Download I. Disease Ecology

Lesson 2/Week 2.
Medical Geographical Approaches.
Disease ecology approach
Landscape epidemiology
Spatial epidemiology
Medical Geography and GIS
Medical Geography and Historical Demography
I. Disease Ecology
Ecology
• Branch of biology
• Concerned with relations between organisms
and their environment.
Disease ecology
Examines the relationships between populations and the changing
environment
Studies how processes of population interactions support or discourage
disease
One of the crucial tenets of disease ecology is that population,
society, and both the physical and biological environments are in
dynamic equilibrium.
Significant enough stress on this equilibrium can produce cascading
effects on any of the aforementioned components.
The human-environment relationship, if disturbed enough by
major changes in land use, migration, population pressure, or other
stressors can show significant maladaptation, as manifested by the
appearance or diffusion of new diseases.
Much historical work has demonstrated the effects on both Europe
and the Americas of the early widespread contact of the European
explorers.
Maladaptation (examples)
•
•
•
•
•
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Example 1: Increase in the incidence of schistosomiasis following the construction of the
Aswan Dam.
Example 2 Malaria, and other vectored diseases following the Volta River project in
Africa.
Example 3: Malaria following land clearance for rubber plantations in Malaysia.
Example 4: Increases in vectored diseases with the construction of transportation routes in
Brazil.
Example 5: The appearance of Lyme Disease in the United States following the
reforestation in suburban areas in the Northeast.
http://csde.washington.edu/downloads/97-3.pdf
http://scholar.lib.vt.edu/theses/available/etd-05212009-173330/unrestricted/KLD_THESIS.pdf
The diagram above shows the changing ecology of a vector-borne disease in non-epidemic versus
epidemic environmental conditions. The non-epidemic environment has no overlap between the
vectors and humans. The overlap in the endemic environment (dark blue), represents areas of risk
for human infection. Seasonal epidemics can be measured by the variable amount of the overlap
over time and space.”
The triangle of human ecology (see diagram below) focuses on three main
categories of factors that affect the state of health: population, behavior, and habitat.
POPULATION
- biological organism that may carry and host disease.
Genetic susceptibility, age, and gender determine whether or not a host can physically and
emotionally cope with infection.
Genetic risks factors for certain cancers have been described since the time of
ancient Rome.
In 1866, Paul Broca, a French physician, reported ten cases of breast cancer
spanning four generations of his wife’s family.
Recently it has been shown that genetic predisposition accounts for five to ten
percent of ovarian and breast cancers.
http://scholar.lib.vt.edu/theses/available/etd-05212009-173330/unrestricted/KLD_THESIS.pdf
Mary-Claire King and associates, in 1990, localized the first major susceptibility
gene for breast and ovarian cancer on chromosome 17 and have referred to it as
BRCA1.
Since that time BRCA2, which predisposes its carriers predominately to breast
cancer, has also been isolated.
http://www.breastcenter.com/procedures/brca1brca2.php?gclid=CIzgg6iO0aQCFSdtgwodD1lRLQ#screening
A number of genetic disorders occur more frequently in certain ethnic populations.
In the Ashkenazi Jewish population (those of Eastern European descent), it has
been estimated that one in four individuals is a carrier of one of several genetic
conditions
http://www.jewishvirtuallibrary.org/jsource/Health/genetics.html
Also: Sickle-cell anemia, Lactose intolerance.
•
New terminology
“previvor”
Age- Mortality and morbidity increase with age and dramatically
in old age.
“ABSTRACT Patterns of morbidity with age can be schematically represented in three situations:
1) as a progressive illness, such as Alzheimer’s disease, leading to a relatively rapid functional
decline. 2) as a catastrophic event, such as a stroke or hip fracture, leading to a decline in function
with improvement after rehabilitation. 3) as normal aging with gradual progressive functional
decline.”
http://www.ajcn.org/cgi/reprint/55/6/1225S.pdf
Strokes are clearly a disease of elderly people;
75% of strokes occur in those aged 65 and older.
The incidence of stroke rises steeply with age, being 10 times greater in people
aged 75-84 years than in people aged 55-64 years.
Europe 1995: Percentage Reporting Chronic Illness by age (Men)
1.0
0.9
0.8
0.6
0.5
0.4
0.3
0.2
0.1
0.0
17
-2
0
21
-2
5
26
-3
0
31
-3
5
36
-4
0
41
-4
5
46
-5
0
51
-5
5
56
-6
0
61
-6
5
66
-7
0
71
-7
5
76
-8
0
81
-8
5
86
-9
0
Probability
0.7
Age
DE
DK
NL
BE
LU
FR
UK
IR
IT
GR
ES
PT
AU
FI
SW
EU
www.enepri .eu/files/AHEAD/AHEAD.../WPI-WPII-ESRI.ppt
Percent of population aged over 65 years (men and women)
17
16
15
14
B ulgari a
E stoni a
H ungary
P oland
S lov akia
13
12
11
10
9
8
197 0
19 80
19 90
2000
201 0
Total fertility rate
2.5
Hungary
Poland
Slovakia
Bulgaria
Estonia
2
1.5
1
1970
1980
1990
2000
2010
L i f e e x p e c t a n c y a t b ir t h , m e n a n d w o m e ( y e a r s )
75
74
73
72
B u lg a r ia
E s to n i a
H un ga ry
P o l an d
S l o v a k ia
71
70
69
www.enepri.eu/files/AHEAD/AHEAD.../WPI-WPII-ESRI.ppt
BEHAVIOR : Observed activities among a populations.
