Adil I. El Awad
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Adil I. El Awad has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Eihab Fathelrahman
Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, United Arab Emirates
3 shared publications - Yassir Mohammed Eltahir
Animals Extension and Health Services Division, Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), Abu Dhabi 52150, United Arab Emirates
3 shared publications - Aaron Reeves
Department of Biology, Colorado State University, Fort Collins, CO 80523, USA
1 shared publication - Aaron Reeves
Epidemiology Research Unit, Department of Veterinary and Animal Science, Northern Faculty, Scotland’s Rural College (SRUC), Inverness EH9 3JG, UK
1 shared publication - Abdelmalik Ibrahim Khalafalla
Biosecurity Affairs Division, Development and Innovation Sector, Abu Dhabi Agriculture and Food Safety Authority (ADAFSA), Abu Dhabi, United Arab Emirates
1 shared publication - Afra Abdalla
Veterinary Public Health Research Laboratory, Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain P.O. Box 1555, United Arab Emirates
1 shared publication
Latest Publications
- Open Access
Epidemiology and Scenario Simulations of the Middle East Respiratory Syndrome Corona Virus (MERS-CoV) Disease Spread and Control for Dromedary Camels in United Arab Emirates (UAE)
Middle East Respiratory Syndrome (MERS-CoV) is a coronavirus-caused viral respiratory infection initially detected in Saudi Arabia in 2012. In UAE, high seroprevalence (97.1) of MERS-CoV in camels was reported in several Emirate of Abu Dhabi studies, including camels in zoos, public escorts, and slaughterhouses. The objectives of this research include simulation of MERS-CoV spread using a customized animal disease spread model (i.e., customized stochastic model for the UAE; analyzing the MERS-CoV spread and prevalence based on camels age groups and identifying the optimum control MERS-CoV strategy. This study found that controlling animal mobility is the best management technique for minimizing epidemic length and the number of affected farms. This study also found that disease dissemination differs amongst camels of three ages: camel kids under the age of one, young camels aged one to four, and adult camels aged four and up; because of their immunological state, kids, as well as adults, had greater infection rates. To save immunization costs, it is advised that certain age groups be targeted and that intense ad hoc unexpected vaccinations be avoided. According to the study, choosing the best technique must consider both efficacy and cost.
Open AccessEpidemiology and Scenario Simulations of the Middle East Respiratory Syndrome Corona Virus (MERS-CoV) Disease Spread and Control for Dromedary Camels in United Arab Emirates (UAE)
Middle East Respiratory Syndrome (MERS-CoV) is a coronavirus-caused viral respiratory infection initially detected in Saudi Arabia in 2012. In UAE, high seroprevalence (97.1) of MERS-CoV in camels was reported in several Emirate of Abu Dhabi studies, including camels in zoos, public escorts, and slaughterhouses. The objectives of this research include simulation of MERS-CoV spread using a customized animal disease spread model (i.e., customized stochastic model for the UAE; analyzing the MERS-CoV spread and prevalence based on camels age groups and identifying the optimum control MERS-CoV strategy. This study found that controlling animal mobility is the best management technique for minimizing epidemic length and the number of affected farms. This study also found that disease dissemination differs amongst camels of three ages: camel kids under the age of one, young camels aged one to four, and adult camels aged four and up; because of their immunological state, kids, as well as adults, had greater infection rates. To save immunization costs, it is advised that certain age groups be targeted and that intense ad hoc unexpected vaccinations be avoided. According to the study, choosing the best technique must consider both efficacy and cost.
- Open Access
Epidemiology and Cost of Peste des Petits Ruminants (PPR) Eradication in Small Ruminants in the United Arab Emirates—Disease Spread and Control Strategies Simulations
Peste des petits ruminants (PPR) is an important infectious viral disease of domestic small ruminants that threatens the food security and sustainable livelihood of farmers across Middle East, Africa, and Asia. The objective of this research is to analyze the disease’s spread and its impacts on direct government costs through conducting three simulations of different control strategies to reduce and quickly eradicate PPR from the United Arab Emirates in the near future. A Modified Animal Disease Spread Model was developed in this study to suit the conditions of the United Arab Emirates. The initial scenario represents when mass vaccination is ceased, and moderate movement restrictions are applied. The second scenario is based on mass vaccination and stamping out the disease, whereas the third simulation scenario assumes mass and ring vaccination when needed, very strict movement control, and stamping out. This study found that the third scenario is the most effective in controlling and eradicating PPR from the UAE. The outbreak duration in days was reduced by 57% and the number of infected animals by 77% when compared to the other scenarios. These results are valuable to the country’s animal health decision-makers and the government’s efforts to report to the World Animal Health Organization (OIE) regarding the progress made towards declaration of the disease’s eradication. They are also useful to other concerned entities in other Middle Eastern, North African, and Asian countries where the disease is spreading.
