiological and laboratory analyses. The goals of outbreak investigations are outlined. Methods for confirming and controlling outbreaks are discussed.
Experimental study in epidemiology methods pptanjalatchi
Experimental epidemiology involves manipulating study factors and conditions to test interventions and their effects on disease. There are two main types: randomized controlled trials (RCTs) and non-randomized trials. RCTs randomly assign subjects to treatment and control groups to reduce bias when testing new interventions. They involve developing a study protocol, selecting and randomizing populations, implementing interventions, follow-up, and assessing outcomes. Non-randomized trials do not randomly assign subjects and are used when RCTs are not possible, such as when interventions apply to groups. Examples include uncontrolled trials with no comparison and natural experiments that mimic real-world circumstances. Experimental epidemiology aims to identify disease causes and evaluate prevention and treatment effectiveness.
This document provides an overview of epidemiological studies and different study designs. It begins by defining epidemiology as the study of disease distribution and determinants in human populations. The major goal of epidemiologic research is to explain patterns of disease occurrence and causation.
It then describes qualitative and quantitative research approaches. For quantitative studies, it distinguishes between descriptive and analytical designs. Descriptive studies summarize disease patterns by time, place and person to generate hypotheses, while analytical studies aim to establish causal links between exposures and outcomes.
The document outlines different epidemiological study designs including experimental, observational, and quasi-experimental designs. It provides examples of randomized controlled trials, cohort studies, case-control studies and other designs, discussing their
This document discusses public health surveillance. It begins by defining surveillance and its main components, which include the ongoing collection and analysis of health data to facilitate disease prevention and control. The document then lists the main uses of surveillance data, such as estimating disease burden and evaluating programs. It describes three main sources of surveillance data: individuals, healthcare providers, and environmental conditions. The document outlines the five main steps of surveillance and discusses selecting health problems for surveillance based on factors like disease severity. It also describes different data collection methods, like notifications, surveys, and disease registries. In closing, it outlines the flow of surveillance information between data providers, analysts, and those responsible for public health response and decision-making.
The document summarizes a term paper on public health surveillance in Nepal. It discusses the objectives, methodology, findings and conclusions of the paper. The key points are: public health surveillance involves ongoing collection and analysis of health data to guide public health practice; Nepal has integrated disease surveillance within its health management information system; and the country was commended for its efficient AFP surveillance and polio eradication efforts while still needing to address potential wild poliovirus circulation.
This document defines key terminology used in epidemiology and describes some important epidemiological methods. It defines epidemiology as the study of disease distribution and determinants in populations. Descriptive epidemiology organizes health data, while analytic epidemiology searches for causes and effects. Important measurements include rates, ratios and proportions to quantify disease frequency and distribution. Methods like incidence, prevalence, mortality and morbidity rates are used to measure disease occurrence and impact in populations.
Introduction to Epidemiology
History of Epidemiology.
Definition of Epidemiology and its components.
Epidemiological Basic concepts.
Aims of Epidemiology.
Ten Uses of Epidemiology.
Scope or The Areas of Application .
Types of Epidemiological Studies.
This document provides an introduction to the basic concepts of epidemiology. It defines epidemiology as the study of patterns, causes, and effects of health and disease conditions in populations. The aims of epidemiology are to describe disease distribution and frequency, identify risk factors, and provide data to prevent and control diseases. Epidemiologists make comparisons between groups with and without disease exposure to identify determinants and test hypotheses. Basic measurements in epidemiology include mortality, morbidity, disability, and the distribution of disease and risk factors. Rates, ratios, and proportions are key tools used to measure and express disease frequency in populations.
This document provides an introduction to biostatistics and key concepts. It defines biostatistics as the development and application of statistical techniques to scientific research relating to human life and health. Some key terms discussed include:
- Population, which is the totality of individuals of interest
- Sample, which is a subset of a population
- Variables, which can be qualitative (non-numerical) or quantitative (numerical)
- Levels of measurement for variables, including nominal, ordinal, interval, and ratio scales
- Descriptive methods for qualitative data, including frequency distributions
Biostatistics plays an important role in modern medicine, including determining disease burden, finding new drug treatments, planning resource allocation, and measuring
This document provides a history of epidemiology, covering its origins and key figures. It traces epidemiology back to ancient Greece and discusses its modern definition as the study of disease distribution and determinants in populations. Some important developments include John Graunt establishing demographic analysis in the 1600s, James Lind identifying citrus as preventing scurvy in 1747, Edward Jenner developing vaccination against smallpox in 1796, Ignaz Semmelweis reducing childbed fever mortality via handwashing in 1847, and John Snow linking cholera to contaminated water in 1854. These pioneers helped establish epidemiology's objectives of identifying disease causes and evaluating preventive measures.