68
67
• Cultural aspects,
66
1 9 70
•
19 80
1 99 0
2 00 0
2 0 10
Gender: Some diseases are gender-specific. Females have a higher life-expectancy
than males but have greater morbidity rates in most countries of the world.
•
•
•
•
Crash fatality rates are higher among teenage boys than girls.
US women had 2.8 times that Chlamydia infection rate of men in 2008.
In the UK men have at least two times higher death rates than women for suicide,
homicide, accidents and cirrhosis of the liver.
In Russia, the difference between male and female life expectancy is 13 years (59 vs. 72).
Life Expectancy at Birth by Sex, 2007
Source: C. Haub, 2007 World Population Data Sheet.
Men's risky behaviors contribute to higher mortality rates
In developing countries the gender gap in mortality has been smaller
than in developed countries. Environmental factors such as unsafe
water and inadequate nutrition increase the death rate due to infectious
diseases for both sexes.
Women, however, face additional risks associated with childbirth.
High maternal mortality in sub-Saharan Africa.
Higher suicide rates among women in China.”
Another reason the smaller gender gap in mortality in developing
countries is the lower social status women.
As women's status catches up with men's in these countries, the gender
gap is expected to increase in the developing nations.
But in developed countries, the gender gap is expected to decrease as
women adopt unhealthy behaviors similar to men's—drinking and
smoking more, experiencing more job-related stress.
http://www.prb.org/Articles/2007/genderdisparities.aspx
HABITAT:
Cultural habitat:
Example 1: Child marriage
The vast majority—of sexually active girls aged 15–19 in developing
countries are married.
Child marriage remains a fact of life in largely rural regions in South
Asia, Latin America, and, crucially, in many sub-Saharan countries that
have HIV prevalence above five percent in populations of women
attending antenatal clinics (defined as a mature and generalized
epidemic).
If present patterns continue, in the next decade over 100 million girls
will be married before age 18; approximately one in seven of these girls
will be under age 15.
In Kisumu, Kenya, 31 percent of male partners of married girls aged 15–19 are
infected with HIV, compared to 12 percent of partners of unmarried girls of the same
age. The age gap between spouses may, in some settings, further intensify the
power differential between husbands and wives, discouraging the open
communication required to ensure voluntary counseling and testing (VCT), sharing
of results, and planning for safe sexual relations throughout marriage
Girls who have become widowed, divorced, or abandoned may be at
particularly high risk of HIV, either because of the nature of their
marriage or the substantial social exclusion and economic risk they face
post-marriage.
In Uganda, 17 percent of previously (but not currently) married girls
aged 15–19 were found to be HIV positive, a rate five times that of
sexually active unmarried girls and four times that of currently married
girls.”
http://www.popcouncil.org/pdfs/TABriefs/PGY_Brief11_ChildMarriageHIV.pdf
Example 2. “Culture of drugs”: US
Example 3. Patterns of movement/migration and disease spread
“Disease has frequently followed those pulled to new destinations by
opportunity, better conditions, or simple inquisitiveness;
or pushed from their homes by events, calamity, or chaos.
The ebbs and flows of populations have often involved a connection
between different environmental, socioeconomic, genetic, biological,
or behavioral conditions that existed between the migrant and host
populations.
The dynamic interaction of the populations and the determinants of
health influenced and changed those who were migrating as well as the
populations hosting the migrants.
“Experiences involving disease and migration have been woven into
humankind’s social, cultural, and medical history.
Remotely, epidemics of plague, cholera, leprosy, and syphilis, and
more recently, HIV/AIDS, viral hemorrhagic fevers, severe acute
respiratory syndrome (SARS), and swine influenza H1N1 have defined
policy responses to protecting regional interests in economics, trade,
security, and health.
Detailed historical and scientific discourses regarding the origin of
disease and its introduction into previously unaffected parts of the
world have continued for centuries.
Several of the public health and infectious disease challenges facing
today’s increasingly integrated and globalizing world have similarities
in context to situations involving migration, illness, and disease that
have occurred in the past.”
http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=nap12758&part=ch1
Example 4. Implementation of disease prevention and control
Example: Eastern Europe
www.enepri.eu/files/AHEAD/AHEAD.../WPI-WPII-ESRI.ppt
• Strong observed relationship between self-reported health status and
age for both men and women, but gradient varies a good deal across
countries
• Controlling for socio-economic characteristics substantially reduces
age-health relationship
• Substantial variation in degree of remaining “age effect” across
countries
• Number of visits increases markedly with age in every country, but much
more in some than others.
