I love math because it turns a messy health problem into a question I can test. In epidemiology, a claim means little without numbers behind it. A rate needs a denominator. A difference needs a measure of uncertainty. Math gives me the tools to check whether a pattern is real or just noise. That discipline has shaped every stage of my work. I studied Environmental Health Sciences at Muhimbili University of Health and Allied Sciences in Tanzania and graduated with a CGPA of 3.87 out of 4.00. I later taught epidemiology and biostatistics at MCHAS. Teaching forced me to explain ideas clearly. A student who fears formulas can still learn what a mean, a rate, and a confidence interval do if the example comes from real health data. Math also sits at the center of my research. I work as a research assistant in Epidemiology at the Johns Hopkins Bloomberg School of Public Health, where I am completing an ScM in Epidemiology in the General Epidemiology and Methodology track with a GPA of 3.9 out of 4.0. I have published 19 papers, 8 as first author. I created qtbi, my first R package on CRAN, so a method I use could be run by other researchers. Writing that package meant turning math into code that had to be correct every time. I was also selected as a 2026 Data Science for Social Good Fellow at Johns Hopkins. That work uses data to address social problems, and math is the part that keeps the conclusions honest. I do not love math as an abstract exercise. I love it because a correct calculation can change a decision about screening, treatment, or prevention, and a wrong one can waste scarce resources.

My definition of the American dream is simple. It is the chance to study at a level that was not available to me at home, and to use that training to do work that helps other people. I grew up in Mwanza, Tanzania. I am the first person in my family to earn a college degree. No one in my family had a degree before me, so I had to learn how higher education worked on my own. I completed a BSc in Environmental Health Sciences at Muhimbili University of Health and Allied Sciences in Dar es Salaam. I graduated with first class honors and a CGPA of 3.87 out of 4.00. Before and after that degree, my work stayed close to the community. I interned with the Tanzania Ministry of Health. I worked as a Data Scientist with the Mo Dewji Foundation. I taught epidemiology and biostatistics at MCHAS. I also took part in community outreach that reached more than 5,000 people. That outreach taught me a basic lesson. Good health information only matters if people can hear it, understand it, and act on it. In August 2025, I started the ScM program in Epidemiology at the Johns Hopkins Bloomberg School of Public Health in Baltimore. I am in the General Epidemiology and Methodology track. My GPA is 3.9 out of 4.0. I work as a research assistant in Epidemiology at Johns Hopkins. In 2026, I was selected as a Data Science for Social Good Fellow at Johns Hopkins. I have published 19 papers, with 8 as first author. I also created qtbi, my first R package on CRAN. I built it so other researchers could use the method without extra cost. None of this made funding easy. I am an international student from Tanzania on an F-1 visa. I live in Baltimore while I study. I need funding for my third and fourth terms. The gap is 18,000 dollars, and I graduate in December 2026. That gap is the main barrier between me and finishing the degree I came here to earn. For me, the American dream is not wealth on its own. It is access. It is a classroom, a lab, and a fair chance to compete based on the quality of your work. It is also responsibility. If I receive that access, I should return value. My plan is to finish my training in epidemiology and keep building tools and studies that improve public health in places with limited resources, including Tanzania. A scholarship of 1,000 dollars would help cover part of my tuition for the terms ahead. It would reduce the amount I still need to find. It would also be a direct statement that a first generation student from Mwanza belongs in this field and can finish what he started.

My contribution would be practical: measure who mental health care does not reach, and publish that work in a form other teams can use for free. I am a ScM student in Epidemiology at the Johns Hopkins Bloomberg School of Public Health, with a 3.9 GPA. Before Hopkins, I earned a first-class BSc in Environmental Health Sciences at MUHAS in Tanzania. Community outreach I took part in in Tanzania reached more than 5,000 people. It covered HIV prevention, maternal health, menstrual hygiene, and handwashing. The work was in person, and it was free to the people who came. Cost is one reason people do not get care. Distance and a lack of local staff are others. None of those show up unless someone counts them by place and by group. That counting is epidemiology. I work as a research assistant and a teaching assistant at Hopkins, I have 19 publications, and my first R package, qtbi, is on CRAN at no charge to users. I would apply the same approach to mental health services: count use and unmet need by community, share the results openly, and design outreach with local workers, as we did in Tanzania.