Screening tests aim to identify unrecognized disease in apparently healthy individuals. They differ from diagnostic tests in that they are applied to groups rather than individuals, use a single criterion, and are less accurate. Validity refers to a test's accuracy while reliability is its precision on repeat tests. Sensitivity measures a test's ability to identify true positives, and specificity measures its ability to identify true negatives. Screening programs must consider factors like disease burden, test characteristics, and whether early detection improves outcomes.
This document discusses different types of error and bias that can occur in epidemiological studies. It defines random error as occurring due to chance and resulting in imprecise measures, while systematic error or bias results in invalid measures that are not true. Types of bias discussed include selection bias, information bias, and confounding. Selection bias can arise from how cases and controls are selected, while information bias occurs when exposure or disease status is incorrectly classified. The document emphasizes the importance of reducing both random and systematic errors to obtain valid study results.
Standardization is a process used to make rates such as mortality rates comparable between populations with different age distributions. There are two main methods: direct standardization which applies the age-specific rates of the populations to a standard population, and indirect standardization which calculates a standardized mortality ratio by taking the ratio of observed to expected deaths based on a standard population's rates. Standardization allows unbiased comparison of health outcomes between groups after removing the effect of differences in age composition.
The 10-step approach to outbreak investigations involves:
1) Identifying an investigation team and resources.
2) Establishing the existence of an outbreak.
3) Verifying the diagnosis, constructing a case definition, and finding cases systematically.
Descriptive epidemiology is then used to develop hypotheses, which are evaluated through additional studies if needed, before implementing control measures, communicating findings, and maintaining surveillance to confirm the outbreak has ended. Being systematic and following these steps is key to determining the source and controlling outbreaks.
Here are the key points to compare the different research methods:
Cross-sectional study:
- Advantages: Quick, easy, low cost, can study multiple factors at once
- Disadvantages: Cannot determine temporal sequence, prone to biases
- Requirements: Representative sample, standardized data collection
Case-control study:
- Advantages: Efficient to study rare diseases, can study multiple exposures
- Disadvantages: Prone to selection and recall biases, uncertain temporal sequence
- Requirements: Clear case definition, appropriate controls matched to cases
Cohort study:
- Advantages: Directly measures risk, establishes temporal sequence
- Disadvantages: Expensive, long follow up needed
Standardization of rates by Dr. Basil TumainiBasil Tumaini
Standardization of rates by Dr. Basil Tumaini, presented during the residency at Muhimbili University of Health and Allied Sciences, Epidemiology class
1. Effect modification and confounding are two aspects to consider when examining the relationship between an exposure and outcome. Effect modification provides useful information about how a third variable impacts the relationship, while confounding can distort the observed effect.
2. Stratifying the data and calculating stratum-specific odds ratios is a way to check for effect modification and confounding. Effect modification is present if the odds ratios differ substantially between strata. Confounding is present if the crude odds ratio differs from the stratified odds ratios.
3. It is important to measure potential confounding factors so they can be controlled for through stratification or multivariate analysis. This prevents confounding from distorting the observed effect between the exposure and outcome.
As per John M. Last (1988) 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.
This document discusses epidemiological methods for studying the distribution and determinants of health events and applying that knowledge to disease control. It defines descriptive epidemiology as the study of disease occurrence, distribution, and patterns in populations. Descriptive methods are observational and can be cross-sectional or longitudinal. Descriptive epidemiology provides insights into disease frequency, trends, and risk factors to inform public health planning and resource allocation.