• Controlling for socio-economic characteristics flattens this relationship, so in
some countries very modest age “effect” remains.
• Increasing age is associated with worse self-assessed health in a cross-section;
partly due to socio-economic composition.
• Increasing age is also associated with more use of health services, much of
this is attributable to socio-economic composition.
Natural habitat:
Topography, land cover, land use, climate, and weather patterns
Example 1. Altitude
As you ascend to higher altitudes, atmospheric pressure decreases,
The air is thinner and less oxygen is available.
It is also colder and drier
Ultraviolet rays from the sun are stronger.
Each of these changes affects the body.
On the plus side, research is showing that people living at high elevations
have longer life spans (study from Greece) than their counter parts at low
altitudes. Most of humanity lives at low altitudes.
Example 2: Aspect (windward vs. leeward)
“Land and fresh water, two of the most valuable resources in the Hawaiian Islands, came under heavy
demand by influential developers and agro-businessmen. By the 1920’s, large sugar corporations such as
American Factors (AMFAC) and Alexander and Baldwin had covered more than half of the arable land on
Oahu with sugar cane crops. While these corporations favored the optimum growing conditions of Oahu’s
leeward side, irrigation remained a prime concern. The island’s aquifers occupied much of the windward
side (the island of Oahu being transected by a central mountain range separating the windward and leeward
sides). In a massive hydro-engineering attempt, tunnels were bored through the Koolau Range in order to
divert natural water flow from the windward to the leeward side of Oahu. The resulting
effects were catastrophic for windward Oahu subsistence farmers. Water supplies from natural aquifers
dwindled, causing a host of ecological and environmental upsets.”
“Because of these conditions, displaced subsistence farmers sought out a livelihood within the city. This
drastic change from rural to urban life brought about a switch in overall lifestyles as well. Urbanized
conditions translated into dietary changes, one of the major downfalls of Native Hawaiian health standards.
Pre-processed foods, high in protein, fat and cholesterol became a staple of the Native Hawaiian diet due to
the fact that access to traditional food staffs became severely limited. These dietary changes soon equated to
higher obesity rates, which then led to associated health problems.”
http://www.iiirm.org/publications/Articles%20Reports%20Papers/Risk/NatvHwnHealth.pdf
Example 3. Effects of land use, climate, and weather will be discussed in forthcoming
chapters.
http://scholar.lib.vt.edu/theses/available/etd-05212009-173330/unrestricted/KLD_THESIS.pdf
Social habitat: Family, friends, cultural, and spiritual influences.
The social environment consists of the groups, relations, and
societies within which people live
The social environment includes the
Groups to which we belong,
Neighborhoods in which we live,
Organization of our workplaces,
Policies we create to order our lives.
The social environment influences disease pathways.
The research that needs to be done could benefit from a long tradition in
sociology and sociological research that has examined the urban
environment, social areas, social disorganization, and social control.
http://www.annualreviews.org/doi/abs/10.1146/annurev.publhealth.20.1.287?journalCode=publhealth
*** Social determinants of health
Read: http://www.euro.who.int/__data/assets/pdf_file/0005/98438/e81384.pdf
Built habitat:
Include the buildings we live in, work at, and travel within
during our daily activities (construction materials, sanitation and waste disposal,
water sources, building design, air flow and lighting, health care facilities, and
transportation).
Settlement types: urban vs. rural
Rural: Dispersed, nuclear, linear
Less developed countries (LDC):
Interventions to improve environmental health:
• Infrastructure -- e.g. water supply, water storage, latrines, improved drainage
Latrine coverage in community is important determinant of health outcomes
whether a particular household has a latrine or not (e.g. when latrine coverage
exceeds 60% households benefit whether or not they have a latrine)
• Private goods -- e.g. cookstoves (Hillary Clinton’s new initiative), ventilation in
houses, bednets
• Behaviour change -- e.g. hygiene practices, handwashing
In 2002, 23% (2.4 million) of all deaths in Africa were attributed to environmental
risks factors (WHO, 2006). In the same year, 1.03 million deaths were linked to
inadequate water supply, sanitation and hygiene, with an additional 550,000 deaths
being attributed to poor water resource management and unsafe water environments
(WHO, 2008). An additional 40,000 deaths in Africa were related to air pollution
(WHO, 2007).
http://www.unep.org/health-env/pdfs/TD-Traditional-and-current-risks.pdf
Industrialization in poor countries
Rising industrial output is causing water contamination from heavy metals and other
chemicals, and significant increases in salinity and proliferation of water weeds are
becoming increasingly noticeable.
Example Africa
The African urban population is doubling every 20 years,
Increase in the number of vehicles, rapid increase in vehicular
pollutants.
The impact of air pollution on health is seen in the rapid increase in
respiratory illnesses, heavy-metal-related illnesses, and allergies and
skin diseases, which are experienced mostly by children and the
poorest.
Environmental pollution is therefore reducing human productivity in
Africa.
Air pollution in Africa is worsened by the continued use of leaded
gasoline, poor quality fuels, and uncontrolled vehicular emissions.
