Grant Programs for Universities And Research Centers [617223]
Cover Page
Item
Description
Initiative
Grant Programs for Universities And Research Centers
Program
Targeted Research Grant Program
Subject
Infectious Diseases Research Grant Program
Research Field
COVID-19 Research Grant Program
Sub Field
Mathematical modeling of COVID-19 and infection dynamics
Project Title (English)
Modelling and Prediction of COVID-19 Dynamics in KSA
Project Title (Arabic)
͂̀͡͵̯̠̺͙͂௬̗̯̺͙̹͂Ͼ̴̻̻̺͙́
19
̚͡௪̠̻̺͙̼̓͵ͣ͵̹ͥ͵௬̴̓͜௬̹௬̻̼̗͖̗̼̘̓̀͡͵̻̼͂̚͢
Principal Investigator
(English)
HAITHAM MOHAMEDOSMAN ABDELGHAFAR OSMAN
Principal Investigator (Urdu)
ͳ̻̓௫̵̮̲̺͙̗̮ͣ̓͡ͳ̻̓௫̮̻̜̻͡Ͳ௫௬̽
Institution
King Khalid University
For Official Use Only
Date Recieved
09-Apr-20
Proposal Code
1
Item
Description
Project Title
Modelling and Prediction of COVID-19 Dynamics in KSA
Track Field
Infectious Diseases Research Grant Program
Estimated Duration
10 Months
Proposed Starting Date
01/06/2020
Project Information
Project Team
Senior Personnel
No.
Name
Role
Area of Specialization
1
HAITHAM MOHAMEDOSMAN
ABDELGHAFAR OSMAN
PI
Chemical Engineering
2
ABDULAZIZ ABDULLAH BINSAEED
P-CO
3
AHMED KAMALELDEN MOHAMMED
ALMRDI
CO-I
Computer Science
4
MAKKI AKASHA ALBASHIER
CO-I
Computer Science
Other Personnel
No.
Name
Role
Area of Specialization
No Record
Consultants
No.
Name
Role
Area of Specialization
1
Mohamed Elyasa Ibrahim
Consultant
Medical Sciences
2
Eliseo Marcos Guallar
Consultant
Public Health –
Epidemiology
2
English Summary
(250-500 words):
This section should provide a summary of the proposed research project suitable for publication in English and
Arabic languages. The summary must not exceed one page in length and should provide a coherent, clear and
concise description of the research activity that would result if the proposal eventually obtains the funding
requested. It should describe the objectives and methods to be adopted by the proposed research as well as
the expected broader impacts on development and society. It should be informative to other persons working
in the same or related fields and understandable to scientifically/technically literate readers. It should not
contain any proprietary or confidential information
The outbreak of novel coronavirus-caused pneumonia (COVID-
19
) has attracted worldwide
attention, spread across national and international borders leading to systemic complications and
death. Prediction models can provide a powerful tool to forecast the expected number of infections
and deaths and quantify the intensity of interventions required to control transmission.
This study aims to construct a prediction model suitable for describing the dynamics of pandemic
spreading of Coronavirus Disease
2019
(COVID-
19
) in Saudi Arabia. Historical data of infected,
recovered and death cases from official sources will be used for the model fitting.
This project will take place in three phases, The first phase will focus on data analysis, models such
as the Global Epidemic and Mobility Structured Metapopulation Model (GLEaM) and Generalized
(Susceptible. Exposed, Infectious and Recovered) SEIR modelling. to predict future waves to
address the limitations of conventional logistic-growth models that tend to underestimate the peak
timing and duration of the disease epidemic.
Second Phase, will Increase the precision of the models to accumulate more factors and develop
hybrid Artificial Neural Network (ANN) algorithms combined with GLEaM model. ANN considered to
be an effective and powerful technique to compute, predict and classify large volume of data.
Moreover, the ANN has been proved as more versatile and robust compare with logistic regression
model.
correlation, and classification using very sophisticated methods of studying and classifying the
importance of these factors such as: Social spacing, Quarantine, Complete Quarantine, Partial
Quarantine, travel and environment. This data will be modeled by using of epidemic forecasting
Finally, we should improve outputs of mechanistic and phenomenological methods for disease
predictions, to be completely implemented by public health authority's decision makers and other
stakeholders.
3
Arabic Summary
(250-500 words):
This section should provide a summary of the proposed research project suitable for publication in English and
Arabic languages. The summary must not exceed one page in length and should provide a coherent, clear and
concise description of the research activity that would result if the proposal eventually obtains the funding
requested. It should describe the objectives and methods to be adopted by the proposed research as well as
the expected broader impacts on development and society. It should be informative to other persons working
in the same or related fields and understandable to scientifically/technically literate readers. It should not
contain any proprietary or confidential information
̺̓͗Ͷ͕̻̻̓͂͡௬̺͵̺͙͡͵͂௬̼ͩ͵̺͙͡͵̡̜̺͙̗̮͡௪̼͙͵̓ ௬̻̺̮̻̻̓̓̓௪͙̽
COVID-19
́̓̚௪̺͙ͥ͵௬̵̺͙ͳ̮Ͳ̼̺͙̺͙̓̀̚̚͡͡ͷ͵̺͙͚̓̾ͅ௪̡̺͙͆ͣ̓௪̼͙͚͢௪͙̚
2020
ͱ̗͕̀
12
̓௪̜̈́ͳ௬̀͡͵̯̠̺͙ͳ̹̠̺͙̓ͳ௬̗௬̡̗̹ͣ̓௪̼͙̺̓͗Ͷ̡͕̻̻̓̈́ͣ̓͡௪̵̼͙̼͙͆ͥ̿̚͵̵̘̠̼̓̾͂̀͡͵̯̠̺͙̚͜͡͵̴͛̓͵̺͙͵̵̮̭̻͂̀ͤ̓̾̓̓̚͜
̻̼̺̓͢͞ͳ̢̡̹̻̞̀̓
52
̺̓͗̓͜௬̴͵̺͙̺̻́̓͗̚ͱ̢͵͵̈́͂̀͡͵̯̠̺͙͂௬̗̯̺͙̹͂Ͼ̴̻̻̺͙́
COVID-19
̢̗̗̺̜ͭ͂̓͗͂̓
4033
̮̿͵̻̻̻̓̚͡௬̹̘̔Ͳ̘̈́
ͱ̸̓௪̴̼͙͆́Ͳ̹̜௪Ͼ̺̗͂͵Ͼ̻̺͙͇̞ͩ͜͡௪̴̺͙͂̓௫̹̜̘̀͡͡͵̓͜௬̴͵̺͙͵Ͷ͵̯͡Ͼ̷̺̰͵௪̻̺͙̯̺̗͖̗̼̓͡͡௪Ͼ̺͂̀͵̷̴͙͕͛͡͵̘ͳ͕͖̗̼௪̺͙
̹͂Ͼ̴̻̻̺͙́
COVID-19
)
2019
̼̓͵ͣ͵̹ͥ͵௬̴̻̺͓̗ͨ̓͵̡̺͙ͣ̓௪̼͙̓͜௬̹௬̢̻̼̓̀ͮ͡͵̺͚̠̼̻̓ͷ͖̗̼̘͢͞͵̻̼͓̼̗̺̠͙̺͙̓̓͗͂ͣ͡ʹ̘̽ͮ̾͢͡
͢͞͵̻̼̺͙͚௬̹௪̺͂௬̢̻̠̺͙̻̺͙ͣ̓͡ͳ̴̻͛̓͵̺͙͵Ͷ͵̯̺͙͡͵̢̗͙̜̺͂̓͆̓͂͜௬̞̀ͣ̓௪̺͙̼̓̓͜௬̗̺͙Ͳ͙̞͡௪̠͙Ͳ௪௬̠͂̀͡͵̯̠̺͙͂௬̗̯̺͙
̠͙̺̲͂ͣ͂̀̓͡Ͼ̸̺̯̻͛ͯͩ͡Ͳ͙̞͡௪̠̗̓ͮ௬̢̼௪̺͙͵̗̘͙ͩ̓ͣ͆͵̼̓̓͜௬̗̺͙ͱ௬Ͼ̜̘̓Ͼ̮̺̓͵͙͋͂Ͼ̜̻̺͙̹௪̠͵̈́ͱ̜͙̻͇̙̓͝Ͼ̮ͫ͵̡̻̺͙͙̽͢͢௬̵̼̘Ͳ௪௬̠
̻̼͂̚͢Ͳ௪௪̠͂ͅ௬̗̺͙͵̵̠̺͙͵̺͙̜̺͙̈́́̚̚ͅ͵̈́ͱ̢̻̹̺͙̜̺͙̜̺͙̓́̚͵̢̜̺͙̜̺͙̈́́̚͵̮̻̈́́̓௪͙̮̗͆̓̚͡௪̺͙ ͱ௫̻ͱ̻͙͵̯̺͙ʹ̽͂͢௬̻͕̽ͮ௬̢̼̘͵
́Ͼ̹௬̺͙̾ͱ̀͵̜௪̺͙͢͞͵̻̼͵ ͡௪̠̻̺͙͵Ͷ̯̻̺͙͡͵ͮ͵̡̹̻̺͙ͱ̻௪̜̻̺͙ Ͳ̻̯̻̺͙͵̻̺̯̺͙͓̗́̓̓͵̺͙͢͞͵̻̼ͱ௫̻̗͂ͅ͵̗͖̗̼͋̓௪̺͙̻̼̓͢͞Ͳ͙̞͡௪̠̗̼̓̓̓͜௬̗̺͙ʹ̽͢
͓̗̓͵̻͛͡͵͛͵̺͙ͣ͢͜௬̷͵̘ͳ̻ͱ௬Ͼ̸௪̺͙̺̓͗ͱ௬̻̘́௪̺͙̻̼̺͙̓͢͞ͷ͡௬Ͼ̸௪̺͙́௪̠̚͵Ͼ̺͙͵̻̼̺͙͡͵௬̷̺̯̻̺͂̓͂̚௬Ͼ̸̗௪̠̻̺͙̓̚͜͵̻̺̗͖̗̼̓௪Ͼ̺
GLEaM
ͱ̸̼௪Ͼ̺
̻̺͙ͨ
̺̗̼̓͗̓̚
ANN
̼͂௬̺͙̾͂̚௬̢̮̼͙̓ͩ͆͂௬̢̡̗̯̺͙̹̗̺͙͂̓͜௬̻͙ͤͣ͵̞̀͵̘ͩ͵ͱ̻͙͵̯̺͙ͳ̻̻̺͙̰̀͡௬̻̚௪̷̺̻̼̺͙̓͂͢͞͡ͳ̻̀͡௪̠̈́͂௬̼̓௫̺͙͂Ͼ̜̻̺͙
ANN
ͳ͕̗̙̈́͜Ͱ̺̓͢Ͼ̮͛͵̵͇̮̿௬̢̼̘͵̗͖̗̼̿௪̺͙͵̼̓̓͜௬̗̺͙ͳ̻௬̗̹Ͳ̜͚̠̜̺̓͂̀̚͵̷͵̴̺̯͂̓͂௬̸̼̘
ANN
̗௪̯̘
GLEaM
͢͞͵̻̼̰̻͚̼̚
́௪̠̚͵Ͼ̺͙͙̜̼͙ͣ͆͢͡͞͵̸̻̼̗̼̻͂ͣ̓͛͵̷͵̓ ̮͵̼̘௫̹͕
̢̜̺͙͂͂ͅ௬̴̸̢͙̺͙̼̽́ͣͫ̓ͱ̷̗ͳ̻ͱ̻̹̺̗̓̓̓̽͢௬̵̼̘Ͳ௪௬̺̻̺̗͙͖̗̼̈́ͨ̓͜௪Ͼ̺͙̽͵̺͙ͪ͵͂௬̹௬̼̹̓௬̻̺͙͚௬̺̠͙̞̻̓͋̓̚͜ͳ௬̠̜̘̼̺̲̗̼͙̓́̀̈́ ௬̞͕͵
ͳ̞͍͙̜̀͂Ͼ̢̢̻̺͙͚̜͕̓͵̻̯̺͙͂̓
4
1 – Introduction (not more than 500 words)
The section should provide a brief background to the research project proposal, briefly explaining the
importance of the research being proposed, scope of work and conditions in which the project will be executed.
