This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the 2020 County Health Rankings page about Life Expectancy:"Life Expectancy is an AverageLife Expectancy measures the average number of years from birth a person can expect to live, according to the current mortality experience (age-specific death rates) of the population. Life Expectancy takes into account the number of deaths in a given time period and the average number of people at risk of dying during that period, allowing us to compare data across counties with different population sizes.Life Expectancy is Age-AdjustedAge is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. Life Expectancy is age-adjusted in order to fairly compare counties with differing age structures.What Deaths Count Toward Life Expectancy?Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, that death is attributed to his/her home county.Some Data are SuppressedA missing value is reported for counties with fewer than 5,000 population-years-at-risk in the time frame.Measure LimitationsLife Expectancy includes mortality of all age groups in a population instead of focusing just on premature deaths and thus can be dominated by deaths of the elderly.[1] This could draw attention to areas with higher mortality rates among the oldest segment of the population, where there may be little that can be done to change chronic health problems that have developed over many years. However, this captures the burden of chronic disease in a population better than premature death measures.[2]Furthermore, the calculation of life expectancy is complex and not easy to communicate. Methodologically, it can produce misleading results caused by hidden differences in age structure, is sensitive to infant and child mortality, and tends to be overestimated in small populations."Click on the map to see a breakdown by race/ethnicity in the pop-up: Full details about this measureThere are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.Data from County Health Rankings 2020 (in this layer and referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World

Over the period 2007-2011, life expectancy at birth was 78.5 years for the total population in New Mexico, 75.8 years for males, and 81.3 years for females.For comparison, in 2011, life expectancy at birth was 78.7 years for the total U.S. population, 76.3 years for males, and 81.1 years for females. (http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6335a8.htm?s_cid=mm6335a8_e )PLEASE NOTE: The data in this map corrects, updates and replaces life expectancy data included in the 2012 Bernalillo County Place Matters 'Community Health Equity Report'. Compare life expectancy in Europe and the USA - Map ImageNOTE: Changes in life expectancy (Increase, Decrease, No Change) over the periods 1999-2003 to 2007-2011 are tested for statistical significance using a rule of one standard deviation.

Life Expectancy at Birth, Small Areas, by Sex, 1999-2003 and 2007-2011 - LEBSASEX

Summary: Life Expectancy at Birth, Small Areas, by Sex, 1999-2003 and 2007-2011

Prepared by: NEW MEXICO COMMUNITY DATA COLLABORATIVE, http://nmcdc.maps.arcgis.com/home/index.html ; T Scharmen, thomas.scharmen@state.nm.us, 505-897-5700 x126,

Data Sources: New Mexico Death Certificate Database, Office of Vital Records and Statistics, New Mexico Department of Health; Population Estimates: University of New Mexico, Geospatial and Population Studies (GPS) Program, http://bber.unm.edu/bber_research_demPop.html. Retrieved Mon, 21 June 2014 from New Mexico Department of Health, Indicator-Based Information System for Public Health Web site: http://ibis.health.state.nm.us

Shapefile: http://nmcdc.maps.arcgis.com/home/item.html?id=1e97d2715d8640ab9023fa35fc7b2634

Feature: http://nmcdc.maps.arcgis.com/home/item.html?id=3104749c2c094044914abf9ba6953eab

Master File:

NM DATA VARIABLE DEFINITION

999 SANO Small Area Number

NEW MEXICO SANAME Small Area Name

9250534 PB9903 Population at Risk, Both Sexes, 1999-2003

77.7 LEB9903 Life Expectancy at Birth, Both Sexes, 1999-2003

77.7 CILB9903 Lower Confidence Interval for Life Expectancy at Birth, Both Sexes, 1999-2003

77.7 CIUB9903 Upper Confidence Interval for Life Expectancy at Birth, Both Sexes, 1999-2003

10188104 PB0711 Population at Risk, Both Sexes, 2007-2011

78.5 LEB0711 Life Expectancy at Birth, Both Sexes, 2007-2011

78.5 CILB0711 Lower Confidence Interval for Life Expectancy at Birth, Both Sexes, 2007-2011

78.5 CIUB0711 Upper Confidence Interval for Life Expectancy at Birth, Both Sexes, 2007-2011

0.8 LEBDIFF Difference in Life Expectancy, Both Sexes, 2007-2011 MINUS 1999-2003

INCREASE LEBSIG Trend of the Difference in Life Expectancy, Both Sexes, (1 standard deviation = 68.2% confidence interval)