Of particular concern in African, Asian, and Latin American cities is scavenging in
waste disposal sites, which involves manual sorting of waste to recover sellable or
reusable components, and the handling of waste from health care facilities, which
carries risks of needle-stick injuries and exposure to toxic or infectious materials.
http://www.unep.org/health-env/pdfs/TD-Traditional-and-current-risks.pdf
Developed countries (environmental risks)
Details in forthcoming chapters.
In the news
Bisphenol A (BPA - used to make polycarbonate plastic)
Bisphenol A (BPA) is an industrial chemical that has been present in many
hard plastic bottles and metal-based food and beverage cans since the 1960s.
“Studies employing standardized toxicity tests have thus far supported the safety of current low
levels of human exposure to BPA. However, on the basis of results from recent studies using
novel approaches to test for subtle effects, both the National Toxicology Program at the National
Institutes of Health and FDA have some concern about the potential effects of BPA on the brain,
behavior, and prostate gland in fetuses, infants, and young children. In cooperation with the
National Toxicology Program, FDA’s National Center for Toxicological Research is carrying out
in-depth studies to answer key questions and clarify uncertainties about the risks of BPA.”
http://www.fda.gov/newsevents/publichealthfocus/ucm064437.htm
In the interim:
•
FDA is taking reasonable steps to reduce human exposure to BPA in the food
supply. These steps include:
o supporting the industry’s actions to stop producing BPA-containing
baby bottles and infant feeding cups for the U.S. market;
o facilitating the development of alternatives to BPA for the linings of
infant formula cans; and
o supporting efforts to replace BPA or minimize BPA levels in other food
can linings.
Phthalates (mainly us ed as plasticizers (substances added to plastics to increase
their flexibility, transp aren cy, durability, and lon gevit y).
“Phthalates are nearl y ubiquitous in mod ern so ciet y, found in, amon g other thin gs,
toys, food packagin g, hoses, rainco ats, shower curtains, vin yl floorin g, wall
co verin gs, lubricants, adhesi ves, d etergents, nail polish, hair spray and sh ampoo. ”
“In July 2008, as a result of pressu re fro m EWG and other h ealth groups, the U.S.
Congress p assed legislation bannin g six phthalates fro m children’s to ys and
cos metics. Legislators in Washin gton, Vermont and California h ave restricted
phthalate use in children ’s goods, and several majo r ret ailers, includin g Wal-M art,
To ys-R-Us, Lego, E ven flo and Gerber say they will phas e out phthalate-lad en to ys.”
htt p://w ww .ew g.org/c hemindex/t erm/48 0
Methyl bromide (used as chemical fumigant)
“California strawberry growers were faced with the possibility of losing
one of their most important chemicals, methyl bromide. Methyl bromide
was believed to be involved in the depletion of the ozone layer and 162
countries had signed the Montreal Protocol, which would lead to an
eventual ban of the chemical.”
http://ageconsearch.umn.edu/bitstream/8153/1/0703ba01.pdf
“Results from a two-year study suggest that drip-applied chloropicrin, and 1,3-D may potentially
be economically feasible alternatives to methyl bromide in commercial California strawberry
production.”
http://www.agecon.ucdavis.edu/extension/update/articles/v9n5_3.pdf
Old environmental dangers
(these will be discussed in detail in the forthcoming chapters)
Lead
Asbestos
Sun-beds
Indoor air pollutants
Outdoor air pollutants
Water pollution
Soil pollution
Electromagnetic fields
Cell phones?
Radon, depleted uranium, nuclear accidents(Chernobyl)
Legionellosis
Heath care waste
Climate change
II.
LANDSCAPE
EPIDEMIOLOGY
http://scholar.lib.vt.edu/theses/available/etd-05212009-173330/unrestricted/KLD_THESIS.pdf
The landscape of a place is characterized by a mosaic of habitats within the
ecosystem. The elements and patterns associated with the biotic, abiotic, and
cultural processes within a landscape are used to identify the factors that influence
disease transmission over time and space.
Landscape epidemiology involves the identification of geographical
areas where disease is transmitted.
It is a holistic approach that involves the interactions and associations
between elements of the physical and cultural environments.
First expressed by the Russian epidemiologist Pavlovsky (1966), the
theory behind landscape epidemiology is that by knowing the
vegetation and geologic conditions necessary for the maintenance of
specific pathogens in nature, one can use the landscape to identify the
spatial and temporal distribution of disease risk.
Key environmental elements, including elevation, temperature,
rainfall, and humidity, influence the presence, development, activity,
and longevity of pathogens, vectors, zoonotic reservoirs of infection,
and their interactions with humans.
http://geo.arc.nasa.gov/sge/health/landepi.html
Landscape epidemiology draws some of its roots from the field of
landscape ecology.
Just as the discipline of landscape ecology is concerned with analyzing
both pattern and process in ecosystems across time and space,
landscape epidemiology can be used to analyze both risk patterns and
environmental risk factors.