A description of expected results should also be provided as well as an enumeration of fields/areas, and the
extent of, their utilization. This introduction must
clearly address the relationship of the project to the scientific
area (s), its tracks and sub-tracks, and the applied area (s).
5
Since the first suspected case in Wuhan China of COVID-
19
on December
1
st
2019
, the world totaled
1780271
cases and
108822
death at the time of writing these words (worldometer
2020
).
Early detection systems and predictive models to effective planning of countries for the yet to come
waves of the diseases are among the top urgent life-saving jobs. Many research teams around the
world are focusing on. Adapting those models to local circumstances of each country is another
challenge local scientist are racing to achieve(Reich NG
2019
).
Saudi Arabia found itself facing the same outbreak, generating considerable spreading among the
Saudi population, up to April
12
,
2020
, a total of
4,033
cases of COVID-
19
infection have been
confirmed in Saudi Arabia, and the death total has reached
52
people.
In this project four models will be tested to predict the spreading behavior of COVID-
19
,
1
. Auto-regression integrated moving average model (ARIMA).
2
. Generalized SEIR modelling.
3
. Global epidemic and mobility structured metapopulation model (GLEaM).
4
. Developing of ANN hybrid model with (GLEaM) for better forecasting.
This project will run in three phases:
Phase I:
2
months (June-July)
Data preprocessing, correlation, classification and model building.
Knowing the impact factors in the spread of the disease and the role of other effective variables
together, using very sophisticated methods of studying and classifying the importance of these
factors such as: Social spacing, Quarantine, Complete Quarantine, Partial Quarantine, travel and
environment, and the role between day-to-day spreads. One of the promising models can be used is
the Global Epidemic and Mobility (GLEaM) model. The GLEaM model combines the infection
dynamics with long- and short-range human mobility, the flexible structure of the model that is open
to the inclusion of different disease structures and local intervention policies.
Phase II:
3
months (Aug.-Dec.)
Improve the precision of the above models to accumulate more factors and give more precise
predication (i.e. in case we need to predict the number of ventilators that the health system will be
needed). Figure
1
, advanced modeling techniques can be used to achieve better performance using
suspected, infected and recovery (SIR) data such as:
Hybrid Artificial Intelligent.
Machine Learning Techniques.
Data Mining Techniques Deep Neural Network.
To develop this model several software can be used such as:
Weka, Clementine, Orange Tool and MATLAB
Figure
1
: Proposed ANN model
Phase III:
4
months (Jan-April)
More research is warranted to compare the performances of mechanistic and phenomenological
approaches for disease forecasts, before such predictions can be fully deployed by public health
authorities, government, decision makers and stakeholders.
Develop an easy to used GUI software for the best model and train the health workers with data
gathering and analysis to be ready for implementation in the GUI model.
6
2 –
Project Objectives / Potential Outputs And Methods Of Utilization
To run the current most advanced prediction model for the first-to-come wave
To enhance the prediction model by using AI model
To develop, test and run a Decision Support System to the same AI model
OBJECTIVES
This section should be set in a SMART way (specific, measurable, attainable, relevant, and time-bound) in a
bullet format. Also this section should include the Potential Outputs and Methods of Utilization.
7
3 – Literature Review
This section should include pertinent, up-to-date background information and cutting edge scientific
literatures. This section should, also, identify clearly gaps in knowledge that the proposed project will address;
and should be interlinked with any concluded or ongoing work by the project team or by others.
In this review we will investigate the previous models that have been developed to predict the
spreading behavior of a global epidemic or outbreak, explore the significant dependent and
independent factors that specifically impacts the propagation of the epidemic; and the latest
research targeted COVID-
19
pandemic.
Past studies have shown that simple logistic- growth models continue to underestimate the peak
timing and length of disease outbreaks. However, these simple logistic-type phenomenological
growth models may usually only accommodate a single-wave epidemic process characterized by a
single peak in the number of new infections followed by a "burnout" phase, unless there is an
external driving force., such as a seasonal variation in contact patterns.
The Generalized logistic growth Model (GLM) displayed promising performance for short-term
forecasting the trajectory of emerging infectious disease outbreaks [
20
–
22
]. Where a parameter is
correlated with significant uncertainty, the design of unknown models requires that its range be
limited to a reasonable or realistic range as close as possible to the best estimate based on
demographic and epidemiological data. data should be non-heterogenous and continuous Mann-
Whitney U-test can be used to evaluate continuous data. Also, Chi-square test will use for
categorical variables. Independent risk factor analysis can also be performed using
multivariate logistic regression analyses with forward stepwise method with selected parameters of
P-value <
0.05
. more information about logistic regression models can be found in Annex
1
.
The Global Epidemic and Mobility (GLEaM) (Balcan, Gonçalves et al.
2010
)one of the promising
models can be used. The model combines the infection dynamics with long-range and short-range
human mobility, the flexible structure of the model that is open to the inclusion of different disease
structures and local intervention policies. GLEaM combine three different data layers (Colizza, Barrat
et al.
2006
) . The population layer is based on the high-resolution population database of the
'Gridded Population of the World' project of the SocioEconomic Data and Applications Center
(SEDAC) (Garnerin and Valleron
1992
) that estimates the population with a granularity given by a
lattice of cells covering the whole planet at a resolution of
15
×
15
minutes of arc. The transportation
mobility layer integrates air travel mobility obtained from the International Air Transport Association
(IATA)(Halloran, Ferguson et al.
2008
) and Official Airline Guide (OAG) databases (Grais, Ellis et al.
2004
)that contain the list of worldwide airport pairs connected by direct flights and the number of
available seats on any given connection (Grais, Ellis et al.
2003
). The combination of the population
and mobility layers allows the subdivision of the world into georeferenced census areas defined with
a Voronoi tessellation procedure around transportation hubs. These census areas define the
subpopulations of the metapopulation modeling structure. Other research used Monte Carlo
generation of the distribution of arrival time of the infection in each country based on the analysis of
106
worldwide simulations of the pandemic evolution with the GLEaM mode.
The complexity of the interrelation between different predictive indicators that propagates the
spread of a pathogen are the major challenge in developing a model of trajectory ((Hoen AG
2015
).
The most important factors intervening in prediction models are the mode of transmission (airborne
in COVID-
19
), individuals
’
interaction and socialization cultures, public health interventions, the
genetic mix of the population, the weather variations, as well as an endless list that all showed
statistically significant effect in prediction models (Wagner BG
2009
)). Simple phenomenological
linear trajectory growth models are the most used in many health systems around the world. Their
main problem is that they are not accurate to an extent that their exaggerated results are
frustrating politicians and the public and resulting in huge waste of resources. The ability to
generate accurate pandemic forecasts models is challenged by the limited data on individual and
8
group diversity and uncertainty affecting the dynamics of infectious disease transmission. That
reason of search of more sophisticated models such as hybrid AI and deep learning. These models
are able to capture nonlinearity of the data and produce more accurate results.
There are six areas the proposed models can be working to the fight against COVID-
19
:
i. Early warnings and alerts
ii. Prediction
iii. Treatments
iv. Social control
Currently diagnosis of COVID-
19
relies on SARS-CoV-
2
nucleic-acid testing. Many false negative cases
continue to appear due to several factors including low viral load, insufficient detection kits and late
presentations. Other factors like atypical symptoms, unclear exposure history and not specific nor
standardized imaging interpretation only adds to the confusion.
