environmental health: GIS & epidemiology – Flashcards
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purposes of epidemiology
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1) identify causes and risk factors for disease 2) determine the extent of disease in the community 3) study natural history and prognosis of disease 4) evaluate preventive, therapeutic, or intervention measures 5) provide foundation for public policy
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types of studies
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- randomized control trial - prospective cohort study - case-control study - retrospective cohort study - cross-sectional study - ecological study - disease cluster - case series
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what is epidemiology?
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study of distribution and determinants of health conditions in human populations
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randomized control trial
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often in clinical trials
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prospective cohort study
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follow group, track exposures and disease incidence
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case-control study
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compare people with and without disease vs. with and without risk factor
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retrospective cohort study
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defines incidence in an existing group
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cross-sectional study
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snapshot in time: prevalence vs. exposure
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ecological study
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group exposure and group prevalence
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disease cluster
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group of similar diseases
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case series
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collection of cases, subject to selection bias
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descriptive epidemiology
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examines the distribution of a disease in a population and observes the basic features of its distribution in terms of time, place, and person
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typical study designs of descriptive epidemiology
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- observational study - community health survey - cross sectional study - case series
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analytic epidemiology
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tests a specific hypothesis about the relationship of a disease to an assumed cause, by conducting a statistical analysis that relates the exposure of interest to the disease of interest
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typical study designs of analytic epidemiology
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- cohort - case-control
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what is a common error in epidemiology?
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moving to analytic epidemiology without having a solid base in the exposure assessment and descriptive epidemiology of the condition
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what is environmental epidemiology?
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the epidemiological investigation of the relationship between environmental exposure and states of health
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occupational epidemiology
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- sub-branch of environmental epidemiology - investigates work-related exposure effects
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what are environmental exposures?
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- usually involuntary exposures to chemical, physical, or biological contaminants from the general or occupational environment - secondhand smoke, radioactive radon gas emissions, salmonella bacteria in chickens
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characteristics of environmental exposures
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- usually very low levels and often difficult to measure - often many of them, in complex mixtures, and correlated with each other - often exposure levels do not differ very much among individuals within areas - multiple routes of exposure - relative risks can be very low although exposed populations may be very large
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common hazards encountered in environmental epidemiology
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- contaminant chemicals in air, water, or food - disease-causing microorganisms in food and water - ionizing and non-ionizing radiation - noise, het, odor - hazardous wastes - occupational exposures - climatic factors
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what are exposures like personal habits, socioeconomic factors, nutritional status, political and legal context, and genotype usually treated as?
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- confounders - effect modifiers - determinants of exposure status
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examples of environmental epidemiology
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- environmental causes of asthma - arsenic in drinking water as a cause of cancer - whether low mercury exposures cause autism - health risks associated with climate change
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reasons for increase in the importance of environmental epidemiology
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- reduction of infectious diseases - increase in human lifespan - increase in chronic diseases - estimated 80-90% of cancers due to environmental factors - cancer latency understanding - toxicology tests showing cancer in animals - increase in analytical capability of chemists
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characteristics of toxicology
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- mostly experimental - variables controlled by the investigator - all variables known - replication possible - results valid for test cells or species - meaning of results for humans uncertain - little need for complex statistical analysis of data - highly equipment intensive
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characteristics of epidemiology in the field
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- mostly observational - variables controlled by nature - some variables unknown - replication difficult; exact replication impossible - results often uncertain - meaning of results for humans clear - statistical control often very important - highly labor intensive
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what are the three essential characteristics of disease relationships in descriptive epidemiology?
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- time - person - place
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person
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- age - socioeconomic status - gender - ethnicity/race - behavior
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time
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- seasonal variation - clustered (epidemic) or evenly distributed (endemic)?
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place
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- geographically restricted or widespread (pandemic)? - multiple clusters or one? - water and air do not match political boundaries
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what are the three phenomena assessed in environmental epidemiology?
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- host - agent - environment
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what is the epidemiologic triangle used for?
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used for describing the causality of infectious diseases
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environment
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- domain in which disease-causing agents may exist, survive, or originate - consists of "all that which is external to the individual human host"
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host
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a person or other living animal, including birds and arthropods, that affords subsistence or lodgment to an infectious agent under natural conditions
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host factors
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- genetic factors - immunologic state - age - personal behavior
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agent
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a factor, such as a microorganism, chemical substance, or form of radiation, whose presence, excessive presence, or (in deficiency diseases) relative absence is essential for the occurrence of a disease
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examples of agents
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- nutrients - poisons (toxins and toxicants) - radiation - physical trauma - psychological experiences - drinking water contaminants - microbes
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modes of transmission
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- phenomena in the environment that bring host and agent together - vector, vehicle, reservoir
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vector
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animate: ticks, mosquitos, copepods, amoebae
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vehicle
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inanimate: apple
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reservoirs
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- crop-field: pesticide - lake: naegleria
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biases in environmental epidemiology
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- selection bias - recall bias - confounding
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calculation of odds ratio
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prob/(1-prob)
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calculation of probability
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outcome/total odds/(1+odds)
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definition of probability
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number of times something occurs divided by the total number of occurrences
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definition of odds
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number of times something occurs divided by the number of times something does not occur
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in evaluating health effects of occupational exposures to toxic agents, researchers may study various endpoints using measures derived from...