This field emerges from the theory that most vectors, hosts and
pathogens are commonly tied to the landscape as environmental
determinants control their distribution and abundance.
http://www.iscanmyfood.com/hd/index.php?t=Landscape+epidemiology
“This [PhD] dissertation investigates the confluence of environmental, topographic, and human
determinants of household malaria in two highland communities of western Kenya. Household
case data from 2001-2004 were analyzed for demographic and environmental risk factors using
clinically-derived case information, high-resolution satellite imagery, and digital elevation models
to explore how local topography, land-cover, and land-use influence infection risk. Results
demonstrated that malaria risk in this region is largely determined by strong,
topographically-determined contextual determinants of risk, such as the proximity of houses to
remotely sensed swamplands or, analogously but more specifically, to regions of the landscape
where water can be predicted to collect on the basis of hydrologic models. Household malaria was
also found to be related to human variables related to agriculture, deforestation, and urban density.
These results confirm the importance of considering the environmental context in which malaria
transmission occurs.” http://gradworks.umi.com/32/76/3276118.html
This approach will help identify factors that encourage or
suspend the spread of disease,
Has been used to define the geographic boundaries and
pathways of transmission, for diseases such as the plague,
malaria, dengue, and schistosomiasis.
Public health officials evaluate the epidemiological pathways
to determine if landscape modifications can be used to block
the route of transmission of a pathogen for the prevention or
control of the disease caused by it.
There are six basic observations that define the concept of landscape epidemiology:
I.
II.
III.
IV.
V.
VI.
The geographic distributions of diseases tend to be limited;
Variations in physical and biological factors that support the virus, vectors,
and reservoirs may cause spatial restrictions or barriers;
If the conditions of the supporting factors can be captured on maps, then
the current and future risk should be predictable.
The important environmental factors are determined from the examination
of the biome and natural nidus of a region where disease activity exists.
Identified by its distinct plants, animals, insects, and microbes, a biome is a
broad biotic region that is highly predictable based on climate, altitude,
and latitude.
The natural nidus is the habitat composed of the vectors, hosts, and
reservoirs involved in a continuous cycle of transmission that sustain a
pathogen within an ecosystem.
By evaluating the biogeography of the vector and host life cycles, the distribution
and the factors associated with transmission of diseases can be determined.
Temperature, precipitation, topography, land use, and land cover, will be carefully
reviewed to identify the factors and possible barriers that affect the transmission of
disease under changing environmental conditions.
III.
SPATIAL
EPIDEMIOLOGY
http://www.ecostudies.org/reprints/Ostfeld_et_al_2005_TREE_20_328-336.pdf
Spatial epidemiology is the study of spatial variation in disease risk or
incidence.
Several ecological processes can result in strong spatial patterns of such
risk or incidence including the following:
Pathogen dispersal might be highly localized,
Vectors or reservoirs for pathogens might be spatially restricted, or
Susceptible hosts might be lumped.
Pathogens use many different modes to disperse from an infected to an
uninfected host.
Some modes involve direct contact (e.g. pathogens transmitted during
aggressive or sexual encounters), some involve near-direct contact (e.g.
pathogens excreted by one host and inhaled or consumed by another),
whereas others rely on an arthropod vector.
In most cases, the probability of transmission declines dramatically
with distance from an infected host.
As a consequence, factors affecting the spatial positions of pathogens,
hosts and vectors, and their probability of close encounter, are
fundamentally important to disease dynamics.
Spatial epidemiology has arisen as the principal scientific discipline
devoted to understanding the causes and consequences of spatial
heterogeneity in infectious diseases, particularly in zoonoses (i.e.
diseases that are transmitted to humans from non-human vertebrate
reservoirs).
Mapping spatiotemporal dynamics of disease
Spatiotemporally dynamic analyses require that data on disease incidence be highly
precise, both in space and time, and also require sophisticated spatial models to
describe patterns in detail. When these requirements are met, the approach appears
quite useful for targeting disease prevention or treatment in space and time and
epidemiological maps can be drawn.
Maps have been used for two distinct purposes in epidemiology.
I.
Retrospective analyses of spatiotemporally dynamic epidemics to
understand what factors govern the spatial pattern and rate of spread of
diseases. For example, a spatiotemporally dynamic approach was used to
research foot and mouth disease (FMD) in cows and sheep in the UK
during the 2001, FMD epidemic.
“The effectiveness of alternative culling strategies was predicted by using
epidemiological models in which farms of different sizes (number of livestock),
species composition (cattle only, sheep only, or mixed), and infection status
(infected or susceptible) were mapped. The spatial clustering and spread of
FMD, combined with the observation that larger farms containing both cattle
and sheep were most susceptible, were used to model local and long-distance
transmission rates. These results were used to predict how different control
strategies (prophylactic vaccination, reactive vaccination, or culling) would
impact FMD epizootics. The models showed that vaccination programs could be
effective if they were spatially targeted and quickly followed FMD detection;
however, for political reasons, culling was the strategy used, in this instance, to
stop the epizootic. Spatiotemporally dynamic approaches have also been used to
describe the characteristics of ‘traveling waves’ in epidemics of measles and
dengue hemorrhagic fever.”