Dependent and independent factors can be used:
Applying multivariate logistic regression analysis on a cohort of critically ill patients in Saudi Arabia
can help in determining important cut-off values to predict the severity of the diseases. Factors like,
signs of pneumonia in CT, history of contact with a positive case, grade of fever, neutrophil-to-
lymphocyte ratio (NLR), age and gender can all be used as predictors. Cut-off values of disease
severity, like CT score, CD
8
+ T cell count, CD
4
+ T cell count can be more precisely determined to be
used in the advanced model (Cong-Ying Song
2020
).
Other multivariate models that can be revalidated for the Saudi data is the Jiangsu Province early
warning system which had a sensitivity of
0.955
(
95%
CI [
0.772
–
0.999
]), and a specificity of
0.899
(
95%
CI [
0.863
–
0.928
]). All COVID-
19
positive cases were screened twice a day in Jiangsu through,
respiratory rate (RR), heart rate (HR), SpO
2
(room air). A cut-off value was identified of SpO
2
<
93%
, RR >
30
/min, HR >
120
/min or any signs of organ failure to ignites the system to refer the
patient to the ICU (Qin Sun
2020
). Such predictive indicators when validated can all be incorporated
into the mathematical model to improve the prediction capacity. Such variables can also be added
to the sophisticated model as preventative intervention to better predict the response to the
expected coming waves.
Latest research targeted COVID-
19
pandemic
A new research by (Nesteruk
2020
) and (Ming, Huang et al.
2020
) focuses on the spread of COVID
19
coronavirus disease due to the international risk of a pandemic emerging in mainland China.
(Nesteruk
2020
) used the popular SIR (Susceptible Infectious Removed) in his study. A model was
developed to obtain optimum values for model parameters using a mathematical method and thus
focused on the number of sick, prone and excluded individuals over time. This conceptual method
by Nesteruk (
2020
) was a significant advance in disease prevention modeling as used by many
scholars (Ming and Zhang,
2020
and Oduwole and Kimbir (
2018
), among others). However, while
there is a growing interest in understanding the risk of transmission that will arise worldwide over
time, it is of considerable importance to suggest a statistical mechanism to end the propagation and
eventual removal of the virus. In this study, therefore, we adopt solutions from (Victor and Oduwole
2020
) for a new endemic deterministic model. (Susceptible
–
Exposed
–
Infectious
–
Removed
–
Undetectable
–
Susceptible: SEIRUS). Originally designed for the management of HIV / AIDS
prevalence in Africa.
The resulting equations are a system of coupled homogeneous differential equations. Numerical
studies with the related simulation demonstrate how the variance of the reproductive number (R
0
)
influences the number of infected individuals. Aware effort is made by testing the current
deterministic SEIRUS model to reduce the reproductive number (R
0
) to zero in order to avoid the
propagation of the disease, contributing to an endogenous equilibrium to eliminate the disease later
in the future.
Okhuese
2020
establishes and tests a modern deterministic endogenous SEIRUS compartmental
model of COVID-
19
coronavirus dynamics that incorporates quarantine / observatory procedures
and behavioral change / social gap in disease management and eradication in the most exposed
sub-population.
9
The broad dissemination of COVID-
19
coronavirus and the absence or inefficiency of purposeful and
result-based activity are a significant demand for more analytical and technical efforts aimed at
updating the theoretical frameworks and guidelines of social and science study for disease control.
While previous experiments have been targeted to epidemiology and disease-free environment
where the reproductive amount of the contagious community is at its lowest minimum, The goal of
this research is to evaluate the evaluative effect of the endemic balance of the current endemic
deterministic model while taking into account the likelihood that the recovered population could be
undetectable and ready to transfer to the Susceptible container, which would then contribute to
zero secondary transmission of the disease worldwide. This research study would also render a
substantial contribution to recent research results by (Nesteruk
2020
) and (Ming, Huang et al.
2020
)as well as educate government, non-governmental organizations and decision makers on
effective disease prevention strategies focused on different age groups of the active population. The
Artificial Neural Network (ANN) model will also be used with other models as it(Balcan, Gonçalves et
al.
2010
) has been used widely and considered to be an effective and powerful technique to
compute, predict and classify large volume of data. Moreover, the ANN has been proved as more
versatile and robust compare with regression model.
10
4 – Description of the Proposed Work
This section should provide sufficient information of the work to be undertaken and should describe in details
how the project questions will be tackled. This section should, also, outline the general plan of work, including
the broad design and methodology that will be adopted, and, where appropriate, should provide a clear
description of experimental methods and procedures as well as expected outcomes. This section should be
structured under the following headings:
4.1.
Approach, tasks and phases:
this sub section should include details of the approaches utilized to achieve
each objective of the project. Research tasks and activities should be divided into groups of assignments,
listed in logical sequence and linked with the project objectives to be achieved. Please complete the
following items.
Approach Utilized For Achieving Objectives
Objectives
Approach of Achieving Objectives
To run the current most advanced
prediction model for the first-to-
come wave
Select the current most advanced prediction model and test it
with the available data
To enhance the prediction model
by using AI model
review the most effective AI models and select the best model to
test the available COVID-19 data
To develop, test and run a
Decision Support System to the
same AI model
Using the most appropriate IDE to develop the DSS to apply the
AI model using a convenient GUI
Please describe (not more than 2000 words)
11
Mapping Of Phases And Tasks To Achieve Objectives
Objectives
Phases
Tasks
Description
To enhance the
prediction model by
using AI model
Phase 2
Present phase 2 outcomes
Present the updated
model to MOH
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Determining Data
Determine the
dependent variable
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Publications preparation
Prepare for publications
and final report
Objective Description
First objective:
To run the current most advanced prediction model for the first-to-come wave
To achieve the objective this data team will determine the sources of information needed and start
contacting them through official channels to request the data according to the needed specifications.
While waiting to acquire the data, the technology team will re-run the prediction models they tested at
the proposal development phase. Hypothetical data will be used to test such models and dummy tables
and expected outcomes will be prepared. As soon as the data come in, it will be assessed, reviewed and
gaps will be determined. A survey to fill these gaps will be developed by the Epidemiology team and the
field personnel will be trained to implement it. This phase will end by the week
8
and
9
by presenting the
initial model to the decision makers at the Ministry of Health (MOH).
Second objective:
To achieve the objective this is dedicated to choosing and implementing an appropriate Artificial
Intelligence model to run. Actually, a subgroup of the Technology team is expected to start testing the
selected models as early as the second week of the project. They are should have one model ready and
tested by week
9
. The initial data collected in the first phase should have been run in the model to test if
any further data is required. Through this phase the logistic model which are to match parts of what the
AI model perform, will be run to its maximum capacity. It is meant to compare the results of the two
models to determine the benefits and extra precision the AI system should provide. By the end of this
phase, specifically in week
15
and
16
, the AI model will be shared with the stakeholders in the Ministry of
Health to try and give their feedback. Then another three weeks will be spent in implementing the
adjustments requested by MOH.
To enhance the prediction model by using AI model
Third objective:
To develop, test and run a Decision Support System to the same AI model
To achieve the objective the teams will be very busy transforming the AI model into a Decision Support
System (DSS) for health with user friendly interfaces. A sub-group for publications will be very active
through this phase too. They would have started earlier in the project, but this is the time the first
publications should see the light and they shall be preparing for further publications and the final report.
The second version of the AI model will be presented to MOH by the
32
nd week. By that time one
engineer from the technology group will be residing at the MOH to support implementing the model,
training the personnel to use it, troubleshoot problems and provide further feedback to the project team.
The final version of the DSS will be installed into the MOH systems by week
36
. Another engineer will be
outsourced to the MOH to facilitate the implementation, training, and troubleshooting. Shortly before
week
42
, the last week of the project, the final report will be ready and the DSS shall be official and final
launched by KACST president -or president representative-, the Minister of Health and other partners in
the project. By that time, the project would have already been contributed to combating COVID-
19
by its
earlier models. This final ceremony is intended to celebrate the efforts of combating the disease and the
provision of a Saudi AI model that can help in better predicting any hazards and early prepare for it, both
nationally and for other countries to use and deploy.
12
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Install the simulation model
Request simulation
models, install and test
them
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Present Draft 2
Present Draft
2
DSS
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data mapping
Determine the missing
data and design
methods of collection
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Update draft 2
Finalize the final version
of DSS
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Design DSS model
Design a Decision
Support System (DSS)
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Testing AI model
Test AI model into the
finally agreed upon
model
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data collection training
Train for data collection
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Testing AI model
Test AI model into the
finally agreed upon
model
To enhance the
prediction model by
using AI model
Phase 2
Data incorporation
Incorporate the new
data into the model
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data cleaning
Clean and incorporate
collected data
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Testing the model
Test the DSS
To enhance the
prediction model by
using AI model
Phase 2
Update the model
Update the model
according to MOH
requirements
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Present the first phase outcomes
Present the first
simulation model
according to data
available
13
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Orientation
Team meeting and
orientation
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data request
List all sources of
information needed and
contact them
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Run logistic model
Run the logistic models
that goes parallel to the
mathematical models
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Present draft 1
Present the DSS to MOH
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Present the Final outcomes
Deliver the final report
and presentation
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Run simulation model
Run the first model
according to available
data
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data acquiring
Collect needed data and
clean it
To enhance the
prediction model by
using AI model
Phase 2
Run logistic model 2
Run the logistic models
that goes parallel to the
mathematical models
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Data collection
Collect data
To run the current
most advanced
prediction model for
the first-to-come wave
Phase 1
Equipment purchase
Purchase equipment,
install and store
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Update draft 1
Update the DSS and
prepare draft
2
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Finalize the publication
Finalize publications and
final report
To develop, test and
run a Decision Support
System to the same AI
model
Phase 3
Implement final draft
Run the DSS with MOH
with all troubleshooting
and adjustments until
make sure the system is
very stable
14
Please describe (not less than 500 words)
15
This study aims to construct a prediction model suitable for describing the dynamics of pandemic
spreading of Coronavirus disease
2019
(COVID-
19
) in Saudi Arabia. Historical data of infected,
recovered and death cases from official sources will be used for the model fitting. This project will
take place in three phases, The first phase will focus on data analysis, correlation, and classification,
and then on the use of epidemic forecasting models such as the Global Epidemic and Mobility
Structured Meta-population Model (GLEaM) to predict future waves to address the limitations of
conventional logistic-growth models that tend to underestimate the peak timing and duration of the
disease epidemic.