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in populations and the application of this study to control health problems. It uses a systematic and unbiased approach to collect, analyze, and interpret data. Some core functions of epidemiology include public health surveillance, field investigations, analytic studies, evaluation of public health programs and services, linkages with other disciplines, and policy development. Epidemiology provides an evidence base for effective public health action and disease prevention.
This document provides an outline for a lesson on measures of association in epidemiology. It begins with introducing the key concepts of association versus causation and how measures of association are used to quantify the strength and direction of relationships between exposures and outcomes. It then discusses the different scales that measures can be calculated on, including relative and absolute scales. Examples of specific relative measures like risk ratio, prevalence ratio, and odds ratio are provided. Absolute measures like attributable risk and population attributable risk are also introduced. The document aims to explain the appropriate interpretation and calculation of various epidemiologic measures of association.
This document discusses hospital outbreak investigations. It defines endemic and epidemic infections in hospitals. Common source and propagated epidemics are described. Steps in investigating outbreaks in hospitals and communities are provided, including forming an investigation team, developing a case definition, conducting epidemiological and laboratory analyses. The goals of outbreak investigations are outlined. Methods for confirming and controlling outbreaks are discussed.
Experimental study in epidemiology methods pptanjalatchi
Experimental epidemiology involves manipulating study factors and conditions to test interventions and their effects on disease. There are two main types: randomized controlled trials (RCTs) and non-randomized trials. RCTs randomly assign subjects to treatment and control groups to reduce bias when testing new interventions. They involve developing a study protocol, selecting and randomizing populations, implementing interventions, follow-up, and assessing outcomes. Non-randomized trials do not randomly assign subjects and are used when RCTs are not possible, such as when interventions apply to groups. Examples include uncontrolled trials with no comparison and natural experiments that mimic real-world circumstances. Experimental epidemiology aims to identify disease causes and evaluate prevention and treatment effectiveness.
This document provides an overview of epidemiological studies and different study designs. It begins by defining epidemiology as the study of disease distribution and determinants in human populations. The major goal of epidemiologic research is to explain patterns of disease occurrence and causation.
It then describes qualitative and quantitative research approaches. For quantitative studies, it distinguishes between descriptive and analytical designs. Descriptive studies summarize disease patterns by time, place and person to generate hypotheses, while analytical studies aim to establish causal links between exposures and outcomes.
The document outlines different epidemiological study designs including experimental, observational, and quasi-experimental designs. It provides examples of randomized controlled trials, cohort studies, case-control studies and other designs, discussing their
This document discusses public health surveillance. It begins by defining surveillance and its main components, which include the ongoing collection and analysis of health data to facilitate disease prevention and control. The document then lists the main uses of surveillance data, such as estimating disease burden and evaluating programs. It describes three main sources of surveillance data: individuals, healthcare providers, and environmental conditions. The document outlines the five main steps of surveillance and discusses selecting health problems for surveillance based on factors like disease severity. It also describes different data collection methods, like notifications, surveys, and disease registries. In closing, it outlines the flow of surveillance information between data providers, analysts, and those responsible for public health response and decision-making.
The document summarizes a term paper on public health surveillance in Nepal. It discusses the objectives, methodology, findings and conclusions of the paper. The key points are: public health surveillance involves ongoing collection and analysis of health data to guide public health practice; Nepal has integrated disease surveillance within its health management information system; and the country was commended for its efficient AFP surveillance and polio eradication efforts while still needing to address potential wild poliovirus circulation.
This document defines key terminology used in epidemiology and describes some important epidemiological methods. It defines epidemiology as the study of disease distribution and determinants in populations. Descriptive epidemiology organizes health data, while analytic epidemiology searches for causes and effects. Important measurements include rates, ratios and proportions to quantify disease frequency and distribution. Methods like incidence, prevalence, mortality and morbidity rates are used to measure disease occurrence and impact in populations.
Introduction to Epidemiology
History of Epidemiology.
Definition of Epidemiology and its components.
Epidemiological Basic concepts.
Aims of Epidemiology.
Ten Uses of Epidemiology.
Scope or The Areas of Application .
Types of Epidemiological Studies.