II.
To characterize spatial variation in contemporaneous (static) ecological
risk of infection and potential causes of that variation. Ecological risk can
be defined as the probability of exposure to an infection in the absence of
active preventative measures.
Efforts to create risk maps pertaining to specific diseases have increased in recent
years, and these can be categorized as being based on distributions of arthropod
vectors, vertebrate reservoirs, or actual cases of disease in the host, usually in
humans. Irrespective of the focal entity, the most common procedure is to:
(i)
(ii)
(iii)
(iv)
Construct distribution maps of the vector, reservoir, or disease;
Use remote-sensing data and geographical information systems to
characterize the distribution of abiotic conditions and sometimes
vegetation that might influence the vector or reservoir;
Select remote-sensing variables that are most strongly associated with the
distribution of the vector, reservoir, or disease; and either
Project the distribution of the identified remote-sensing variables to make
predictions about disease risk beyond the current map; or
(v)
Guide the imposition of interventions, such as pesticide application or
vaccination.
Because arthropod vectors, vertebrate reservoirs and cases of disease in humans
represent distinct challenges for the mapping of disease risk, each approach is
discussed in turn.
Risk mapping based on vectors
Important facts to remember:
1. Demographic rates of arthropod vectors of human pathogens tend to be
sensitive to variation in temperature and moisture.
2. Cold temperatures induce mortality or diapauses (delay on
development), or reduce host-seeking activity.
3. Similarly, rainfall creates habitat for breeding (e.g. for mosquitoes and
midges), and high humidity is necessary for survival of some insect and
tick vectors.
4. The dependence of vectors on specific abiotic conditions, combined
with advances in remotely sensing and mapping variation in abiotic
conditions, has stimulated efforts to create risk maps for vector-borne
diseases.
5. From an almost infinite number of abiotic variables that can be
spatially referenced on maps, typically a subset is chosen and
confronted with data on presence versus absence or abundance of
vectors.
6. Those abiotic variables showing the greatest degree of spatial
concordance with vector distribution are assumed to be causative and
are often used to predict current distributions of vectors in unstudied
areas or future distributions under different scenarios of climate
change.
Limitations to this approach fall into two major categories.
I.
Disease risk or incidence is more closely correlated with the abundance of
pathogen-infected vectors, rather than with simply presence of vectors, or
total abundance of vectors. For instance, Lyme disease in North America
is largely restricted to the northeastern and upper Midwestern USA in spite
of widespread populations of the tick vector in southeastern and lower
II.
Midwestern regions. The invasion of North America by West Nile Virus
appears unrelated to changes in the distribution or abundance of
mosquitoes, but rather with changes in the distribution of the virus in
vectors and avian reservoirs. Only in rare cases is the abundance of
infected vectors used to create maps of risk.
Such studies are fundamentally correlational, so that the direct causal
relationship linking environmental conditions to vector distribution or
abundance remains to be established.
Risk mapping based on reservoirs
Important facts to remember:
Example 1. Hantavirus pulmonary syndrome:
Less commonly, risk maps are created from distributions of wildlife
reservoirs for human pathogens.
Such efforts have been most successful in predicting the risk of directly
transmitted zoonoses, such as hantavirus pulmonary syndrome.
Abundance of the deer mouse Peromyscus maniculatus reservoir in the
southwestern USA is predictable from plant community composition
(pine and oak abundance, which is determined with the use of satellite
imagery), and hantavirus pulmonary syndrome cases, in turn, are
predictable from mouse abundance.
Recently, GIS modeling combined with statistically robust measures of
spatiotemporal clustering of epidemiological events demonstrated that
the locations of dead American crows Corvus brachyrhynchos around
New York City during 2000 could be used to predict the locations of
human victims of West Nile virus during 2001. Five of seven human
cases of West Nile encephalitis occurred in areas designated high or
medium risk based on crow mortality. American crows are frequently
killed byWest Nile virus, although their status as a wildlife reservoir
remains unknown.
In a retrospective study of hantavirus pulmonary syndrome in the
southwestern USA, areas of high incidence could be identified on the
basis of both Landsat Thematic Mapping bands, representing soil type
and moisture, and vegetation structure. Satellite data could then be used
to predict locations where outbreaks were expected.
Example 2. Malaria
Rogers and Randolph mapped the worldwide distribution of
falciparum malaria to derive the multivariate (temperature,
precipitation and vapor pressure) abiotic boundary conditions
within which malaria occurs. They then projected the future
distribution of those boundary conditions according to climate
projections to predict the future distribution of malaria.