I am January G. Msemakweli, a first-generation college student from Mwanza, Tanzania. I grew up in Kahama. No one in my family has a degree, and I was the first in my clan to leave Africa. I earned a BSc in Environmental Health Sciences with first-class honors at MUHAS in Tanzania, finishing with a CGPA of 3.87 out of 4.00 in December 2023. I now study for a ScM in Epidemiology at the Johns Hopkins Bloomberg School of Public Health, where I hold a 3.9 GPA. I need funding for terms 3 and 4 of the program. The gap is $18,000. Work shaped my goals before this degree did. I taught epidemiology and biostatistics at MCHAS. I worked as a Data Scientist at the Mo Dewji Foundation from March 2025 to March 2026. Community outreach I took part in in Tanzania reached more than 5,000 people. At Hopkins I work as a research assistant and a teaching assistant in Epidemiology. I am a 2026 Data Science for Social Good Fellow. I have 19 publications, 8 as first author, and I am a peer reviewer for Cureus and for Internal and Emergency Medicine. My first R package, qtbi, is on CRAN. My goal is specific. I want to keep doing epidemiology research and teaching, and to make methods available to researchers who cannot pay for them. A package on CRAN costs its users nothing. Outreach in Tanzania taught me a similar point in a different setting: people use a health service more when someone explains it clearly and in person. This scholarship would pay part of the $18,000 I still need for terms 3 and 4. That would let me finish the ScM without stopping the research and teaching work I am already doing.

I started in health work in Tanzania, not in a classroom. As an intern with the Ministry of Health in Pwani, I did facility inspections and checked vaccine cold chains. Later I ran community outreach on HIV prevention, maternal health, menstrual hygiene, and handwashing that reached more than 5,000 people, and I trained health workers in Kibaha on waste management. The pattern was the same in each place. People used a service when the person in front of them spoke their language, knew their town, and did not need their life explained to them first. That pattern followed me to Baltimore. At Charm City Care Connection, I built the data system the outreach team uses to document and map needle collection and harm reduction work. People who inject drugs decide in seconds whether a service is safe for them. Who staffs it, and who designed it, is part of that decision. My goal is to do epidemiology that starts from that fact. I am finishing a master's degree in epidemiology at the Johns Hopkins Bloomberg School of Public Health. My thesis studies cervical cancer screening among women in four sub-Saharan African countries and asks whether health insurance and HIV status change who gets screened. I work as a research assistant and a teaching assistant, I have published on antimicrobial resistance, malaria, and hospital care, and my first R package is on CRAN so other researchers can use the method without charge. Diversity in healthcare matters for a practical reason: it changes what gets measured. A research team decides which questions are worth asking, which variables a survey collects, and whose records are complete enough to analyse. A clinic decides which complaints get believed quickly. When Black patients and Black communities are missing from those rooms, whole exposures go unrecorded, and the papers and policies built on that data inherit the gap. I have seen the other side of it. In Tanzania I was the local person in the room. In the United States I am often the only Tanzanian, and sometimes the only Black analyst, in the room. Both positions taught me things the data alone would not have. After finishing this degree I want a research role at Hopkins, then a PhD. The work stays the same either way: count the people who are usually left out, and build the tools so the next team can count them too.