Epidemiology is defined as the study of health and disease in populations. It examines the patterns and causes of disease distribution. Key terms include epidemic, which is a disease rate above normal; endemic, a usual disease rate; and pandemic, a global epidemic. Epidemiology is used to study disease history, assess community health needs, estimate individual disease risk, identify disease causes, and guide prevention efforts. Prevention includes primary prevention to stop disease onset, secondary prevention to halt early disease progression, and tertiary prevention to reduce disability from established disease.
This document provides an overview of modern epidemiology. It defines epidemiology as the study of the occurrence and distribution of health-related diseases or events in populations, including their determinants and control. The purposes of epidemiology are described as investigating disease extent and priorities, studying disease progression, identifying causes and risks, recommending interventions, and informing public policy. John Snow is highlighted for his work tracing a cholera outbreak that improved public health systems.
epidemiology with part 2 (complete) 2.pptAmosWafula3
This document provides an overview of epidemiology. It begins by defining epidemiology as the study of what falls upon populations in terms of health and disease. A modern definition is provided that describes epidemiology as studying the distribution and determinants of health states in populations.
The objectives and purposes of epidemiology are then outlined, which include describing disease distribution and magnitude, identifying risk factors, providing data for prevention/control programs, and recommending interventions. Key epidemiological terms like incidence, prevalence, endemic, epidemic, and pandemic are also defined. Descriptive and analytical study designs commonly used in epidemiology like cross-sectional and case-control studies are described. The document concludes by contrasting the approaches of epidemiology versus clinical medicine
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in populations, and the application of this study to control health problems. It aims to describe the distribution and magnitude of health problems, identify factors involved in disease causation, and provide data to plan, implement and evaluate prevention and control efforts. Epidemiology provides a framework and methodology for community health nurses to assess community health needs, evaluate nursing services, and investigate and address health problems in populations.
Epidemiology and preventive veterinary medicine.docx1Arjun Chapagain
The document provides an overview of preventive veterinary medicine and epidemiology. It defines preventive veterinary medicine as dealing with infectious diseases, their occurrence in animal populations, and methods of prevention and control. Epidemiology is introduced as the study of disease distribution and determinants in populations. The document then discusses key epidemiological concepts like agents, hosts, and the environment. It also outlines the objectives, scope, aims, methods, and applications of epidemiology, providing definitions for important epidemiological terminology.
This document provides an overview of epidemiological methods and concepts. It defines epidemiology as the study of disease distribution, determinants, and control in populations. Key concepts discussed include agents, hosts, and environments that influence disease occurrence. Descriptive epidemiology aims to describe disease distribution by time, place and person, while analytical epidemiology identifies risk factors. Observational and experimental study designs are classified. The document outlines the scope, aims, history and uses of epidemiology to understand and control health problems.
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. It investigates how disease spreads and is caused. The key factors that influence disease transmission include characteristics of the infectious agent, environmental factors that support the agent, and characteristics of the host that influence susceptibility.
The document provides an overview of epidemiology including:
- The definition and origins of epidemiology as the study of disease distribution and determinants in populations.
- Key concepts in epidemiology including rates, ratios, proportions, mortality, morbidity, incidence, prevalence and descriptive vs analytical study methods.
- Descriptive studies examine disease frequency and distribution by person, place and time to identify potential risk factors. Analytical studies further test hypothesized associations between suspected causes and effects.
- Examples of rates and ratios used to measure disease occurrence include crude death rates, case fatality rates, and proportional mortality rates. Incidence and prevalence are used to measure disease frequency and burden.
statistical methods in epidemiology.pptxAnusha Are
This document discusses key concepts and measurements used in statistical epidemiology. It defines epidemiology as the study of disease patterns in populations and notes its importance for public health. Some key measurements covered include incidence rate, prevalence, relative risk, attributable risk, and attributable fraction. Incidence rate measures new cases over time, while prevalence looks at total current cases. Relative risk compares risk between exposed and unexposed groups. Attributable risk is the difference in rates between groups, and attributable fraction shows the proportion of disease from an exposure.
Epidemiology is defined as the study of the distribution and determinants of health-related states or events in specified populations. It aims to describe disease frequency, distribution, and causative factors in order to provide data to plan, implement, and evaluate disease prevention and control programs. The epidemiological approach involves asking questions about health events and outcomes in populations, and making comparisons between groups with different exposures to identify risk factors and draw inferences about disease causation.