4683013 PF9903 Population at Risk, Females, 1999-2003

80.6 LEF9903 Life Expectancy at Birth, Females, 1999-2003

80.6 CILF9903 Lower Confidence Interval for Life Expectancy at Birth, Females, 1999-2003

80.6 CIUF9903 Upper Confidence Interval for Life Expectancy at Birth, Females, 1999-2003

5155192 PF0711 Population at Risk, Females, 2007-2011

81.3 LEF0711 Life Expectancy at Birth, Females, 2007-2011

81.3 CILF0711 Lower Confidence Interval for Life Expectancy at Birth, Females, 2007-2011

81.3 CIUF0711 Upper Confidence Interval for Life Expectancy at Birth, Females, 2007-2011

0.7 LEFDIFF Difference in Life Expectancy, Females, 2007-2011 MINUS 1999-2003

INCREASE LEFSIG Trend of the Difference in Life Expectancy, Females, (1 standard deviation = 68.2% confidence interval)

4567521 PM9903 Population at Risk, Males, 1999-2003

74.8 LEM9903 Life Expectancy at Birth, Males, 1999-2003

74.8 CILM9903 Lower Confidence Interval for Life Expectancy at Birth, Males, 1999-2003

74.8 CIUM9903 Upper Confidence Interval for Life Expectancy at Birth, Males, 1999-2003

5032911 PM0711 Population at Risk, Males, 2007-2011

75.8 LEM0711 Life Expectancy at Birth, Males, 2007-2011

75.7 CILM0711 Lower Confidence Interval for Life Expectancy at Birth, Males, 2007-2011

75.8 CIUM0711 Upper Confidence Interval for Life Expectancy at Birth, Males, 2007-2011

1 LEMDIFF Difference in Life Expectancy, Males, 2007-2011 MINUS 1999-2003

INCREASE LEMSIG Trend of the Difference in Life Expectancy, Males, (1 standard deviation = 68.2% confidence interval)

1.077540107 FMRT9903 Female to Male Ratio of Life Expectancy, 1999-2003

1.072559367 FMRT0711 Female to Male Ratio of Life Expectancy, 2007-2011

5.8 FMDT9903 Female Life Expectancy MINUS Male Life Expectancy, 1999-2003

5.5 FMDT0711 Female Life Expectancy MINUS Male Life Expectancy, 2007-2011

-0.3 FMDTDIFF Difference in Female Life Expectancy MINUS Male Life Expectancy, over both time periods, in Years

Life expectancy at birth data by census tract.

This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the 2020 County Health Rankings page about Life Expectancy:

Breakdown by race/ethnicity in pop-up:

There are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.

Data from County Health Rankings 2020 (in this layer and referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World

The map contains data on the life expectancy for the census tracts within Texas. The longevity data for this service was created by the Center for Disease Control U.S. Small-area Life Expectancy Estimates Project ( USALEEP).The map is an ongoing collaboration with EGIS and the City of Dallas Senior Affairs Commission. EGIS has aggregated the life expectancy estimates to the Dallas proper geographical boundaries by using the center points of tracts. These are estimations and can be over- or under- estimated due to these approximations.

This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the County Health Rankings page about Life Expectancy:"Life Expectancy is an AverageLife Expectancy measures the average number of years from birth a person can expect to live, according to the current mortality experience (age-specific death rates) of the population. Life Expectancy takes into account the number of deaths in a given time period and the average number of people at risk of dying during that period, allowing us to compare data across counties with different population sizes.Life Expectancy is Age-AdjustedAge is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. Life Expectancy is age-adjusted in order to fairly compare counties with differing age structures.What Deaths Count Toward Life Expectancy?Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, that death is attributed to his/her home county.Some Data are SuppressedA missing value is reported for counties with fewer than 5,000 population-years-at-risk in the time frame.Measure LimitationsLife Expectancy includes mortality of all age groups in a population instead of focusing just on premature deaths and thus can be dominated by deaths of the elderly.[1] This could draw attention to areas with higher mortality rates among the oldest segment of the population, where there may be little that can be done to change chronic health problems that have developed over many years. However, this captures the burden of chronic disease in a population better than premature death measures.[2]Furthermore, the calculation of life expectancy is complex and not easy to communicate. Methodologically, it can produce misleading results caused by hidden differences in age structure, is sensitive to infant and child mortality, and tends to be overestimated in small populations."Breakdown by race/ethnicity in pop-up: (This map has been updated with new data, so figures may vary from those in this image.)There are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.Proven strategies to improve life expectancy and health in general A database of dozens of strategies can be found at County Health Rankings' What Works for Health site, sorted by Health Behaviors, Clinical Care, Social & Economic Factors, and Physical Environment. Policies and Programs listed here have been evaluated as to their effectiveness. For example, consumer-directed health plans received an evidence rating of "mixed evidence" whereas cultural competence training for health care professionals received a rating of "scientifically supported." Data from County Health Rankings (layer referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World.