My name is January G. Msemakweli. I am a Tanzanian public health researcher and data scientist, and I am now pursuing a Master of Science in Epidemiology at the Johns Hopkins Bloomberg School of Public Health. I am the first person in my family and in my clan to earn a college degree. That single fact is the adversity that has shaped my whole educational journey, because I had to learn how higher education works without a guide at home. When I started my undergraduate studies in Environmental Health Sciences at Muhimbili University of Health and Allied Sciences in Tanzania, I did not know how to choose courses, how to approach lecturers, or how to plan for a career in research. My family supported me with encouragement, but they could not answer questions they had never had the chance to face themselves. As a low-income student, I also had to think constantly about money: fees, housing, transport, and the cost of staying in school. These challenges affected my education in two ways. First, they slowed me down at the start. I spent time figuring out basic things that many students learn from parents or siblings who went to college before them. Second, they taught me to work hard and to ask for help. I learned to find mentors, to read beyond the syllabus, and to treat every opportunity as something I could not waste. Over time, the student who once felt lost became a researcher. I have published six first-author papers, I built an R package called qtbi that is available on CRAN, and I served as a Data Science for Social Good Fellow, using data to work on problems that affect the public. The adversity did not end when I came to the United States. I study here as an international student on an F-1 visa, far from my family in Tanzania. I work as a research assistant and graduate student at Johns Hopkins while I study, and I still carry financial need. Being far from home, in a system that is new to me, reminded me of my first days at university. Once again, I had to learn new rules, new expectations, and a new culture, largely on my own. But this time I knew what to do. I asked questions early. I sought out mentors. I kept my long-term goal in front of me: to become an epidemiologist who builds strong data systems for health in low-resource settings, so that outbreaks and other threats are seen early and handled well. My background gives me a clear reason to do this work. I know what it means when health systems and families have very little, because I have lived with very little while trying to learn. Financial support would help me stay focused on my studies and research instead of worrying about how to cover the cost of my education. I have overcome adversity by working steadily, learning from mentors, and refusing to quit when the path was unclear. I plan to use this education to serve communities in Tanzania and other low- and middle-income countries, and to open doors for students who, like me, are the first in their families to reach this level.

I want to build the data systems that let health systems in low-resource settings see threats coming before they arrive. I have built versions of this before. In Tanzania, I worked with the Mo Dewji Foundation on MoAfya Camps, building a digital system that let clinical teams collect and monitor patient data in real time during large-scale health outreach programs. Before that system, teams tracked patients on paper, and reporting was fragmented and delayed. After it, they could see patient flow and outcomes as they happened and make faster decisions about staffing and follow-up care. In Baltimore, I built software for Charm City Care Connection, a harm-reduction organization, that documents and maps needle collection services so outreach teams can see where needs are greatest. Both projects taught me the same lesson: the people doing frontline work know what they need, and a well-built tool multiplies their effort. What I want to build next is bigger. Most health systems in countries like Tanzania are reactive. They respond after disease spreads, after clinics are overwhelmed, after the data finally arrives. I want to build surveillance and analytical systems that detect risk early: pipelines that pull together clinical, environmental, and population data, and models that flag emerging threats while there is still time to act. My research points in this direction. I study critical care epidemiology with MIMIC-IV data, environmental exposures with NHANES, and malaria and anemia inequality with Tanzania DHS data. I am applying to PhD programs in epidemiology for Fall 2027 to train in causal inference methods, because early-warning systems are only useful if their signals are trustworthy. Building this will help me directly: it is the research program I intend to spend my career on, and progress on it strengthens my PhD applications and my training. It will help my community in a concrete way. Stronger data systems mean faster outbreak detection, better-targeted interventions, and fewer preventable deaths in places that cannot afford to waste resources. The MoAfya Camps system showed me that this works at the scale of a health camp. The next step is the scale of a health system. I build because I have seen what happens without the tools: paper records, delayed reports, decisions made too late. I want to build the alternative.

I am a Tanzanian epidemiologist-in-training at the Johns Hopkins Bloomberg School of Public Health, pursuing an ScM in Epidemiology with a 4.0 GPA. I earned my BSc in Environmental Health Sciences with first-class honors from Muhimbili University of Health and Allied Sciences, where I received the Professor Emeritus Japhet Killewo Award for the best performance in Epidemiology. What gives me an advantage is a record of producing work that other people use. I have published six first-author papers. My work in the Journal of Critical Care examined between-hospital variation in liberation from invasive mechanical ventilation. I work with MIMIC-IV data on delirium, acute kidney injury, and ICU-acquired infection. I analyze NHANES data on PFAS and cadmium exposure. I study malaria and anemia inequality in Tanzania with DHS data. I do ToxCast computational toxicology and study CLSI antibiotic breakpoint changes. I also serve as a peer reviewer for Cureus and for Internal and Emergency Medicine. Few graduate students arrive with this volume of finished, published work. I also build things. With the Mo Dewji Foundation in Tanzania, I built MoAfya Camps, a digital system for real-time clinical data collection during large-scale health outreach programs. In Baltimore, I built software for Charm City Care Connection that documents and maps needle collection services for harm-reduction outreach. I work as a research assistant with restricted NHATS data and as a teaching assistant at Johns Hopkins. I received a Community Service Award from SOURCE at Johns Hopkins and was nominated as Student Employee of the Year. I am applying to PhD programs in epidemiology for Fall 2027 to train in causal inference methods and critical care epidemiology. My goal is to build analytical approaches that help countries like Tanzania anticipate and prevent emerging health threats. The honest reason I deserve this scholarship is financial. I am an international student. I received a Public Health Grant and a Merit Tuition Scholarship from Johns Hopkins, but funding terms 3 and 4 of my program remains a challenge. This scholarship would go directly toward tuition, letting me focus on the research and service work described above instead of the gap in my funding. My advantage is that I have already shown what I do with support: I turn it into published research and working tools for people who need them.