Second Phase, will Increase the precision of the models to accumulate more factors and develop
hybrid Artificial Intelligent (AI) algorithms combined with GLEaM model. Finally, we should improve
outputs of mechanistic and phenomenological methods for disease predictions, to be completely
implemented by public health authority's decision makers and
other stakeholders initiate the project and data collection.
Phase
1
:
The data will be collected from reliable sources both for the national and international levels. For
instance, the International Air Transport Association (IATA) air travel information will be solicited to
run the expected imported cases, if Umra and Hajj are re-opened. John Hopkins Coronavirus
Resource Centre, can be considered the official source of the international COVID-
19
spread data.
On the local level, only the Ministry of Health (MOH), or sources the MOH recommends like the
WHO, will be used. Yet, it is understood that more data will be required that the MOH might not
have. Therefore, the project will make sure to have a couple of research teams to elicit more data or
do further investigation and verification from the data sources. For example, coronavirus positive
cases contact tracing and mobility patters will be needed to develop the model and is not usually
collected in surveillance systems. Such systems will trace only close and direct contacts and isolate
them, while it is needed to know how many personnel could have been exposed to the diseases by
tracing the travel and contact history of at least
20
cases to help forecast the expected level of
spread. Moreover, the hospitals reports related to supplies consumption at different stages of
implementing public health interventions to measure the effect of those measures, should always
be reviewed for accuracy and precision. That include Personal Protective Equipment (PPE), COVID-
19
related pharmaceutical supplies and ventilators in particular. The accuracy of the model projection
in such data is very sensitive due to the financial implications and the scarcity of the availability of
such supplies during the times of pandemics. The two teams will ensure that enough data is
provided to run the prediction models to the highest precision as well as that data provided is well
reviewed and verified.
Phase
2
:
Improve the precision of the above models to accumulate more factors and give more precise
predication (i.e. in case we need to predict the number of ventilators that the health system will be
needed). Advanced modeling techniques can be used to achieve better performance using
suspected, infected and recovery (SIR) data such as:
Hybrid Artificial Intelligent.
Machine Learning Techniques.
Data Mining Techniques Deep Neural Network.
Phase
3
This phase will focus mainly on developing and testing software using an appropriate Integrated
Development Environment (IDE) platform to design and implement the software with a convenient
Graphical User Interface (GUI) for the proposed prediction model so the forecasts to be fully
integrated into public health decision-making authorities. Officials must understand how forecasts
were made and how to interpret forecasts, in terms of forecast the timing, intensity, and short-term
trajectory of COVID-
19
illness in Saudi Arabia.
16
4.2.
Management Plan:
this sub section should indicate how each team member of the project would be
involved (with durations) in executing specific tasks relating to the project as illustrated in. "MS Project"
software may be used in this regard. This section should also clearly identify and outline the role of
collaborators or consultations (if any) who might be contracted to provide assistance in carrying out the
proposed research project. This sub section should also include various elements of the intended work plan;
with phases, related tasks and outcomes, assignments, responsibilities, and dates of submission of progress
and final technical reports.
Senior Personnel
No.
Name
Role
Involvement
Duration
(Months)
1
HAITHAM
MOHAMEDOSMAN
ABDELGHAFAR OSMAN
PI
Data incorporation ,Design
DSS model,Determining
Data,Equipment
purchase,Finalize the
publication,Implement final
draft ,Install the simulation
model,Orientation ,Present
draft 1,Present Draft
2,Present phase 2
outcomes,Present the Final
outcomes ,Present the first
phase
outcomes,Publications
preparation ,Run logistic
model,Run logistic model
2,Run simulation
model,Testing AI
model,Testing the model
,Update draft 1,Update
draft 2,Update the model
10
2
ABDULAZIZ ABDULLAH
BINSAEED
P-CO
Data acquiring ,Data
cleaning ,Data collection
,Data collection
training,Data mapping
,Data request
10
Role and Involvement Duration of Project Team
17
3
AHMED KAMALELDEN
MOHAMMED ALMRDI
CO-I
Data incorporation ,Design
DSS model,Determining
Data,Equipment
purchase,Finalize the
publication,Implement final
draft ,Install the simulation
model,Orientation ,Present
draft 1,Present Draft
2,Present phase 2
outcomes,Present the Final
outcomes ,Present the first
phase
outcomes,Publications
preparation ,Run logistic
model,Run logistic model
2,Run simulation
model,Testing AI
model,Testing the model
,Update draft 1,Update
draft 2,Update the model
10
4
MAKKI AKASHA
ALBASHIER
CO-I
Data incorporation ,Design
DSS model,Determining
Data,Equipment
purchase,Finalize the
publication,Implement final
draft ,Install the simulation
model,Orientation ,Present
draft 1,Present Draft
2,Present phase 2
outcomes,Present the Final
outcomes ,Present the first
phase
outcomes,Publications
preparation ,Run logistic
model,Run logistic model
2,Run simulation
model,Testing AI
model,Testing the model
,Update draft 1,Update
draft 2,Update the model
10
Other Personnel
No.
Name
Role
Involvement
Duration
(Months)
Consultants
No.
Name
Role
Involvement
Duration (Days)
18
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To develop,
test and run
a Decision
Support
System to the
same AI
model
Phase 3
Publications
preparation
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Present Draft 2
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Update draft 2
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Project Plan
19
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To develop,
test and run
a Decision
Support
System to the
same AI
model
Phase 3
Design DSS model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Testing AI model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Testing AI model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
20
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To develop,
test and run
a Decision
Support
System to the
same AI
model
Phase 3
Testing the model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Present draft 1
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Present the Final
outcomes
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
21
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To develop,
test and run
a Decision
Support
System to the
same AI
model
Phase 3
Update draft 1
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Finalize the
publication
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Implement final
draft
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
22
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To run the
current most
advanced
prediction
model for the
first-to-come
wave
Phase 1
Determining Data
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Install the
simulation model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Data mapping
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
Data collection
training
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
Data cleaning
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
23
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To run the
current most
advanced
prediction
model for the
first-to-come
wave
Phase 1
Present the first
phase outcomes
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Orientation
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Data request
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
Run logistic model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
24
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To run the
current most
advanced
prediction
model for the
first-to-come
wave
Phase 1
Run simulation
model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Data acquiring
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
Data collection
ABDULAZIZ
ABDULLAH
BINSAEED, Eliseo
Marcos Guallar,
Mohamed Elyasa
Ibrahim
Equipment
purchase
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
25
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To enhance
the
prediction
model by
using AI
model
Phase 2
Present phase 2
outcomes
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Data incorporation
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Update the model
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
26
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
To enhance
the
prediction
model by
using AI
model
Phase 2
Run logistic model
2
AHMED
KAMALELDEN
MOHAMMED
ALMRDI,
HAITHAM
MOHAMEDOSMA
N
ABDELGHAFAR
OSMAN, MAKKI
AKASHA
ALBASHIER
Deliverable
Phase
Task Name
Resources
M1
M2
M3
M4
M5
M6
M7
M8
M9
M1
0
M1
1
M1
2
M1
3
M1
4
M1
5
M1
6
M1
7
M1
8
M1
9
M2
0
M2
1
M2
2
M2
3
M2
4
Please describe (not less than 500 words)
27
Action plan
This project is meant to be completed in
10
months. It is divided into three phases which ends by week
8
, week
20
and
48
respectively. The implementation team is divided
into three main groups, each group has a coordinator and specific roles and responsibilities. The groups will work seamlessly parallel with specific expected outcomes and
milestones to ensure efficiency and meeting targeted deadlines on time. This project is meant to build a strong partnership with the decision makers in the health sector
and enhance the spirit of ownership in them. The products of this project shall be used by decision makers to combat the COVID-
19
epidemic as well as be accessible for
the educational entities to train the students on the model and further develop it into newer versions.
Phase I
The first week will be dedicated for orienting the teams, assigning tasks and going through the overall plan to ensure that everybody is onboard towards the project aim.
The data team will determine the sources of information needed and start contacting them through official channels to request the data according to the needed
specifications. While waiting to acquire the data, the technology team will re-run the prediction models they tested at the proposal development phase. Hypothetical data
will be used to test such models and dummy tables and expected outcomes will be prepared. As soon as the data come in, it will be assessed, reviewed and gaps will be
determined. A survey to fill these gaps will be developed by the Epidemiology team and the field personnel will be trained to implement it. This phase will end by the week
8
and
9
by presenting the initial model to the decision makers at the Ministry of Health (MOH).
Phase II
This phase is dedicated to choosing and implementing an appropriate Artificial Intelligence model to run. Actually, a subgroup of the Technology team is expected to start
testing the selected models as early as the second week of the project. They are should have one model ready and tested by week
9
. The initial data collected in the first
phase should have been run in the model to test if any further data is required. Through this phase the logistic model which are to match parts of what the AI model
perform, will be run to its maximum capacity. It is meant to compare the results of the two models to determine the benefits and extra precision the AI system should
provide. By the end of this phase, specifically in week
15
and
16
, the AI model will be shared with the stakeholders in the Ministry of Health to try and give their feedback.
