 Hi, I'm Balogun Steving and thanks for tuning in to my lightning talk on digital analysis using the TIGI NDR. First day introduction. Forty years have passed since the first case of HIV rates, yet in the year 2020, 1.5 million people were nearly infected with the virus. 690,000 people died of rates related in essence, and approximately 37.6 million people were living with HIV rates. While remarkable progress has been reported in the last decade, inequity between Amidian countries continue to have the epidemic. Those some countries have attained epidemic control, many are off track with COVID-19 conflict and humanitarian emergencies reversing the case. The rates are set to the ambitious identity to achieve epidemic control of HIV rates by year 2030 through identification of at least 95% of persons living with the virus, retaining 95% of those identified on treatment, and achieving virus suppression at least 95% of those on treatment. Nigeria has the fourth largest epidemic in the world, with an estimated 1.5 million people living with HIV. At the end of 2020, the progress across the three 95s are 73%, 89%, and 78%, with very privileged progress across the states as shown by the map. To achieve the innate standard, granular data at community, local government, and sub-population levels must continuously be made available, i.e. utilized by a fund decision. In 2016, through the preferred support, the journey to the Nigeria National HIV Data Reprocessory started. The Reprocessory contains the identified reports of over 1.5 million HIV clients on treatment across the country. This is accessible to persons within the country to track progress and improve programmer address levels. A line list of these clients can be downloaded for further analysis and use. The picture below shows the snapshot of the NDR public dashboard. According to the PEPFA Monetary Evaluation and Reporting guideline version 2.5, it is essential to not only capture high quality data, but to also continuously use and analyze the data to achieve maximum programming path. The only way to improve data is to use the data. However, analysis of the downloaded data is traditionally conducted through special applications. While this provides a great platform, the downside is include, the software must be installed on the user's computer, the user must be familiar with the formula for the calculations. The point-and-click nature of the analysis makes it a platform with difficult reproducibility. Also, performing the same analysis vertically can require tedious and time-consuming. Therefore, the cross-functional team of seven clinical and data experts came together to put the TIDI NDR package to support analysis of the NDR pressure guidelines. This package was designed in line with the data science work proposed by Adlericam. Variant functions are responsible for importing, tidying, transforming, and summarizing the data. Line tidyverse and tidyverse related packages were used in the development of the TIDI NDR package. It's available for installation from both the Github and CRAM. Where possible, we named the functions similar to the PEPFA program indicators that users are already familiar with. These functions are grouped into one important function, seven treatment-related functions, four parallel functions, and so several functions. The benefits of the package include it provides a platform for data analysis and automation of project projects. Analysis conducted using the package is reproducible. It can be used in a light volume of data. It supports easy identification of program graphs for tailored intervention and provides a foundation upon which other relevant program applications can be built. This many-hands dashboard and the weekly detailed analysis showed underlight where some of the examples of applications fit on the package. We are courage to try the package out, give us feedback, and we welcome your contributions and suggestions. Thank you for your time.