Rogers, D.J. and Randolph, S.E. (1991) Mortality rates and population
density of tsetse flies correlated with satellite imagery. Nature 351,739–741
Their projections, based on climatic conditions correlated with
human malaria cases, suggested a much smaller increase in cases
of malaria with global warming than did projections based on
climatic conditions correlated with mosquito distributions.
http://www.ecostudies.org/reprints/Ostfeld_et_al_2005_TREE_20_328-336.pdf
Example 3: LaCrosse Encephalitis
For LaCrosse encephalitis in Illinois, Kitron et al. used GIS and spatial statistics to
identify physical features such as gullies and ravines, which often contain both
natural and artificial breeding sites for mosquitoes, as major risk factors. Most cases
of LACV disease occur in the upper Midwestern and mid-Atlantic and southeastern
state.
Example 4: Onchocerciasis and Schistosomiasis:
About 50% of the variation in onchocerciasis incidence among West African
villages was explained by variation in forest cover and landcover class, with little
explanatory power of rainfall, temperature, or soil. Satellite-determined normalized
difference vegetation index (NDVI) was a strong predictor of schistosomiasis
distributions in Bahia, Brazil.
Caveats and future directions
The overarching question for spatial epidemiologists is whether disease risk or
incidence can be explained by (or predicted from) the distribution of vectors,
reservoir hosts or human cases. But distribution is a difficult concept. Creating
distribution maps based on presence or absence (i.e. boundary conditions) is
relatively simple, but excludes potentially crucial information about abundance of
vectors, cases, and so on, within their range. Even when the abundance of vectors,
reservoirs, or disease incidence are mapped, misleading results might occur if:
(i)
(ii)
(iii)
(iv)
Vector infection varies spatially (e.g. Anopheles mosquitoes are abundant
in large geographical areas with no malaria because the Plasmodium
parasite has been eliminated), destroying an assumed correlation between
simple vector abundance and disease risk.
The abundance of vertebrate reservoirs is highly dynamic spatially or
temporally, which could lead to significant variation in risk that would be
invisible to cross-sectional mapping exercises.
Vertebrate reservoirs are less strongly (or simply) delimited by climatic or
vegetation variables that can be remotely sensed and organized with GIS.
The disease system is in disequilibrium; for example, when vector or
pathogen range is expanding. In the case of an expanding range, the
assumption that the vector or pathogen lives everywhere it can currently
live is violated and, therefore, projecting future distributions is
compromised.
“The importance of landscape composition (number and types of patches) and
configuration (spatial relationships among patches) to disease dynamics is only
beginning to be explored. Landscape structure has a strong potential to influence
disease dynamics through impacts on both abiotic conditions and species
interactions that are important to disease spread and prevalence. For instance, by
reducing or eliminating predators on disease reservoirs, fragmentation could
increase disease risk above that expected from local habitat quality alone.
Pathogens, vectors, reservoirs and hosts are all embedded within ecological
communities within which they interact directly or indirectly with many other
species. As diseases invade new areas or change distribution with climate and
land-use change, a major research challenge will be to determine the level of
ecological complexity that is necessary to predict spatial dynamics accurately. At
one extreme is the notion that species (including pathogens) are restricted to
specific abiotically defined niches, which can be accurately mapped and tracked
into the future. At the other is the argument that trophic interactions among
species and landscape structure contribute crucially to current patterns of
abundance and distribution, such that future distributions cannot be predicted
simply by tracking changes in abiotic conditions.”
http://www.ecostudies.org/reprints/Ostfeld_et_al_2005_TREE_20_328-336.pdf
I.V Medical Geography and GIS
Text
pp. 77-93
Map Scales:
Small scale – 1:250,000 to 1:1,000,000 or more
Appropriate for continents, realms and other large regions.
Medium scale – 1:25,000 to 1:250,000
Appropriate for states, state economic areas, health service areas,
standard metropolitan statistical areas, and some minor civil divisions
(counties, cities); topographic maps and coverage, satellite coverage of
vegetation, watersheds and geological formations.
Large scale – (1:200 to 1:25,000)
Minor civil divisions (cities, census tracts, etc.); satellite imagery of
transport routes, buildings, agricultural fields, etc.
Types of Maps
Point distribution maps- represent information that has no spatial dimension, but
of course this is a matter of scale.
Flow maps – Lines are used to show direction of movement, often with the
thickness of the line being scalar (proportional to the amount that is moving).
Most commonly, lines are used to connect points and so portray new
information. Isolines (also known as isotherms or isarithms) can connect
points of equal value. These are most familiar as lines of equal altitude
(contour lines).
Area maps – Area information is symbolized on thematic maps by shades, patterns,
or colors covering the area and symbolizing the class or category to which the
information category belongs. This kind of map is known as a choroplate map.
A map made well can communicate a lot of information. The information, however,
can be distorted if the intervals are not appropriate to the data distribution.
Disease maps on the web.
The GIS in conjunction with the World Wide Web, has made it possible to display
disease maps inexpensively and sometimes interactively to a wide audience.
e.g.
apps/who.int/globalatlas
diseasemaps.usgs.gov
V.
Medical Geography and Historical Demography
Medical geography is helping demographers understand ongoing demographic
changes all over the world by allowing trend analysis of mortality rates and the
resulting impacts on population dynamics and demographic transitions.
Examples:
The effects of HIV/AIDS on life expectancy in southern African countries –
South Africa, Zimbabwe, Zambia, etc.