Then another three weeks will be spent in implementing the adjustments requested by MOH.
Phase III
This is the longest phase which will run for
22
weeks. During this phase the teams will be very busy transforming the AI model into a Decision Support System (DSS) for
health with user friendly interfaces. A sub-group for publications will be very active through this phase too. They would have started earlier in the project, but this is the
time the first publications should see the light and they shall be preparing for further publications and the final report. The second version of the AI model will be
presented to MOH by the
32
nd week. By that time one engineer from the technology group will be residing at the MOH to support implementing the model, training the
personnel to use it, troubleshoot problems and provide further feedback to the project team. The final version of the DSS will be installed into the MOH systems by week
36
. Another engineer will be outsourced to the MOH to facilitate the implementation, training, and troubleshooting. Shortly before week
42
, the last week of the project,
the final report will be ready and the DSS shall be official and final launched by KACST president -or president representative-, the Minister of Health and other partners in
the project. By that time, the project would have already been contributed to combating COVID-
19
by its earlier models. This final ceremony is intended to celebrate the
efforts of combating the disease and the provision of a Saudi AI model that can help in better predicting any hazards and early prepare for it, both nationally and for other
countries to use and deploy.
28
5 – PROJECT EXECUTION
5.1 Current Resources:
This sub section should provide information on current or pending funding of the
proposed project from any other sources. Equipment and instruments already available at the executing
institution should be enumerated and briefly described.
Available resources: will be mainly provided by King Khalid University, for both the College of
Computer Science and college of Engineering. This will include basic laboratory facilities equipped
with state-of-the-art research tools, basic health, and relevant safety equipment and monitoring
facilities. In addition, the King university is equipped with an updated library with online databases
that will come handy in the literature review phase. Moreover, the University will provide an
assistance in acquiring access to various site locations. In addition, the university administration will
assist in obtaining contacts with different governmental bodies and institutes for their making
available their support.
Available software resources
There is a wide variety of installable software tools available for potentially enhancing the output of
our research. These include Microsoft windows operating system and mac operating system which
are installed in computers, laptops and notebooks of the research teams. In addition to the offline
software like the Microsoft office package which has essential and significant use in our project like:
Microsoft Word processing for writing and editing most of the research related documents and
paper work, Microsoft power point for the necessary presentation and visual communication with
internal teams or any other external party in order to introduce and present all aspects of our
research in terms of thoughts, ideas, tables, figures and diagrams. Microsoft excl which is
significantly use to facilitate the planning part of the project and organize the data and information
of the research as well as the required calculations parts in the budgets and other related issues.
Document management like Skydox can be used as well beside Microsoft word processing. The web
browsers as well considered as a powerful available software that mainly used in the internet
research process. Reference management software like Mendeley and Endnote are used to manage
all references of the research. Since some if the team members are overseas, communication
software media is an available tools research team will be using for the research meetings and
interaction like Skype, Microsoft Teams, hangout, and others.
Platforms for programming languages and machine learning models and algorithm are available to
in specific in this project we will use TensorFlow to facilitate building of both statistical Machine
Learning solutions as well as deep learning through its extensive interface of CUDA GPUs. We can
also use Weka as an open source machine learning software that can be accessed through a
graphical user interface, standard terminal applications, or a Java API. It is widely used for research,
and industrial applications, contains a built-in tool for standard machine learning tasks. RapidMiner
as well can provide an integrated and comprehensive environment for carrying out several tasks like
data preparation, machine learning, deep learning, text mining as well as predictive analytics. It is
popular for its lightning-fast speed to drive revenue, reduce costs and avoid risks. One of its most
essential features is its GUI based drag and drop feature that allows the users to intuitively build
data processing workflows that can be selected from over
2000
available nodes.
5.2 Requested Resources:
This sub section should include
details of all requested human resources,
equipment, materials and consumables, as well as details of transportation facilities and travel arrangements
that may be needed in the execution of field work or special training required. Applicants must give details of
all relevant costs.
29
Requested Resources:
1
. Human Resources:
a. Participants
The project needs four participants in the national level They live in the Kingdom of Saudi Arabia to
carry out the project tasks as follows:
PI: Dr.Haitham Osman
P-CO: Eng. Ahmed Sahl
P-CO: Eng. Makki Akasha
b. Consultants
c. The project needs two Consultants with a great experience in epidemiology and its ways of
spread, they are from overseas for the consultation in epidemic related work
Consultant Dr. Mohamed Ibrahim Yasa.
Roles & Responsibilities as a Consultant:
•
Act as the coordinator of the Epidemiology team and follow the day-to-day work with the project
team
•
Review the Epidemiological literature and provide the latest needed information to the
Epidemiology team and the project group
•
Review acquired data, design surveys for missing data, design data-collection tools, train the field
epidemiology team and lead the team in implementing the surveys
•
Implement the advanced logistic models for prediction of the coming waves
•
Advise and work with the Technology team in needed interventions and data to run the AI models
•
Facilitate the communication and data acquiring from the MOH and other sources
•
Participate in writing and editing the scientific publications
Consultant: Dr. Abd alaziz bin saeed
Roles & Responsibilities as a Co-PI:
•
Advise the team on determining the most important dependent and independent factors
intervening in the spread of the disease
•
Advise the team on the national capacities to combat the diseases and the learned lessons from
the previous experience with MERS-COV
•
Communicate with the MOH and other healthcare authorities in KSA to facilitate building
ownership and adequate collaboration to implement the project
•
Review and discuss the processes of the project as well as its outcomes to determine and prioritize
the most needed information to help the country manage the current epidemic on the ground
•
Discuss with the project team and the healthcare leaders the best decision support information
they need the project to provide and the most practical and reliable means to provide it
•
Participate in the design of surveys and publications
•
Present the results to the healthcare leadership and advocate the pertinent use of the model to
better predict and prepare for any expected waves of the epidemic
Consultant: Dr. Eliseo Guallar
Roles & Responsibilities as a Consultant:
•
Advise the team on determining the most important dependent and independent factors
intervening in the spread of the disease
•
Share the international and JHU experience in acquiring and managing data
•
Facilitate international communications to acquire data and learning first hand form East-Asia
experience whom are ahead of the rest of the world in the progression of the disease
•
Advise in logistic models
’
implementation
•
Lead the scientific publication efforts to find a place in reputable international journals
d. Technicians:
The project needs two technicians for the technical support
30
Consultants
Name
Role
Duration
Allowance
Travel
Total
Mohamed Elyasa Ibrahim
Consultant
8
4000
10000
42000
Eliseo Marcos Guallar
Consultant
7
4000
10000
38000
e. Data collectors
The project needs two data collectors to take care of the data collection tasks
2
. Conferences and travels
Project will publish several scientific papers so all required facilities to achieve this task will be
necessary. As well as the participation in national and international conferences. As well as the travel
between cities to collect data from different sites and for the conferences travel.
Travel for consultants from their countries to Kingdom of Saudi Arabia
3
. Software
The project needs the following software:
a. Visual Studio Professional
2019
b. SQL Server Database
2019
c. SPSS full edition
d. Image editing software
e. Online subscription for some web sites
4
. Equipment
’
s and materials
Computer Systems:
The project needs the following computers for a high-performance computing:
Dell Precision
7920
Tower Workstation, Intel Xeon Silver
4210
2.2
GHz,
3.2
GHz Turbo,
10
C,
9.6
GT/s
2
UPI,
13.75
MB Cache, HT, Windows
10
Pro for Workstations (
4
Cores Plus) Multi
–
English, NVIDIA®
Quadro® P
1000
,
4
GB,
4
mDP (
7
X
20
T),
32
GB
4
x
8
GB DDR
4
2666
MHz RDIMM ECC,
3.5
"
1
TB
7200
rpm
SATA Hard Drive.
The project needs two laptops:
Dell XPS
13
7390
Laptop,
10
th Generation Intel® Core
™
i
7-10710
U, Windows
10
Pro,
16
GB, LPDDR
3
,
2133
MHz, Integrated,
512
GB M.
2
PCIe NVMe Solid State Drive,
13.3
-in. display.
5
. Other
a. Stationaries for all office and paper work related
b. Books Whether electronic or hardcopy
c. Transportation for data collection and other needs
d. Entry permit fees to the related institutions and organizations
e. Labour
f. Typing fees
g. Communication
h. Medical
31
5.3 Proposed Budget
: this sub section should be completed in accordance to the entire duration of
proposed research project. Note that equipment valued at less than SR 10,000 should be included in the
materials and consumables section.