I give back in two ways: by building tools for people who serve others, and by doing research that answers questions affecting real patients and communities. The first started in Tanzania. I worked with the Mo Dewji Foundation on MoAfya Camps, large-scale health outreach programs for underserved communities. Clinical teams tracked patients on paper, so reporting was fragmented and slow. I built a digital system that let teams collect and monitor clinical data in real time during health camps. It was unpaid work over many months. Once it went live, teams could see patient flow and outcomes as they happened, which changed how they assigned staff and followed up with patients. The lesson stayed with me: the right tool, built for the people doing the work, multiplies their effort. In Baltimore I do similar work with Charm City Care Connection, a harm-reduction organization. I built software that documents and maps their needle collection services, including a geocoding system that helps outreach teams see where needs are greatest. Harm reduction is stigmatized and underfunded, and the organization could not pay for custom software. I built it because the outreach workers needed it. I also serve as a teaching assistant at Johns Hopkins, spending hours each week helping students master material I have already learned. And I serve as a peer reviewer for Cureus and for Internal and Emergency Medicine, which is unpaid work that keeps published science honest. My research is the other half. I have published six first-author papers. One, in the Journal of Critical Care, examined between-hospital variation in liberation from invasive mechanical ventilation using a competing-risk analysis. I study delirium, acute kidney injury, and ICU-acquired infection with MIMIC-IV data. I analyze NHANES data on PFAS and cadmium exposure and albuminuria. I study malaria and anemia inequality in Tanzania using DHS data. I work on ToxCast computational toxicology and on CLSI antibiotic breakpoint changes. Each project starts from the same question: what do clinicians and policymakers need to know to make better decisions? I was recognized with a Community Service Award from SOURCE at Johns Hopkins and nominated as Student Employee of the Year, which tells me the pattern is visible to others too. In the future I want to scale both halves. I am applying to PhD programs in epidemiology for Fall 2027, with research interests in causal inference methods and critical care epidemiology. My long-term goal is to become an epidemiologist who builds analytical approaches that help countries like Tanzania anticipate and prevent emerging health threats through stronger data systems and evidence-driven policy. Too many health systems only react after disease spreads. I want to help build systems that detect risk early and prevent harm before communities suffer. The plan is concrete. Finish the ScM in Epidemiology in 2027. Complete a PhD with rigorous training in causal inference. Keep building tools with and for the organizations doing frontline work, in Baltimore and in Tanzania. Keep publishing research that clinicians can use. Giving back, for me, is not separate from my career. It is the career: use data and epidemiology to make health systems work better for the people who need them most.

