अमूर्त
Malaria is one of the most dangerous disease for human
Atef Ali
Malaria is one of the most dangerous disease for human which causing death of over than half million people annually which is 90% of them are children under five years of age in addition to pregnant women. An important question needs a compelling logical answer; within the presence of both sensitive methods of laboratory diagnosis and an effective anti-malaria drugs; why still this large number of incidence and mortality in malaria cases. To win the battle it is not enough standby equipment’s and own the strongest power but need management skills for both the time and the resources. Therefore, establishing a logical and scientific algorithm for management of malaria cases is the best choice to decrease of the mortality numbers of deaths causes by malaria. To establish and prepare an effective algorithm it must be taken in account a comprehensive knowledge and background about the life cycle for the malaria plasmodium parasite in the patient’s body and what are the stages of the parasite appear in blood sample and what the importance of each phase of these stages is. The issue of parasite counting and determination and estimated the parasitemia density and know what the border levels for the risk indicators as a quantity are or as a type. Biography: Atef Ali spent 40 years’ experience working in Malarial field. He has got the chance to work in both malaria lab oratories departments, the entomological and the parasitological lab. Mr. Atef is a member of the malarial technologist’s team who participated in the UAE national program for eradication malaria disease and assisted in the success of the program, which had been certified by WHO among announced the UAE is free of malaria transmission. Recent Publications: 1. The Importance of Learning Identification of Larvae and Adult Mosquitoes, September 22, 2017 2. THE IMPORTANCE OF LEARNING IDENTIFICATION OF LARVAE AND ADULT MOSQUITOES, Virology Research Journal, June 25-26, 2018. 3. Development of rapid immuno-diagnostic test for the early detection of tuberculosis, 2017.