Budget
Participants
Name
Role
Duration
Allowance
Total
AHMED KAMALELDEN
MOHAMMED ALMRDI
CO-I
10
2500
25000
MAKKI AKASHA ALBASHIER
CO-I
10
2500
25000
ABDULAZIZ ABDULLAH
BINSAEED
P-CO
10
2500
25000
HAITHAM
MOHAMEDOSMAN
ABDELGHAFAR OSMAN
PI
10
3000
30000
Total
105000
Total
80000
Assistants
Name
Role
Duration
Allowance
Total
No Record
Students
Name
Role
Working
Mode
Duration
Allowance
Total
No Record
Other Technical Resources
Name
Count
Duration
Allowance
Total
Administrative
3
3
1200
10800
Labor
1
3
600
1800
Total
12600
Materials
Type
Name
Justification
Year
Total
Equipment
Dell Precision 7920
Tower Workstation
The project needs the
computer for a high-
performance
computing for the
modeling
First Year
11758
Equipment
Dell XPS 13 7390
Laptop
The project needs the
computer for a high-
performance
computing for the
modeling
First Year
6216
32
Equipment
Dell XPS 13 7390
Laptop
The project needs the
computer for a high-
performance
computing for the
modeling
First Year
6216
Material/Supplies
Visual Studio
Professional 2019
The project needs the
software for
developing high-
performance
application
First Year
2621
Material/Supplies
SQL Server
Database
The project needs the
software for
developing high-
performance computer
application
First Year
10874
Total
37685
Conferences & Travel
Type
Justification
Year
Total
Travel Foreign
Site Visits and data
Collection
First Year
6000
Travel Foreign
conustlants visit for to
help in the project
First Year
20000
Travel Foreign
conustlants visit for to
help in the project
First Year
20000
Conference
Participation in
National and
International
Conferences
First Year
4000
Conference
Participation in
National and
International
Conferences
First Year
4000
Total
54000
Others
Type
Justification
Year
Total
Other
Books and Stationaries
(external drives,
memories, projectors
First Year
3000
Other
Typing fees writing and
editing
First Year
2000
Other
Medical Consumable
First Year
7000
Publish Research
Paper
First Year
6000
Publish Research
Paper
First Year
6000
33
Total
24000
BUDGET SUMMARY
Type
Total
%
Compensations (including summer
compensation)
197600
59.5%
Equipment & materials
37685
11.35%
Travel
54000
16.26%
Others
24000
7%
Administration STU Expenses
18797.1
6%
Grand Total
332082
100%
34
6.4 Budget Justification
: A detailed justification of the funding requested in each budget
subcategory outlined in subsection 6.3. should specify if the equipment and infrastructure to be
purchased using requested funds would be used in other research projects (not less than 1000
words).
Please describe (not less than 1000 words):
Request Budget justification
The justification for the proposed budget for the smooth accomplishment of this research project
is
provided in the following paragraphs. The total budget for the project is amounting
to a value of SAR _____
332082
_____
This breakdown of the budget is presented in the following segments:
1
. Human Resource:
It includes the human resources which will be responsible for carrying out the
tasks of the project and each member of this team has been assigned particular task based on his
area
of expertise. Below is the summary for the tasks allocated for each member in addition to the
salaries:
Role and tasks of the Principal Investigator (PI):
(Dr. Haitham Osman- Total Salary: _
30000
____SR)
•
Coordination of the PI with Co-PI
’
s and other members of the project to fine tune the details of
the
project and finalize the work plan.
•
Placement of orders for the supply of required equipment, glassware, computers, soft-wares
and other accessories.
•
Liaising with internal and external bodies to facilitate administrative requirements for easy flow
of the
research project.
•
Customizing and running the GleMA model
•
Using Computational intelligent techniques (CIT) for remote sensing application, data analysis,
clustering and classifications.
•
Developing future hybrid prediction model using KSA data.
•
Comparing the performance of the models and optimizing ANN
•
Supervising the research write-ups related to:
o progress reports
o technical reports
o final reports
o papers for publications
Role and tasks of the CO-Principal Investigator (CO-PI):
(Dr. Fakri Total Salary
25000
( Eng. Ahmed Sahl Total Salary
25000
35
Data collection
Data preprocessing
Machine learning modeling
Software development
End-user training
(Eng. Makki Total Salary
25000
Data collection
Data preprocessing
Machine learning modeling
Software development
End-user training
Dr. Abdelaziz Bin Saeed Total Salary
25000
Short Bio: Dr. Binsaeed is currently a consultant in medical education in Washington Dc. His
previous position was deputy minister of health for public health in KSA. He led the country
’
s
efforts to combat MERS-COV which is another corona virus KSA succeeded in managing and
controlling with the least possible casualties. Dr. Binsaeed was the head of Public Health
department in King Saud University and initiated an international master
’
s program as one of
several achievements he attained during that period. Dr. Binsaeed has several publications many
of them are about KSA experience with the previous corona virus epidemic.
Roles & Responsibilities as a Co-PI:
•
Advise the team on determining the most important dependent and independent factors
intervening in the spread of the disease
•
Advise the team on the national capacities to combat the diseases and the learned lessons from
the previous experience with MERS-COV
•
Communicate with the MOH and other healthcare authorities in KSA to facilitate building
ownership and adequate collaboration to implement the project
•
Review and discuss the processes of the project as well as its outcomes to determine and
prioritize the most needed information to help the country manage the current epidemic on the
ground
•
Discuss with the project team and the healthcare leaders the best decision support information
they need the project to provide and the most practical and reliable means to provide it
•
Participate in the design of surveys and publications
•
Present the results to the healthcare leadership and advocate the pertinent use of the model to
better predict and prepare for any expected waves of the epidemic
•
Dr. Eliseo Guallar (
15
days) Total Salary
38000
Short Bio: Dr. Guallar is a DrPH graduate of Harvard and currently is working as a lead professor
of epidemiology at John Hopkins University. Dr. Guallar designed and implemented several
epidemiological surveys in the United States and internationally. He has over
310
published
papers and has a wide network of collaborators in the epidemiology field around the world. Dr.
Guallar is an expert in logistic and prediction model and relating outcomes to biological and
environmental intervening factors. John Hopkins University, where Dr. Guallar is among the
leadership, is leading the world nowadays in COVID-
19
data capturing and processing. It
’
s the
36
main pinnacle the whole world follows the progress and spread of the diseases through. Dr.
Guallar brings all that knowledge and connections to the project.
Roles & Responsibilities as a Consultant:
•
Advise the team on determining the most important dependent and independent factors
intervening in the spread of the disease
•
Share the international and JHU experience in acquiring and managing data
•
Facilitate international communications to acquire data and learning first hand form East-Asia
experience whom are ahead of the rest of the world in the progression of the disease
•
Advise in logistic models
’
implementation
•
Lead the scientific publication efforts to find a place in reputable international journals
Dr. Mohamed Ibrahim (
15
days ) Total Salary
42000
Short Bio: Dr. Ibrahim is a clinical epidemiologist who worked with both the governmental sector
and the UN systems in combatting diseases. He participated in Acute watery diarrhea, Dengue
Fever, Avian flue and MERS-COV epidemics as a front-line epidemiologist, in policy and planning
and as a third-party auditor to early preparedness and surveillance systems. Dr. Ibrahim designed
and implemented several national level surveys and applied advanced biostatistics in analysis and
building decision support systems. Dr. Ibrahim runs his own business in the United States and
taking part in several epidemiological consultancies. His previous position to that was an advisor
to the deputy minister of health for Public Health in Saudi Arabia where participated in designing
the KSA
2030
vision for health and the
2020
plan. Dr. Ibrahim was among the leadership who
implemented the national public health reform project.
Roles & Responsibilities as a Consultant:
•
Act as the coordinator of the Epidemiology team and follow the day-to-day work with the project
team
•
Review the Epidemiological literature and provide the latest needed information to the
Epidemiology team and the project group
•
Review acquired data, design surveys for missing data, design data-collection tools, train the
field epidemiology team and lead the team in implementing the surveys
•
Implement the advanced logistic models for prediction of the coming waves
•
Advise and work with the Technology team in needed interventions and data to run the AI
models
•
Facilitate the communication and data acquiring from the MOH and other sources
•
Participate in writing and editing the scientific publications
2
. Computer Systems:
•
The project needs the following computers for a high-performance computing:
o Dell Precision
7920
Tower Workstation, Intel Xeon Silver
4210
2.2
GHz,
3.2
GHz Turbo,
10
C,
9.6
GT/s
2
UPI,
13.75
MB Cache, HT, Windows
10
Pro for Workstations (
4
Cores Plus) Multi
–
English,
NVIDIA® Quadro® P
1000
,
4
GB,
4
mDP (
7
X
20
T),
32
GB
4
x
8
GB DDR
4
2666
MHz RDIMM ECC,
3.5
"
1
TB
7200
rpm SATA Hard Drive.
o Cost:
11,758.63
SAR
•
The project needs two laptops:
o Dell XPS
13
7390
Laptop,
10
th Generation Intel® Core
™
i
7-10710
U, Windows
10
Pro,
16
GB,
LPDDR
3
,
2133
MHz, Integrated,
512
GB M.
2
PCIe NVMe Solid State Drive,
13.3
-in. display.
o Cost:
12,433.46
SAR
•
Total cost:
24,192.09
SAR
3
. Software procurement:
37
•
The project needs the following computers
o Visual Studio Professional
2019
o Cost:
2,621.00
SAR
o SQL Server Database
2019
o Cost:
10,874.00
SAR
4
. The budget for miscellaneous items: This segment covers the unseen expenses that may arise
along with the progress of the research project. The total value allocated does not exceeds
30,000
SAR. The items covered in this segment covers the fees of publications in the ISI journals,
stationaries
and office items for project support, labour work that may rise during the soil and water samples
collection and others.
In conclusion, it is very important to highlight the pressing issue that the prices allocated in the
budget
are subject to many parameters, i.e. inflation rates, availability in the local market and shipment
and
transportation for purchases made from outside the Kingdom. The prices allocated is also valid
during
the period of writing the proposal, however, future estimations are sometimes included, but in
this ever-changing
global economy all predictions can sometimes overshoots and/or under-estimate actual
prices. Having said that the research team is committed to investigate thoroughly the prices of
each
item before committed to a supplier to ensure best value for money, in addition extra budget
and/or saved value of any equipment will be refunded to KASCT by the end of the project.
38
7 – UNDERTAKING OF THE RESEARCH TEAM
This section includes a consent of the research team on some scientific rules and ethics, and the compliance
with their violation measures.
Section I. The research team undertakes that:
1. The text and graphics herein as well as any accompanying publications or other documents,
unless otherwise indicated, are the original work of the signatories or individuals working
under their supervision.