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- self-reported symptom rates - physiologic or clinical examinations - mortality
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healthy worker effect
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- employed workers have lower mortality rates than general populations - healthy worker effect could introduce selection bias into occupational mortality studies
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confounding
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existence of other factors that contribute to the outcome of the study
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RR or OR = 1
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risk is the same in exposed and unexposed
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RR or OR > 1
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risk is higher in exposed and unexposed
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RR or OR < 1
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risk is lower in exposed and unexposed (the agent is protective)
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limitations of epidemiologic studies
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- long latency periods - low incidence and prevalence - difficulties in exposure assessment - nonspecific effects
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limitations in detecting disease
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- long and variable latency periods between exposure and disease diagnosis - etiologic non-specificity of disease clinical features - small population size coupled with low disease frequency - observer bias in reporting illness occurrence
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limitations in measuring exposure
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- dependence on indirect, surrogate estimates of exposure and dose (distance from pollution site) - uncertainty regarding pathways of exposure - probable low-dose levels in most settings - frequent inability to develop useful dose-response data
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Bradford-Hill's Criteria of Causality
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- strength - consistency - specificity - temporality - biological gradient (dose/response) - plausibility - coherence
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what is GIS a combination of?
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data acquisition, storage, display, and analysis
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what does the GIS analysis system consist of?
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hardware, software, data, analysis capabilities, and people networked together
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definition of GIS
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system of hardware, software, and procedures designed to support the capture, management, manipulation, analysis, modeling, and display of spatially referenced data for solving complex planning and management problems
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variety of required hardware for GIS
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- input and output devices - display devices (screen) - computer processors - storage system - network--can be the "cloud"
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software functions
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- data input, editing, output - linkage to georeferencing systems - analytic capabilities - map composition and display
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all GIS data is explicitly...
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SPATIAL - has a location in a spatial reference system - contrast to aspatial phenomena
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aspatial data
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income, gender, ideas, beliefs
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spatial data
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mountains, city or county lines, city elevation, pesticide use per area
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data requirements
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- data acquisition - georeferencing - data representation - data quality - data storage
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data acquisition
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how do we get data into a digital format? from what sources?
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georeferencing
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how do we link the data to the places on the earth's surface we are mapping?
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data representation
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how do we represent different types of objects we map?
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data quality
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how do we measure and track the quality of the data?
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data storage
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how can we efficiently store and retrieve the data?
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strengths and weaknesses of GIS
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- often suggestive of relationships and hypotheses - can educate public and officials - open to abuse with cartographic tricks - can be misinterpreted as causal
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how do you search for relationships with maps meeting certain conditions?
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- Boolean or set operations - AND, OR
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information about place important for many applications
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- efficient location and management of services - understanding the function of natural systems - insights on the functioning of urban economies - exploring market opportunities - managing utilities and infrastructure
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what is GIS both?
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recording and display of information and its analysis
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data characteristics
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- space - attribute - relationships between features - time
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space
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- feature locations; all data are georeferenced - ways to define a single point on the planet - ex: latitude/longitude, UTM, state plane
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attribute
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- feature attributes, qualities and characteristics to geographic places - ex: elevation, soil moisture, temperature, disease case (ebola, Zika, cholera)
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relationships between features
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overlay, connectivity, adjacency, distance
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vector data
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- based on mathematical function - point, line, polygon, surface
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raster data
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- data present on a fixed grid structure (matrix) - image, grid
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examples of polygon, lines, points
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- polygon: area of Berkeley - lines: streets - points: pizza restaurants
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dot map
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- dots represent a unit number of items within the larger geographic unit - dot density indicates the intensity of concentration
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points with different symbols
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- easier to distinguish - difficult to see in dense areas - potential need to change scale
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point with proportional symbols
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- easiest to interpret - difficult to see in dense areas - potential need to change scale or symbol size
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chloropleth map
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- group geographic units into categories based on a numeric value - choices in classification--number of categories, break points (natural, quartiles, quintiles, by standard deviation, etc) - when possible, choose numeric break points that relate to data type - ex: rent or income
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area map
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each area represents a unique value for that part of the surface
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isoline map
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- lines connecting points of equal value (elevation) - could also be a surface generated by other types of data (e.g. disposable income, travel time to a particular destination)
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cartogram
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- adjust the size of a unit based on a secondary variable (attribute) to illustrate its weight
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examples of vector data
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- GPS data - rivers - counties - habitat boundaries - soil type - census data
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examples of raster data
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- satellite imagery - elevation - digital USGS - landcover/landuse - precipitation - aerial photography
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what does spatial analysis enabled by?
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software but requires people to executive appropriately
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what does spatial analysis require?
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- extensive planning and management before implementation - resources to maintain data integrity - avoid misrepresentation of data
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uses of spatial analysis
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- represent trends in space and time as well as spatial relationships - scenarios of the future (e.g. population migration, flooding, land use change) - build statistical models of patterns and relationships - optimize the location of infrastructure and services
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tobler's first law of geography
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- everything is related to everything else, but near things are more related than distant things - we use GIS to help us create models or representations of those relationships - one problem we then face is the accuracy of the depiction of those relationships and how it is impacted by the scale of the data, data quality, and the types of data available
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spatial autocorrelation
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measure of the degree to which a set of spatial features and their associated data values tend to be clustered together in space (positive spatial autocorrelation) or dispersed (negative spatial autocorrelation)
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positive spatial autocorrelation
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clustered together in space
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negative spatial autocorrelation
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dispersed
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spatial autocorrelation implications
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- forms basis of many geostatistical methods - can suggest new hypotheses - can render traditional statistical tests invalid because it violates the independent observation assumption
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independent observation assumption
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assumptions of randomness and variables are not correlated with each other
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most common autocorrelation test
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Global Moran's I statistic most common
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what do global tests measure?
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overall tendency of high (or low) values to cluster together
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what do local tests measure?
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smaller areas in relation to all data points (hot spots)