This document discusses epidemiology and how it was used to identify smoking as a cause of lung cancer. It shows that lung cancer rates increased dramatically between 1937-1950 in the US. A case-control study found that smokers were over 20 times more likely to develop lung cancer than non-smokers. A later British study found that lung cancer risk increased with the number of cigarettes smoked per day. Through observational epidemiological studies, researchers were able to establish smoking as a major risk factor and cause of lung cancer.
This document outlines the educational objectives and content for a lecture on epidemiology. The objectives are to define key epidemiology terms, discuss the functions and modes of epidemiologic investigation, and identify sources of data and potential sources of error. The content includes definitions of epidemiology and related terms, the main functions of epidemiology, descriptive and analytic modes of investigation, how surveillance system data is applied through outbreak investigation, and sources of epidemiological data and potential sources of error.
2. How these inferences are
arrived
Normal pulse rate 60-90/minute
Measles & chicken pox mostly occurs during
spring
Cancer of stomach more common in Japanese
Lung cancer is common among smokers
Paracetomol is 90% effective in headache
Metronidazole is effective against Amoebiasis
3. Epidemiology
What is epidemiology ?
We study health and disease
1. By observing individuals
2. By laboratory of experimental animals
3. By measuring the distribution of health
problem in population
Third one is epidemiology – putting people into
groups
4. John snow- epidemic of
cholera
Located the home of each person of cholera
in London 1854
Found out association between source of
water supply and cholera
Cholera – spread by contaminated water
before discovery of the organism of cholera
6. British Doctors Study
By Doll & Hill
The relationship between cigarette smoking
& lung cancer in 1950 a follow up study on
British doctors
7. Epidemiology
Epidemiology derived from Greek word
Epi-- on or upon
demos-- people
logos-- the study
The study upon the people or population
8. Definition
The study of the distribution and
determinants of health related states or
events in specified population, and the
application of this study to control of health
problems
Disease frequency
Disease distribution
Disease determinants
9. Disease frequency
Epidemiology is concerned with the frequency and
pattern of health events in a population
Measurements of frequency of disease, disability or
death in the form of rates and ratios
Rates are essential for the comparison of frequency
in different population
Comparison may yield important clue for the
etiology or formulation of etiological hypothesis
10. Distribution of disease
Time characteristics include annual occurrence,
seasonal occurrence and daily or even hourly
occurrence during an epidemic
Place characteristics include geographic variation,
urban- rural differences.
Personal characteristics include age, sex, race,
marital status, socioeconomic status, Behaviour and
environmental exposure
This aspect of study is called as descriptive study
11. Descriptive epidemiology provides what,
when, and where of health related events
What is the event or disease?
What is the magnitude?
When did it happen?
Where did it happen?
Who are affected?
The important out come distribution study is
formulation of etiological hypothesis
12. Determinants of disease
Test the etiological hypothesis and identify the
underlying causes or risk factors of disease
This aspect of epidemiology is Analytical
epidemiology
Which provides why and how of such events by
comparing groups with different rates of disease
occurrence.
By searching the differences in the characteristics
between the diseased and healthy
13. Making comparison
The basic approach in epidemiology is to
make comparison and draw conclusion
By comparison we try to find out curial
differences in the host and environmental
factors between those affected and not
affected
Basic tools of measurement are necessary
for the comparison –rates, ratio and
proportion
14. Rate
There were 500 deaths from motor vehicle
accident in city A
In epidemiology compare the rates of
accident in city a with city B
Rate – elements denominator, numerator,
time specification and multiplier.
Crude rates
Specific rates
Standardized rates
15. Ratio
Another measure of disease frequency
Shows the relation in size between two
quantities
The numerator not a component of the
denominator
Sex ratio, doctor population ratio, child
woman ratio etc.
16. Proportion
Shows the relation in magnitude of the part of
the whole
The numerator is always included in the
denominator
Proportional mortality rate
17. Measurements of mortality
Mortality data provides the starting point for
many epidemiological studies.