This map displays data from the Selected Social and Economic Indicators dataset (tables DP02 and DP03) from the American Community Survey 5-Yr Estimates, U.S. Census Bureau. Economic and education measures are from 2010, while race/ethnicity estimates are from 2011, these data are presented at the census tract level. Life expectancy is presented at the small area level, as defined by NMDOH, and is based on birth/mortality records for the period 2007-2011.

Algeria had the highest life expectancy at birth in Africa as of 2023. A newborn infant was expected to live over 77 years in the country. Cabo Verde, Tunisia, and Mauritius followed, with a life expectancy between 77 and 75 years. On the other hand, Chad registered the lowest average, at nearly 54 years. Overall, the life expectancy in Africa was almost 63 years in the same year.

The U.S. Small-area Life Expectancy Estimates Project (USALEEP) is a partnership of NCHS, the Robert Wood Johnson Foundation (RWJF)External, and the National Association for Public Health Statistics and Information Systems (NAPHSIS)External to produce a new measure of health for where you live. The USALEEP project produced estimates of life expectancy at birth—the average number of years a person can expect to live—for most of the census tracts in the United States for the period 2010-2015. These estimates were published in September, 2018."A growing body of research is recognizing the importance of measuring mortality outcomes in small geographic areas, such as U.S. census tracts, to identify health disparities within a population. The indicator most widely identified as the ideal measure of a population’s mortality experience is life expectancy at birth. The concept of life expectancy is intuitive and easily understood by both policymakers and the lay public. Life expectancy is estimated for national populations by most developed countries, including the United States, which has produced the estimate annually since 1945 and decennially since 1900. However, its calculation is relatively complex compared with that of other summary mortality measures, because it entails the calculation of six distinct functions and requires a minimum number of age groups and total population size, below\ which the estimates become unstable and unreliable." - USALEEP Methodology Summary The methodology used to calculate the U.S. censustract abridged life tables consisted of several stages. First, through a collaboration between the National Vital Statistics System registration areas and the National Center for Health Statistics, death records of U.S. residents (excluding residents of Maine and Wisconsin) for deaths occurring in 2010 through 2015 were geocoded using decedents’ residential addresses to identify and code census tracts. Second, population estimates were produced based on the 2010 decennial census and the 2011–2015 American Community Survey 5-year survey. Third, a methodology that combined standard demographic techniques and statistical modeling was developed to address challenges posed by small population sizes and small and missing age-specific death counts. Last, standard, abridged life table methods were adjusted to account for error introduced by population estimates based on sample data. To review the full methodology, please use the following link: https://www.cdc.gov/nchs/data/series/sr_02/sr02_181.pdf

