Augustine Malero is currently working as an HIV Specialist contracted with the CDC in Tanzania. He has seven years of public health experience and an extensive background in computer science! His public health career first began as a Data Manager for a government agency for health and demographics. Then, two years later he attended an Epidemiology and Biotstatistics course in the summer session of Havard’s T.H Chan School of Public Health and was hooked! He found that Epidemiology and Biostatistics was the perfect intersect of his background in Computer science and passion for public health.
His current portfolio of projects includes working with COVID-19 vaccination data and systems supported by PEPFAR. One specific project includes a data quality assessment in CDC supported communities. Augustine provided training to local facilities and conducted quality assessments to mitigate client duplication. Related to this project, he is working on a pilot program which partners with a local agency to use fingerprints as unique identifiers to prevent unintentional duplication. Augustine is looking forward to this pilot and believes it will be “game-changing” for public health in Tanzania.
In the next year, Augustine plans to develop and maintain a master list of facilities that CDC is supporting using unique facility ID numbers which cut across the various systems currently in place. As it stands currently, different systems use different identification numbers to reference the same facility, often causing confusion.
Recent field work with Augustine
For six weeks during the summer, Augustine participated in the DQA activity both onsite and virtually where the CDC SI team provided technical support in the verification of current number of HIV clients for CDC implementing partners across the country. On the ground, he supervised the data collection
teams in Mwanza region ensuring recruited research assistants have the required qualifications, training of research assistants is well conducted, data collection is done according to the protocol established, all data quality issues and challenges are flagged, and partners develop site specific actions and
remediation plans for improving the quality of data and address challenges discovered during the data collection exercise.