Mortality data is relatively easy to collect and
reasonably accurate
The basis of mortality data is the death
certificate
18. International death certificate
For national and international comparison a
standardized system of recording and
classification death
Part I – deals with immediate
cause( pneumonia) and underlying cause of
death( strangulated hernia)
Part II – deals with associated disease that
contributed to the death( diabetes)
19. Limitation of mortality data
Incomplete reporting of death
Lack of accuracy
Lack of uniformity
Choosing a single cause of death
Changing coding system
Diseases with low fatality
20. Uses mortality data
Can explain the trends and differences in
overall mortality
Help in prioritization for health action
Allocation of scares resource
For assessment and monitoring of public
health programmes
Gives important clue for epidemiological
research
21. Commonly used mortality
rates and ratio
Crude death rate – simplest measure, lack
comparability
Specific death rate – age, disease, income, religion
etc.
Case fatality- killing power of disease for acute and
not chronic
Proportional mortality rate –cause, age etc. can be
used when population data are not available
Survival rate- usually for five years
Standardized rates – direct and indirect
22. Measurements of morbidity
Any departure, subjective or objective, from
a state of physiological well-being
Sickness, illness, disability
Measured by
1. Persons who are ill
2. Illness frequency( spells of illness)
3. The duration
23. Incidence rate
The number of NEW cases occurring in a
defined population during a specific period of
time.
Incidence
Number of new cases of specific
Disease during a given time period
Population at risk during that period
X 1000
24. Uses of incidence rate
Taking action to control disease
Research into the etiology or causation
Research into the pathogenesis
Studying distribution of disease
Test the efficacy of preventive and
therapeutic measures
Used for formulating and testing the
hypothesis
25. Special incidence rates
Attack rate
Used only when the population is exposed to
risk for a limited period of time such as during
an epidemic
Usually expressed as a percentage
26. Secondary attack rate
The number of exposed person developing
the disease within the range of the incubation
period following exposure to primary case
SAR
Number of exposed person developing the disease
within the range of the incubation period
Total number of exposed/ susceptible contacts
X100
27. Secondary Attack Rate
Limited to application in infectious diseases
In disease where there are numerous sub-
clinical cases
Useful to determine the disease of unknown
etiology is communicable or not
Useful in evaluating the effectiveness of
control measures – immunization
28. Prevalence
All current cases ( old or new) existing at a
given point of time or over a period of time in
a given population
Point prevalence
Period prevalence
29. Start of illness
Duration of illness
Incidence - case 3,4,5 & 8
Jan 1 Dec 31
Case 1
Case 2
Case 3
Case 4
Case 5
Case 6
Case 7
Case 8
Point prevalence Jan 1- 1, 2 & 7
Point prevalence Dec 31- 1,3,5 & 8 Period prevalence Jan-Dec- 1,2,3,4,5,7,&8
Number of cases Jan- Dec
30. Relationship between prevalence &
incidence
• Depends upon two factors, incidence &
duration
P = I X D
Prevalence = incidence X mean duration
Longer the duration of the disease the greater the prevalence
A decrease in incidence & duration will decrease prevalence
31. • For chronic diseases (TB)- high
prevalence rate relative to incidence
• For acute diseases ( food poisoning,
diarrhoea)- prevalence is relatively low
compared to incidence
• For acute disease- no prevalence ( No of
episodes)
• Treatment decreasing the duration will
decrease the prevalence
• Treatment preventing death but no
recovery will increase the prevalence
32. Uses of prevalence
• To estimate the magnitude of
health/disease problems in a community
• Identify potential high risk population
• Useful for administrative & planning
purpose ( No of hospital beds, man power
need, rehabilitation facilities)
33. Aims of epidemiology
To describe the distribution and magnitude of
health and disease problem in human
population
To identify etiological factors in the
pathogenesis of disease
To provide data essential to the planning,
implementation and evaluation of services for
the prevention, control and treatment of
disease and setting up priorities
34. Epidemiology and Clinical
medicine
Epidemiology Clinical medicine
Population at risk Case or cases
Both sick and healthy Only sick
Relevant data by studying group or
population
History taking Sign and
symptoms Lab investigation
Patient comes to the doctor Investigator goes to the
community
A knowledge of prevalence, etiology and prognosis derived from
epidemiological research is important to the clinician for the
diagnosis and management of individual patient