The effect of malaria on childhood survival rates and maternal mortality rates
in Africa and south Asia.
Tuberculosis and its resurgent impacts on adult mortality rates (also,
co-infection with HIV/AIDS)
Sexually transmitted infections and its likely contributions to infertility
The impacts of modern medical procedures on mortality rates and
demographic trends
Historical:
Population growth is a recent phenomenon. For almost all of human history since its
inception w million years ago, world population growth has been negligible. Until
about 1750 high birth rates were matched by high death rates, with periodic
catastrophic losses from famine war and, most importantly, disease.
Examples:
www.nuim.ie/staff/dpringle/mg/mg10.ppt
The Chinese population declined from 123 million in 1200 to 65 million
1393. Due probably to bubonic plague.
In Europe the Black Death killed an estimated 25 million people, reducing the
total population by 25-40 per cent.
England, Italy, France, Poland, Russia and the Balkans are said to have lost 50
per cent of their populations.
Labour shortages hit food production; wage labour was introduced to attract
workers; wages increased.
Cities became more important - growth of the bourgeoisie.
Net effect – collapse of feudalism, beginnings of capitalism.
Pre-Columbian America
By the time Columbus discovered ‘America’ – probably San Salvador in the
Bahamas – there was already a lengthy history of urban civilization in the
Americas.
Olmec civilistion lasted 1200-300 BC.
Mayan civilisation peaked in second half of first millennium AD. Toltecs in
mexico 900-1200.
Aztec and Inca empires in Mexcio and Peru were at their peak in the 15th
century.
Total population of the Americas was about 100 million, with 25-30 million
in each of the Aztec and Inca empires.
• Most of the North America Indian tribes were hunter-gatherers,
but there was a major civilization in the Mississippi valley (mound builders).
• Cahokia’s population had only been exceeded by Philadelphia at the time of
US independence (1775).
Hernan Cortes captured the Aztec empire in 1521 with an army of only 600
Spaniards.
• Francisco Pizarro captured the Inca empire in 1532 with an army of 168
Spaniards.
Why were they so successful?
Smallpox epidemics had occurred in the Spanish West Indies previously, but
a major epidemic arrived from Spain in 1518.
• This killed one-third to one-half of the Arawaks in Hispaniola and then
spread to Cuba and Peurto Rica.
• It was transmitted to Mexico by an infected slave in 1520. Smallpox
killed about one half of the Aztecs, paving the way for conquest by
Cortes.
• Smallpox reached the Incas in 1526. It killed the Inca emperor and his son,
resulting in a civil war.
• Resistance to Pizarro was limited.
• By 1530 smallpox had spread south to the pampas and north to the Great
Lakes.
• When Spanish explorers reached the Mississippi in the 1540s many towns
had already been abandoned, although some still functioned.
• The Mississippi towns had vanished when the French arrived in the 1600s.
• 1529: Measles killed two third of the surviving native population of Cuba,
before sweeping through Honduras, Mexico and Peru.
• 1546: Aztecs and Incas ravaged by typhus.
• 1558-59: Americas hit by influenza pandemic.
• 1589: Peru hit by unidentified disease. Three quarters of the Indian
population of Chile died.
• Diphtheria, mumps, plague, pertussis, scarlet fever, typhoid, typhus, and
tuberculosis followed. Also malaria and yellow fever.
• Pilgrim Fathers in 1620 found a landscape depopulated by smallpox which
arrived via Nova Scotia.
• Population of Mexico declined from 30 million to 3 million in 50 years, then
to 1.6 million by 1602.
• Figures for Inca empire similar: 8 million by 1553, 1million by 1791.
• Main decline was in the first few decades, but it continued into the 19th
century.
• Smallpox killed half the Hurons in 1684. Their enemies, the Iroquois, were
also halved.
• In 1738, smallpox killed half of the Cherokees in the Charleston area.
• In the early nineteenth century, smallpox destroyed two-thirds of the
Omahas.
• In 1837 the Mandan Indian tribe was totally wiped out by smallpox.
• Overall, native populations reduced by about 90-95 percent.
• What was the impact in the opposite direction? Syphilis would seem to have
been the only possible ‘export’.
• Why was there so little impact on Europeans? Amerindians carried very few
infectious diseases to infect Europeans.
• Why were they so free of infectious diseases? No one knows for certain, but
it could be because Amerindians had very few domesticated animals: turkey
(Mexico), llama / alpaca (Andes), guinea pig (Andes), muscovy duck
(tropics), dog (everywhere).
Impact Elsewhere
• 100,000 Guanches in Canary Islands more or less wiped out by 1530s.
• Indian population in Hispaniola declined from 8 million in 1492 to zero by
1535.
• Hawaii’s population was about 500,000 when Captain Cook arrived in 1792,
but it fell to 84,000 by 1853 – the year smallpox killed another 10,000.
• Fiji lost about one-quarter of its remaining population to smallpox in 1875.
• Australian aborigine population declined from about 1million in 1788 to
90,000 by 1901.