CEL 899 Term Paper on
“Microbial Risk Assessment for Ebola Virus”
Prepared Under the Guidance Of
Dr. Arun Kumar
Asst. Professor IIT Delhi
Submitted By
Madhur Chachondia, Entry No. 2014CEV2586: Abstract, Introduction, Types
of Ebola, Exposure Routes (Fault Trees), Risk Assessment Matrix, Future Scope
Helish Lokesh Sharma, Entry No. 2014AST2288: Hazard Identification, Types
of Ebola, Dose-Response Curve, Model Fitting, Risk Comm. & Mgmt, Limitations
Yogesh Gurnani, Entry No. 2014CEV
• Ebola virus disease (EVD) is a severe, often fatal illness in humans. The virus is
transmitted to people from wild animals and spreads in the human population
through human-to-human transmission. The average EVD case fatality rate is
around 50%. Case fatality rates have varied from 25% to 90% in past outbreaks.
The first EVD outbreaks occurred in remote villages in Central Africa, near tropical
rainforests, but the most recent outbreak in West Africa has involved major urban
as well as rural areas.
• Ebola virus has emerged as a deadly disease today especially in the West Africa
killing thousands of people and thus been declared as an emergency by the World
Health Organization. This present day hazard thus has been identified and its
various exposure routes has been and there assessment has been done in this
paper. The fault tree diagrams showing the failure model has been depicted for
the various cases and also the risk assessment matrix particularly pertaining to
the West Africa is shown. The major world health agencies concerned for the
increasing Ebola death counts as depicted by exponential model fitting for the
disease. This control of the disease could only be done by developing the vaccine
and the cure for it from the support of developed markets which will ensure a
safer future for all.
Exposure Assessment : Fault Trees
• The average EVD case-fatality rate is around 50%. Case fatality rates have varied
from 25% to 90% in past outbreaks ([2] WHO 2014b).
• Exposed Populations are Front-line Health Workers, village residents and urban
city residents. Foreign nationals are under remote risk of infection via
transmission through flights/trains across borders.
• The Risk Assessment Matrix shows the various priority levels of the risk
associated with Ebola infection, which seems to be very high in the West African
region. The priority level would be less for developed countries like USA and
European countries. In India, we can expect it to be in moderate to low risk zone,
because there very less probability of Ebola eruption here. If once erupted, it may
reach to moderate to high level, due to inadequate medical infrastructure.
• The medical services include: rapid detection of cases of disease, contact tracing
of those who have come into contact with infected individuals, quick access to
laboratory services, proper care and management of those who are infected and
proper disposal of the dead through cremation or burial. [4]
• Prevention includes limiting the spread of disease from infected animals to
humans. It also includes wearing proper protective clothing and washing hands
when around a person with the disease. Samples of body fluids and tissues from
people with the disease should be handled with special caution. [WHO]
Model Fitting
• DATA: Ebola data for the
three worst-affected
countries (Guinea, Sierra
Leone and Liberia) was
compiled from World
Health Organization’s
“Disease Outbreak News
and Situation Reports”.
Total cases and deaths
were used to make a
model for forecasts. The
data include confirmed,
probable, and suspected
Total (Exponential Fit)
Expon. (Cases)
Expon. (Deaths)
y = 88.072e0.0226x
R² = 0.9869
y = 60.358e0.0207x
R² = 0.9874
X-AXIS: No. of Days starting from 22-Mar, 2014
Results and Discussion:
• From fault trees, we can say that the dangers are high for Health Workers in
Ebola-affected areas. Whereas, in developed countries (like USA), the chances of
a case in the developing world turning into an outbreak are remote. That’s
because they possess the knowledge and tools necessary to stop Ebola.
Unfortunately, many of these tools are missing in African’s poor health
systems and therefore the epidemic has almost spun out of control.
• Also, we saw that the exponential model fits the current scenario quite well. This
means that if not contained soon, it may lead to over 1 lac cases by Feb-15
(based on Expo. Model)
• Extrapolating current trends in increase of cases to forecast all future cases might
not be appropriate.
• Other random factors such as a spontaneous change in contacts with ill persons
or dead bodies or substantial movement within countries or across borders
could alter future growth patterns.
• Therefore, any projections made using these models can be safely applicable to
shorter durations (approx. 3 months).
Future Scope
• From this review we can have various future research scopes. As we have
seen that Ebola is a deadly disease which is actually killing thousands of
people across the globe especially in the West Africa. But still there has
been no proper treatment developed and even no vaccination is still
available .The reason for that is that since the Ebola virus has been
confined to the poor African countries historically when first developed
four decades ago for the first time, thus the R&D (research and
development) incentive is virtually non-existent as a profit-driven industry
does not invest in products for markets that cannot pay. Thus after this
assessment showing higher risk for the individuals major research work
needs to be carried out to develop the cure for this deadly disease.
• Another major problem is substantial under-reporting of cases and
deaths. According to WHO, actual cases may be as high as 2 to 3 times the
current data. Still, analysis of trend as done here may be useful for
containing the spread of this outbreak.
• Also we do not know the uncertainty in the WHO data yet.
1. World Health Organization, Africa Regional Office (2014), “Ebola virus disease in Guinea”,
Available at <>
2. World Health Organization, Geneva, Switzerland (2014), “Ebola virus disease outbreak—West
Africa:, Available at <>
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Liberia and Sierra Leone, 2014–2015”, Morbidity and Mortality Weekly Report (MMWR),
September 26, 2014 / 63(03);1-14
4. Michael Washington, Charisma Atkins, Martin Meltzer (2014),“Generic Ebola Response (ER) :
modeling the spread of disease impact & intervention”, Centers For Disease Control & Prevention
(CDC) Public Health Publications, September 2014
5. Shaman J. Columbia (2014), “Prediction of infectious diseases: Ebola forecasts”, Columbia
Mailman School of Public Health. Available at <>
6. Lt. Col. Christian Janke (2014), “2014 Ebola Outbreak West Africa Risk Assessment”, NATO
MilmedCoe Deployment Health Surveillance Capability Branch
7. Centers for Disease Control and Prevention (2014), “Ebola outbreaks 2000-2014”
8. David S. Fedson (2014), “A Practical Treatment for Patients with Ebola Virus Disease”, Journal of
Infectious Diseases Advance Access published August 25, 2014
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Hu, Adriano Nicolucci, Saad Ahmed, James W Yoon, Isha Berry, Simon I Hay, Aranka Anema, Andrew J Tatem, Derek
MacFadden, Matthew German, Kamran Khan (2014), “Assessment of the potential for international dissemination of
Ebola virus via commercial air travel during the 2014 west African outbreak”, The Lancet, Early Online Publication, 21
October 2014. doi:10.1016/S0140-6736(14)61828-6
10. Bryan Lewis, Caitlin Rivers, Stephen Eubank, Madhav Marathe, and Chris Barrett (2014), “Modeling the Ebola
Outbreak in West Africa, 2014 August 11th Update”
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Nichol, Thomas G. Ksiazek, and Pierre E. Rollin, (2014), “Assessment of the Risk of Ebola Virus Transmission from
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12. Allen G.P. Ross a,Remigio M. Olveda b Li Yuesheng c 2014 “Are we ready for a global pandemic of Ebola virus?”,
International Journal of Infectious Diseases, Volume 28, November 2014, Pages 217–218
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Leone and Liberia. PLOS Currents Outbreaks. 2014 Oct 31. Edition 1. doi: 10.1371/currents.outbreaks
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