Open AccessEpidemiology and Cost of Peste des Petits Ruminants (PPR) Eradication in Small Ruminants in the United Arab Emirates—Disease Spread and Control Strategies Simulations
Peste des petits ruminants (PPR) is an important infectious viral disease of domestic small ruminants that threatens the food security and sustainable livelihood of farmers across Middle East, Africa, and Asia. The objective of this research is to analyze the disease’s spread and its impacts on direct government costs through conducting three simulations of different control strategies to reduce and quickly eradicate PPR from the United Arab Emirates in the near future. A Modified Animal Disease Spread Model was developed in this study to suit the conditions of the United Arab Emirates. The initial scenario represents when mass vaccination is ceased, and moderate movement restrictions are applied. The second scenario is based on mass vaccination and stamping out the disease, whereas the third simulation scenario assumes mass and ring vaccination when needed, very strict movement control, and stamping out. This study found that the third scenario is the most effective in controlling and eradicating PPR from the UAE. The outbreak duration in days was reduced by 57% and the number of infected animals by 77% when compared to the other scenarios. These results are valuable to the country’s animal health decision-makers and the government’s efforts to report to the World Animal Health Organization (OIE) regarding the progress made towards declaration of the disease’s eradication. They are also useful to other concerned entities in other Middle Eastern, North African, and Asian countries where the disease is spreading.
- Open Access
- 24 September 2020
- Published by MDPI AG in Agriculture
- Vol. 10 (10) , 426
Biosecurity Preparedness Analysis for Poultry Large and Small Farms in the United Arab Emirates
Biosecurity implemented on the poultry farms in the United Arab Emirates (UAE), in the form of preparedness against any possible outbreak of disease, is critical for farm survival, safety, and development. Little information on the status of biosecurity readiness for containing any outbreak of poultry disease is available. This study was conducted to evaluate the status of biosecurity on commercial poultry farms in the UAE. Four categories of biosecurity measures/actions: isolation, human and traffic flow, cleaning, and disinfection, and adoption of vaccination protocols were considered. All 37 licensed commercial poultry farms in the country were enrolled in the study’s survey. Cumulative Distribution Functions (CDFs) and Artificial Neural Network statistical (ANN) methods were used for ranking biosecurity on farms, including a breakdown for large and small farms, and to identify areas that require improvements. The ANN is used to correlate preparedness in the focus areas to the poultry farms’ biophysical and business characteristics, such as the number of yearly flock cycles, farm capacity, the total area of the farms, density, and the number of biosecurity workers. This study finds that more stringent implementation of vaccination protocol, isolation, and human and vehicle-flow controls for disinfection are most needed. The study also revealed that poultry farms address biosecurity preparedness differently based on the type of production on large or small farms, and for broilers or layers.
- 24 September 2020
- Published by MDPI AG in Agriculture
- Vol. 10 (10) , 426
Open AccessBiosecurity Preparedness Analysis for Poultry Large and Small Farms in the United Arab Emirates
Biosecurity implemented on the poultry farms in the United Arab Emirates (UAE), in the form of preparedness against any possible outbreak of disease, is critical for farm survival, safety, and development. Little information on the status of biosecurity readiness for containing any outbreak of poultry disease is available. This study was conducted to evaluate the status of biosecurity on commercial poultry farms in the UAE. Four categories of biosecurity measures/actions: isolation, human and traffic flow, cleaning, and disinfection, and adoption of vaccination protocols were considered. All 37 licensed commercial poultry farms in the country were enrolled in the study’s survey. Cumulative Distribution Functions (CDFs) and Artificial Neural Network statistical (ANN) methods were used for ranking biosecurity on farms, including a breakdown for large and small farms, and to identify areas that require improvements. The ANN is used to correlate preparedness in the focus areas to the poultry farms’ biophysical and business characteristics, such as the number of yearly flock cycles, farm capacity, the total area of the farms, density, and the number of biosecurity workers. This study finds that more stringent implementation of vaccination protocol, isolation, and human and vehicle-flow controls for disinfection are most needed. The study also revealed that poultry farms address biosecurity preparedness differently based on the type of production on large or small farms, and for broilers or layers.