LF307:One World Health
and Neglected Tropical
Diseases
, LECTURE 1: ONE WORLD HEALTH AND NTDs
One world, One health
There is an overlap with human population health, wildlife, animal and
ecosystem population health. 75% of the earth’s surface has been altered
by humans for agricultural purposes, we have lost huge numbers of forests,
biodiversity, extinction rate of species is happening at x100 times more than
the normal rate of extinction due to human distraction. This has an effect on
plant growth along with soil conditions and health that will affect Human
Resources, such as food and antibiotic resources. So there is no one
discipline that can tackle all these problems. So the research is commonly
collaborative and multidisciplinary and one of the concepts that has originated through WHO
collaboration with OIE and FAO is to try and keep vigilant as to conditions that can arise, such as
pandemics.
History of Pandemics
On the right hand side we have the timeline from the beginning
of the 1st venture until the current times. The sizes of these
“balls” indicate the numbers of deaths that have been attributed
to these different pandemics. These need to be taken into
account in terms of the population size at the time. So at the
beginning of the chart there were around 200 million people in
the world, moving to the 1800s when the population was around
1 billion and currently the earth’s population is 7.8 billion and is
rising. So the sizes of these bags are relative to the population
size at the time of the pandemic. So if we see the “Antonine
Plague” in the 1st century, it was brought by the troops of the
Roman Empire when they returned to Rome from the Near East.
They brought back plague, which was probably measles or
smallpox. Around 2,000 people would die every day as a result.
Plague was a term used to describe the outbreaks of various
pathogens because it was only until recently that people understood the causative agents of the
pandemics and disease outbreaks. If we see the “Justinian plague” it was caused by Yersinia pestis,
and was transmitted by fleas that lived on rodent species. It evolved from Yesrinia tuberculosis
which was already existing and was transmitted from infected soil and water. If we see the “Black
Death period”, in the Middle Ages, it was caused by Yersinia pestis again and caused 30-50% of the
EU population to die, 25 million in Asia and many more in other parts of the world. The very high
mortality rate is attributed, not so much to the infection via fleas, but the clinical outcome which was
a pneumonic form of plague that got into the airways and the lungs and respiratory tract and was
transmitted through aerosol routes from human to human. And the fatality rate of pneumonic plague
is 60% whereas bubonic plague has a case mortality of 13%. In bubonic plague the symptoms
include swollen lymph nodes and becoming black. During the “Spanish flu” it had an avian origin
from the USA or China. It is associated with France and the UK due to warfare in the WWI. It killed
more people that the WWI. The main point of this graphic presentation of pandemics, is that 75% of
emerging diseases are considered to be of a zoonotic origin.
, Human Zoonotic Diseases
- It is an infection or a pathogen that can be transmitted between
humans and animals. It can be considered as a zoonotic disease,
as there is an animal reservoir organism and the humans become
infected when they are involved in the transmission cycle between the animal host and the vector, or
animal to animal, or it could be of animal origin.
- More than 61% of human pathogens are zoonotic
- &5% of all emerging pathogens such as Ebola, HIV and Influenza virus are of zoonotic origin.
List of recently emerging zoonotic infectious diseases of humans
What are the main causes of all these emerging the
!
- Ebola
- Pandemic Influenza (Avian Influenza) last decades?
- HIV/ AIDS
Population pressure results in growing population
- West Nile virus
and results in usage of wildlife habitat for human
- Severe Acute Respiratory Syndrome (SARS)
needs, which makes transmission easier due to
- Monkeypox Virus
closer proximity. Growth of population means that
- Bovine Spongiform Encephalopathy (BSE)
there is more overcrowding which improves the
- Rift Valley Fever
ability of the pathogen to transmit. Reduced hygiene
- Non Human primate malarias
and poor diet which increases susceptibility to
- SARS, MERS, COVID-19
infectious disease.
- HIV/ AIDS for example, emerged in the early 1980s and HIV-1 was the main cause of AIDS. It
emerged from chimpanzees in Cameroon and cause 60 million infections and 25 million deaths.
Spillover infection: non-human primate (NHP) malarias transmission to humans
- 4 Plasmodium species are infectious to humans and
can cause malaria disease.
- There are around 250 Plasmodium species that infect
birds, lizards, snakes and other mammals.
- Malaria in humans causes 200 million cases/ year and
0.6 million deaths/ year.
- We can see at the top graph that the rate that new
Plasmodium species are infecting has been increasing.
We can see that some of those lines (continents),
especially Africa, has not reached a peak (plateau) yet.
- At the bottom graph we can see the recent example of
the wildlife transmission cycle of Plasmodium knowlesi,
between macaques and and South East Asia and
Anopheles introlatus mosquitos.
- In Malaysia we can see that the prevalence of human
infection is 58% with rapid 10-fold increase from
2004-2011. More recently, (2017) 81% of diagnosed
cases were due to this specific plasmodium species,
which is now considered to be the 5th human species of plasmodium causing malaria.
, Infectious Disease Epidemiology
- Non infectious disease: Individual’s risk of disease are essentially independent. Eg. Cancer, CVD
- Infectious disease: Individual’s risk of infection and disease is dependent on everybody else’s infection
status. This happens because of transmission from one human to the other. Interventions, such as
vaccines can change risk rate for those people who are un-immunized. This is herd immunity where
vaccination of a critical proportion of a population, around 80%, you can reach that coverage and
depending on the value of R0 you can protect the population part that hasn’t been vaccinated. However
infectious agents are constantly going through changes and they race with the host immune system. So
every few years the flue vaccine is changed in terms of its antigenic contents, in order to keep up with
the changes in the circulating viral antigens in the population.
Effective Reproduction Number, R
- Basic case reproductive number, R0 is the average number of secondary cases of infection arising
from a single primary case, in a completely susceptible population. So at the beginning of a pandemic
for example, like COVID-19 now, the population has no antibodies against the virus, no innate immunity
against the infection and the whole population is considered susceptible.
- After some time in the pandemic, part of the population becomes immune, and so protected by
vaccination or it has acquired the disease and has recovered, meaning that now it won’t be the entire
population that is susceptible. This is called the Effective Reproduction number, R. As it is limited by
the proportion of the population and infectious contacts that are susceptible (x).
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The logic of health interventions is to target the components
R = x*c*p*D, so R = x*R0, where:
based on available tools and transmission form of the
disease and try reduce:
P: probability of transmission
- Number of x through vaccination
c: contact rate
- Number D by treating the person and reduce clinical
D: duration of infectiousness
disease and therefore their infectiousness
x: fraction of susceptible population
-Number c*x (infectious contacts), through isolation or trace.
Using this equation we can work out what R is.
We can see here examples of the R0 (basic
reproduction number), so in the fully susceptible
population. These are region specific examples
so they are not valid for every part of the world. It
is a way to see the differences of the diseases
and compare them of how infectious they are for
example.