2. No part of this proposal has been funded by any other source.
3. No fund would be sought from any other source if an award is made as a result of this
proposal.
4. The proposal will be carried out in full alignment with the
GOVERNING RULES OF THE
PROGRAM
, if awarded.
5. Proposal is prepared in full conformity with the
SCIENTIFIC INTEGRITY RULES
.
6. Proposal is prepared in full conformity with the Regulations of
RESEARCH BIOETHICS ON THE
LIVING CREATURES
.
7. None of the research and supporting team of the project receives more than (3) projects
compensations, nor participates in more than (5) projects from different sources of King
Abdulaziz City for Science and Technology (KACST).
8. Committed to deliver the minimum scientific outputs.
9. Bear the consequences of the violation of what have been stated above.
Section II. Undertaking for the Extramural Researchers:
1.
I
‘
ve read carefully the guidelines (
English
/
Arabic
) for the participation of the extramural researchers
in the awarded projects from KACST and I am committed to them precisely, in addition to the above
missioned undertaken in Section I.
ROLE
NAME
ID No.
SIGNATURE
PI
HAITHAM
MOHAMEDOSMAN
ABDELGHAFAR OSMAN
2312428655
Approved
CO-I
AHMED KAMALELDEN
MOHAMMED ALMRDI
2350711277
Approved
CO-I
MAKKI AKASHA ALBASHIER
2329096594
Approved
Consultant
Mohamed Elyasa Ibrahim
P01832131
Approved
Consultant
Eliseo Marcos Guallar
XDC653426
Approved
P-CO
ABDULAZIZ ABDULLAH
BINSAEED
1029303383
Approved
39
8 – REFERENCES
References should be cited in the standard style used in scientific/technical publications. Links to
online versions may be provided together with dates on which the material was accessed
Balcan, D., et al. (
2010
). "Modeling the spatial spread of infectious diseases: The GLobal Epidemic
and Mobility computational model." Journal of computational science
1
(
3
):
132-145
.
Garnerin, P. and A.-J. Valleron (
1992
). The French communicable diseases computer network.
[Proceedings]
1992
IEEE International Conference on Systems, Man, and Cybernetics, IEEE.
Grais, R., et al. (
2004
). "Modeling the spread of annual influenza epidemics in the US: The potential
role of air travel." Health care management science
7
(
2
):
127-134
.
Grais, R. F., et al. (
2003
). "Assessing the impact of airline travel on the geographic spread of
pandemic influenza." European journal of epidemiology
18
(
11
):
1065-1072
.
Halloran, M. E., et al. (
2008
). "Modeling targeted layered containment of an influenza pandemic in
the United States." Proceedings of the National Academy of Sciences
105
(
12
):
4639-4644
.
Hoen AG, H. T., Eggo RM, Lenczner M, Brownstein JS, Meyers LA (
2015
). "Epidemic wave dynamics
attributable to urban community structure: a theoretical characterization of disease transmission
in a large network." J Med Internet Res:
17
(
17
).
Ming, W.-K., et al. (
2020
). "Breaking down of healthcare system: Mathematical modelling for
controlling the novel coronavirus (
2019
-nCoV) outbreak in Wuhan, China." bioRxiv.
Nesteruk, I. (
2020
). "Statistics based predictions of coronavirus
2019
-nCoV spreading in mainland
China." MedRxiv.
Qin Sun, H. Q., Mao Huang & Yi Yang (
2020
). "Lower mortality of COVID-
19
by early
recognition and intervention: experience from Jiangsu Province." Annals of Intensive Care.
Reich NG, B. L., Fox SJ, Kandula S, McGowan CJ, Moore E, Osthus D, Ray EL, Tushar A, Yamana TK,
et al (
2019
). "A collaborative multiyear, multimodel assessment of seasonal influenza forecasting
in the United States." Proc Natl Acad Sci USA:
146-154
.
Victor, A. and H. Oduwole (
2020
). "Evaluating the Deterministic SEIRUS Model for Disease Control
in an Age-Structured Population." Global Scientific Journal. Preprint.
Wagner BG, C. B., Blower S. (
2009
). "Calculating the potential for within-flight transmission of
influenza A (H
1
N
1
)." BMC Med:
7:81
.
worldometer (
2020
). COVID-
19
Coronavirus Pandemic. worldometers.
40
9 – ATTACHMENTS
Following are the attachments provided with proposal,
•
Drawings
41
Figure 1: Proposed ANN model
Data (SIR)
without
lockdown
Data (SIR) with
lockdown
Data (SIR) with
Social distancing
Data Mining
+Machine
Learning
+Artificial
Intelligent
Spread
Early
waring
Treatments
42
Resumes of above mentioned researchers are attached,
Role
Name
ID No.
PI
HAITHAM MOHAMEDOSMAN
ABDELGHAFAR OSMAN
2312428655
CO-I
AHMED KAMALELDEN MOHAMMED ALMRDI
2350711277
CO-I
MAKKI AKASHA ALBASHIER
2329096594
Consultant
Mohamed Elyasa Ibrahim
P01832131
Consultant
Eliseo Marcos Guallar
XDC653426
P-CO
ABDULAZIZ ABDULLAH BINSAEED
1029303383
10 – Resumes
A biographical sketch (max.3 pages) is required for each senior personnel involved in the research project. Resumes
should include information related to professional preparation, appointments, publications, synergistic activities and
collaborators and other affiliations.
43
Resume of HAITHAM MOHAMEDOSMAN ABDELGHAFAR
OSMAN
PERSONAL DETAILS
Name
Dr. HAITHAM MOHAMEDOSMAN ABDELGHAFAR
OSMAN
Gender
Male
DOB
19/04/1973
Nationality
Sudan
Iqama Number
2312428655
Iqama Issue Date
1432/05/02
Iqama Expiry Date
1442/02/02
ORCID
CONTACT DETAILS
Email
haman@kku.edu.sa
Alternate Email
haitham.osman@gmail.co
m
Address 1
king khalid university
Address 2
Department of chemical
engineering
Postal Code
61413
PO Box
394
Country
Saudi Arabia
City
abha
Phone Number
0569537424
Fax
N/A
Mobile
966569537424
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
PhD
United Kingdom
Newcastle University
Chemical
Engineering
2005
Excellent
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
king khalid
university
Academic
Ahba
08/09/2011
Till Date
Assistant professor
INTERESTS
Field
Interest
Sub Interest
No record exists
Current Activities
waste lube oil recycle,
process optimisation and
control
Keywords
AI, ANN, Genetic Algorithm,
Model predictive Control,
Petrochemical Optimization
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
44
Resume of HAITHAM MOHAMEDOSMAN ABDELGHAFAR
OSMAN
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Saudi Universities
Name
King Khalid University
College Name
n/a
Section Name
chemical engineering
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
No record exists
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
No record exists
45
Resume of HAITHAM MOHAMEDOSMAN ABDELGHAFAR
OSMAN
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
No record exists
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
No record exists
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
No record exists
46
Resume of ABDULAZIZ ABDULLAH BINSAEED
PERSONAL DETAILS
Name
Prof. ABDULAZIZ ABDULLAH BINSAEED
Gender
Male
DOB
15/10/1966
Nationality
Saudi Arabia
ID Number
1029303383
ID Issue Date
1403/11/26
ID Expiry Date
1458/03/14
ORCID
AAA11
CONTACT DETAILS
Email
abinsaid@ksu.edu.sa
Alternate Email
abinsaeed90@Gmail.com
Address 1
Department of Family and
Community Medicine
College of Medicine
King Saud University
Address 2
N/A
Postal Code
12343
PO Box
7737
Country
Saudi Arabia
City
Riyadh
Phone Number
0114670836
Fax
N/A
Mobile
966-507554455
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
No record exists
INTERESTS
Field
Interest
Sub Interest
No record exists
Current Activities
N/A
Keywords
N/A
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
47
Resume of ABDULAZIZ ABDULLAH BINSAEED
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Saudi Universities
Name
King Saud University
College Name
College of Medicine
Section Name
Family and Community
Medicine
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
No record exists
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
No record exists
48
Resume of ABDULAZIZ ABDULLAH BINSAEED
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
No record exists
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
No record exists
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
No record exists
49
Resume of AHMED KAMALELDEN MOHAMMED ALMRDI
PERSONAL DETAILS
Name
Mr. AHMED KAMALELDEN MOHAMMED ALMRDI
Gender
Male
DOB
23/08/1983
Nationality
Sudan
Iqama Number
2350711277
Iqama Issue Date
1440/12/22
Iqama Expiry Date
1441/12/22
ORCID
https://orcid.org/0000-0002-0773-7422
CONTACT DETAILS
Email
akaldin@kku.edu.sa
Alternate Email
ahmed.sahl@hotmail.com
Address 1
Almanhal
Address 2
N/A
Postal Code
62529
PO Box
62529
Country
Saudi Arabia
City
Abha
Phone Number
0530825892
Fax
N/A
Mobile
966-530825892
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
Bachelor
Sudan
Sudan University of
Science and Technology
Computer Science
2006
Excellent
Master
Sudan
University of Khartoum
Computer Science
2012
Good
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
King Khalid
University
Lecturer
Abha
20/08/2013
Till Date
N/A
INTERESTS
Field
Interest
Sub Interest
Computer Science
Others
Others
Current Activities
N/A
Keywords
N/A
50
Resume of AHMED KAMALELDEN MOHAMMED ALMRDI
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Saudi Universities
Name
King Khalid University
College Name
n/a
Section Name
Computer Science
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
A committed Teaching Staff with over 12 years of experience at leading academic institutions teaching
students from several social and cultural backgrounds, Have excellent administrative, oral
communication and written skills along with useful and effective teaching methods that encourage a
motivating learning environment. Working to excel in the data science field and its tools.