Click a census tract on the map to view the details. Click "Layers" to explore other demographic layers.The Racial and Social Equity Index combines information on race, ethnicity, and related demographics with data on socioeconomic and health disadvantages to identify where priority populations make up relatively large proportions of neighborhood residents. Click here for a User Guide.The Composite Index includes sub-indices of: Race, English Language Learners, and Origins Index ranks census tracts by an index of three measures weighted as follows: Persons of color (weight: 1.0) English language learner (weight: 0.5) Foreign born (weight: 0.5)Socioeconomic Disadvantage Index ranks census tracts by an index of two equally weighted measures: Income below 200% of poverty level Educational attainment less than a bachelor’s degreeHealth Disadvantage Index ranks census tracts by an index of seven equally weighted measures: Adults with no leisure-time physical activity Adults with diagnosed diabetes Adults with obesity Adults who reported mental health as not good Adults with asthma Low life expectancy at birth Adults with one or more disabilityThe index does not reflect population densities, nor does it show variation within census tracts which can be important considerations at a local level.Sources are as indicated below. Additional layers are updated annually by the Office of Planning and Community Development.Produced by City of Seattle Office of Planning & Community Development. For more information on the indices, including guidance for use, contact Diana Canzoneri (diana.canzoneri@seattle.gov).Get the data for this map from SeattleGeoDataSources: 2017-2021 5-Year American Community Survey Estimates, U.S. Census Bureau; 2020 Decennial Census, U.S. Census Bureau; modeled estimates from the Centers for Disease Control’ in the PLACES project; Washington State Department of Health’s Washington Tracking Network (WTN);, and estimates from the Public Health – Seattle & King County (based on the Community Health Assessment Tool).Notes: Language is for population age 5 and older. Educational attainment is for the population age 25 and over.Life expectancy is life expectancy at birth.Other health measures based on percentages of the adult population.

!!PLEASE NOTE!! When downloading the data, please select "File Geodatabase" to preserve long field names. Shapefile will truncate field names to 10 characters.Version: CurrentThe Racial and Social Equity Index combines information on race, ethnicity, and related demographics with data on socioeconomic and health disadvantages to identify where priority populations make up relatively large proportions of neighborhood residents. Click here for a User Guide.See the layer in action in the Racial and Social Equity ViewerClick here for an 11x17 printable pdf version of the map.The Composite Index includes sub-indices of: Race, English Language Learners, and Origins Index ranks census tracts by an index of three measures weighted as follows: Persons of color (weight: 1.0) English language learner (weight: 0.5) Foreign born (weight: 0.5)Socioeconomic Disadvantage Index ranks census tracts by an index of two equally weighted measures:Income below 200% of poverty level Educational attainment less than a bachelor’s degreeHealth Disadvantage Index ranks census tracts by an index of seven equally weighted measures:No leisure-time physical activityDiagnosed diabetes ObesityMental health not good AsthmaLow life expectancy at birthDisabilityThe index does not reflect population densities, nor does it show variation within census tracts which can be important considerations at a local level.Sources are as indicated below.Produced by City of Seattle Office of Planning & Community Development. For more information on the indices, including guidance for use, contact Diana Canzoneri (diana.canzoneri@seattle.gov).Sources: 2017-2021 Five-Year American Community Survey Estimates, U.S. Census Bureau; 2020 Decennial Census, U.S. Census Bureau; estimates from the Centers for Disease Control’ Behavioral Risk Factor Surveillance System (BRFSS) published in the “The 500 Cities Project,”; Washington State Department of Health’s Washington Tracking Network (WTN);, and estimates from the Public Health – Seattle & King County (based on the Community Health Assessment Tool).Language is for population age 5 and older. Educational attainment is for the population age 25 and over.Life expectancy is life expectancy at birth.Other health measures based on percentages of the adult population.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which
counts all residents regardless of legal status or citizenship--except
for refugees not permanently settled in the country of asylum, who are
generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: Life expectancy at birth indicates the number of years a newborn infant
would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which
counts all residents regardless of legal status or citizenship--except
for refugees not permanently settled in the country of asylum, who are
generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: Life expectancy at birth indicates the number of years a newborn infant
would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

C. shasta (Ceratonova shasta) is a parasite that can adversely affect salmonids and in some instances maybe fatal. This parasite completes its life cycle by infecting polychaete worms (Manayunkia speciosa) in their myxospore stage; then is released as a actinospore which infects salmonids. Steelhead (Oncorhynchus mykiss), Chinook (Oncorhynchus tshawytscha) and Coho (Oncorhynchus kisutch) are species of concern regarding C. shasta infection in the Klamath River.U.S. Fish and Wildlife Service Fish and Aquatic Conservation program's Arcata office in coordination with Oregon State University's John L. Fryer Aquatic Animal Health Laboratory annually collects information on abundance of polychaete worms and infection rates of C. shasta for three reaches on the Klamath River from below the Shasta River confluence to the Scott River confluence. These are all of the monitoring transects.