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
No record exists
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
51
Resume of AHMED KAMALELDEN MOHAMMED ALMRDI
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
0
0
0
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
0
0
0
0
0
0
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
0
0
0
0
0
0
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
0
0
0
52
Resume of MAKKI AKASHA ALBASHIER
PERSONAL DETAILS
Name
Mr. MAKKI AKASHA ALBASHIER
Gender
Male
DOB
01/01/1984
Nationality
Sudan
Iqama Number
2329096594
Iqama Issue Date
1440/12/24
Iqama Expiry Date
1441/12/26
ORCID
0000-0001-7027-9586
CONTACT DETAILS
Email
mbabikier@kku.edu.sa
Alternate Email
okashababikier@gmail.co
m
Address 1
king khalid university
Address 2
khamis mushit
Postal Code
0000
PO Box
00000
Country
Saudi Arabia
City
khmuis mushit
Phone Number
0507624461
Fax
N/A
Mobile
966-507624461
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
Bachelor
Sudan
Sudan university of
Science and Technology
Computer Science
2006
Very Good
Master
South Korea
Chungbuk National
University
Computer Science
2010
Excellent
53
Resume of MAKKI AKASHA ALBASHIER
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
RA,
Database/Bioinf
ormatics
Laboratory
Researcher
Assistant
Chungbuk
National
University,
Cheongju, South
Korea.
22/08/2009
05/09/2010
Researcher Assistant
Lecturer
Lecturer
College of
Computer ,
Department of
Computer
Science.
07/10/2010
01/07/2012
teaching
Lecturer
Lecturer
College of
Computer ,
Department of
Computer
Science.
25/03/2012
Till Date
teaching
INTERESTS
Field
Interest
Sub Interest
No record exists
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Saudi Universities
Name
King Khalid University
Current Activities
N/A
Keywords
N/A
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
o More than
3
years of work experience in educational and research organizations, including some data
mining projects in South Korea.
o Energetic, reliable, competitive and professional; with a strong work ethic and commitment to
success.
o Excellent communication, presentation, and interpersonal relationship skills.
o Experienced with working in a multi-linguistic and multicultural environment.
o Fluent in multiple languages, including excellent English, Arabic as a native language, and basic
understanding of the Korean Language.
o Have leadership skills and also have the ability to work independently.
o Have ability to communicate, analyze and troubleshoot problems in an efficient manner.
54
Resume of MAKKI AKASHA ALBASHIER
College Name
n/a
Section Name
Deprtment of computer
Science
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
No record exists
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
0
0
0
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
0
0
0
0
0
0
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
0
0
0
55
Resume of MAKKI AKASHA ALBASHIER
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
0
0
0
0
0
0
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
56
Resume of Eliseo Marcos Guallar
PERSONAL DETAILS
Name
Prof. Eliseo Marcos Guallar
Gender
Male
DOB
18/06/1963
Nationality
Spain
Passport Number
XDC653426
Passport Issue Date
23/03/2017
Passport Expiry Date
22/03/2027
ORCID
0000-0002-4471-9565
CONTACT DETAILS
Email
eguallar@jhu.edu
Alternate Email
eguallar@jhsph.edu
Address 1
2024
E. Monument St.
Room
2-645
Address 2
N/A
Postal Code
21205
PO Box
21205
Country
United States of America
City
Baltimore
Phone Number
4106140574
Fax
N/A
Mobile
1-4434135611
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
PhD
United States of
America
Harvard University
Public Health –
Epidemiology
1994
Pass
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
Johns Hopkins
University
Professor
2024 E.
Monument Street,
Baltimore, MD,
USA
01/01/2000
Till Date
Teaching and
research
INTERESTS
Field
Interest
Sub Interest
Public health – Epidemiology
Others
Others
Current Activities
N/A
Keywords
N/A
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
Dr. Guallar expertise is in the identification of risk factor for disease in human populations
57
Resume of Eliseo Marcos Guallar
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Outside Other
Organization
Name
N/A
College Name
N/A
Section Name
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
https://pubmed.ncbi.nlm.nih.gov/?term=Guallar+E
430+ publications
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
0
0
0
58
Resume of Eliseo Marcos Guallar
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
0
0
0
0
0
0
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
0
0
0
0
0
0
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
0
0
0
59
Resume of Mohamed Elyasa Ibrahim
PERSONAL DETAILS
Name
Dr. Mohamed Elyasa Ibrahim
Gender
Male
DOB
01/01/1976
Nationality
Sudan
Passport Number
P01832131
Passport Issue Date
14/05/2015
Passport Expiry Date
13/05/2020
ORCID
0000-0002-4165-433X
CONTACT DETAILS
Email
mdelyasa@gmail.com
Alternate Email
moqasimovish@gmail.co
m
Address 1
5501 Seminary Rd
Address 2
N/A
Postal Code
22041
PO Box
2609-S
Country
United States of America
City
Falls Church
Phone Number
2023753789
Fax
N/A
Mobile
1-2023753789
QUALIFICATION
Qualification
Country
University
Specialization
Year
Grade
Master
(fellowship)
Netherland
Maastricht University
Medical Sciences
2008
Very Good
Master
Netherland
Maastricht University
Medical Sciences
2005
Very Good
Bachelor
Sudan
Gezira University
Medical Sciences
2001
Very Good
EXPERIENCE
Organization
Job Title
Address
From
To
Responsibilities
Leaf LLC
Business
Development
Manager
401 Aldersgate
Dr, Denton, MD,
USA
01/07/2018
Till Date
Managing Parter
Ministry of
Health
Epidemiologist
Alwesham,
Riyadh, Saudi
Arabia
01/09/2011
01/06/2018
N/A
Prince Sultan
Cardiac Centre
Epidemiologist
Riyadh, Saudi
Arabia
01/09/2008
20/08/2011
N/A
INTERESTS
Field
Interest
Sub Interest
No record exists
60
Resume of Mohamed Elyasa Ibrahim
CONSULTATION
Organization
Country
Description
No record exists
MEMBERSHIP
Organization Name
Membership Number
Start Date
End Date
Status
No record exists
ORGANIZATION DETAILS
Organization Type
Outside Other
Organization
Name
N/A
College Name
N/A
Section Name
Current Activities
N/A
Keywords
N/A
PERSONAL STATEMENT
Please provide a summary of your current and future research goals
PEER-REVIEWED PUBLICATIONS
Articles published in peer-reviewed journals relevant to the proposed work (up to 10)
Citation details (e.g. authors, year, title, journal,
volume, page number)
DOI
Charbel El Bcheraoui, Mohammed Basulaiman,
Mohammad A AlMazroa, Marwa Tuffaha, Farah
Daoud, Shelley Wilson, Mohammad Y Al Saeedi,
Faisal M Alanazi, Mohamed E Ibrahim, Elawad M
Ahmed, Syed A Hussain, Riad M Salloum, Omer Abid,
Mishal F Al-Dossary, Ziad A Memish, Abdullah A Al
Rabeeah, Ali H Mokdad (2015). Fruit and vegetable
consumption among adults in Saudi Arabia, 2013.
Nutrition and Dietary Supplements,
41—49
https://doi.org/10.2147/NDS.S77460
•
Fahad Alnouri, D. Wood, Kornelia Kotseva, M.
Ibrahim, (2014). Which statin worked best to achieve
lipid level targets in a European registry? A post-hoc
analysis of the EUROASPIRE III for coronary heart
disease patients. J Saudi Heart Assoc,
183–191
10.1016/j.jsha.2014.04.005
CONFERENCE PROCEEDINGS
Publications in conference proceedings (abstracts or conference papers) relevant to the proposed
work (up to 10)
Citation details (e.g., authors, year, title, conference)
No record exists
61
Resume of Mohamed Elyasa Ibrahim
BOOK CHAPTERS AND OTHER PUBLICATION FORMS
Book chapters, articles, and other academic non-peer-reviewed publications (up to 10)
Citation details (e.g., authors, year, title, publisher)
No record exists
PATENTS
Patents in the last 5 years related to the proposed work
Patent Description
Issuing Authority
Year
No record exists
MENTORING EXPERIENCE
Number (#) of current doctoral students(Ph.D.)
Women(#)
Men(#)
Total # of all
students
No record exists
Number (#) of former doctoral (Ph.D.) advised in last 5 years (not including the current)
Women(#)
Women who
received Ph.D.
(#)
Men(#)
Men who
received
Ph.D.(#)
Total # of
all
students
Total # of all
students who
received Ph.D.
No record exists
Number (#) of former master (M.S.) advised in last 5 years (not including the current)
Women(#)
Women who
received M.S.(#)
Men(#)
Men who
received
M.S.(#)
Total # of
all
students
Total # of all
students who
received M.S.
No record exists
CURRENT FUNDING
Projects that are currently funded
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
PENDING FUNDING
Proposals that have been submitted to funding competitions and are awaiting a decision
Project Title
Funding Organization
Requested
Award Amount
Expected Start
Date
Expected
End Date
No record exists
Number (#) of current master students (M.S.)
Women(#)
Men(#)
Total # of all
students
No record exists
62
Resume of Mohamed Elyasa Ibrahim
RECENT PAST FUNDING
Projects that were funded and have been completed in the last 5 years
Project Title
Funding Organization
Award Amount
Start Date
End Date
No record exists
63
Copyright Notice
© Licențiada.org respectă drepturile de proprietate intelectuală și așteaptă ca toți utilizatorii să facă același lucru. Dacă consideri că un conținut de pe site încalcă drepturile tale de autor, te rugăm să trimiți o notificare DMCA.
Acest articol: Grant Programs for Universities And Research Centers [617223] (ID: 617223)
Dacă considerați că acest conținut vă încalcă drepturile de autor, vă rugăm să depuneți o cerere pe pagina noastră Copyright Takedown.