I measure my work by whether it helps people who need it. Two projects show what that means in practice. In Tanzania, I worked with the Mo Dewji Foundation on MoAfya Camps, large-scale health outreach programs serving underserved communities. Clinical teams were tracking patients and outcomes on paper, which meant reporting was fragmented and decisions were slow. I built a digital system that let outreach teams collect and monitor clinical data in real time during health camps. The work was unpaid and took months of evenings. When the system went live, teams could see patient flow and outcomes as they happened instead of weeks later. That changed how they allocated staff and followed up with patients. In Baltimore, I volunteer with Charm City Care Connection, a harm-reduction organization. I built software that documents and maps their needle collection services, including a geocoding system that helps outreach teams map service locations and identify where community needs are greatest. Harm reduction work is stigmatized and underfunded. The organization needed better tools but could not pay for them. I spent my time building those tools because the outreach workers needed them and the people they serve deserved better. I also serve as a teaching assistant at Johns Hopkins, which means spending hours each week helping other students understand material I have already mastered. It is not the highest-paying use of my time. I do it because I remember what it was like to struggle with difficult coursework and because someone helped me when I needed it. These choices come from how I was raised and what I have seen. I grew up in Tanzania, where I watched health outcomes depend not only on medicine but on whether systems existed to detect risks early and respond. I come from a modest background. Pursuing graduate education abroad required overcoming significant financial barriers, and I received a Public Health Grant and a Merit Tuition Scholarship from Johns Hopkins. People invested in me. I take that seriously, and I repay it by investing my skills where they are needed most. My research follows the same principle. I have published six first-author papers, including work in the Journal of Critical Care on between-hospital variation in liberation from invasive mechanical ventilation. I study delirium, acute kidney injury, and ICU-acquired infection using MIMIC-IV data. I analyze NHANES data on PFAS and cadmium exposure. I work on malaria and anemia inequality using Tanzania DHS data. None of this is abstract to me. Each project is an attempt to answer a question whose answer could change how care reaches people. I was recognized with a Community Service Award from SOURCE at Johns Hopkins and nominated as Student Employee of the Year. I did not seek those. I mention them only to show that the people around me have noticed the pattern: I show up, I do the work, and I do it for others. Selflessness, to me, is not a feeling. It is a habit of choosing work that serves people over work that serves only yourself. I have built that habit into my career, and I intend to keep it.

My interest in supporting individuals with intellectual disabilities comes from a broader commitment to building health systems that serve everyone, especially populations that are often overlooked. Throughout my academic and professional journey in public health, I have become increasingly aware that individuals with intellectual and developmental disabilities frequently face barriers in accessing healthcare, education, and social services. These barriers are not only medical but also structural, reflecting gaps in awareness, resources, and inclusive policy. I am currently pursuing a Master of Science in Epidemiology at the Johns Hopkins Bloomberg School of Public Health, where my work focuses on understanding patterns of disease and improving population health systems. Epidemiology provides powerful tools for identifying health disparities and designing interventions that can improve outcomes for underserved communities, including individuals with intellectual disabilities. One of the realities that motivates my work is the fact that many public health systems were historically designed without considering the needs of people with disabilities. As a result, individuals with intellectual disabilities often experience poorer health outcomes, reduced access to preventive care, and greater social isolation. These disparities highlight the need for research and policies that intentionally include disability perspectives. My experience living with noise-induced hearing loss has also shaped how I understand accessibility and inclusion. While hearing loss differs from intellectual disability, it has helped me recognize how easily environments can become barriers when accessibility is not considered. This awareness has strengthened my commitment to ensuring that health systems and community programs are designed with diverse needs in mind. In my academic and community work, I seek opportunities to translate these values into real-world impact. For example, through my work with Charm City Care Connection in Baltimore, I helped develop a geocoding system that supports harm reduction outreach programs. The system allows outreach teams to map service locations and identify where community needs are greatest. Projects like this demonstrate how data and technology can improve how public health programs reach underserved populations. Looking ahead, my career goal is to use epidemiology and public health research to better understand the health needs of populations that are often marginalized, including individuals with intellectual disabilities. By studying patterns in healthcare access, disease risk, and social determinants of health, I hope to contribute to policies and programs that create more inclusive health systems. Supporting the intellectual disability community requires more than medical care; it requires societal commitment to dignity, inclusion, and equity. Public health research has the potential to play an important role in this effort by generating evidence that informs policy and expands access to services. Ultimately, my goal is to ensure that the systems we build reflect the needs of all individuals, including those whose voices are too often excluded from decision-making processes. By combining research, data-driven solutions, and community engagement, I hope to contribute to a future where individuals with intellectual disabilities receive the respect, support, and opportunities they deserve.

My name is January G. Msemakweli, a Tanzanian public health researcher currently pursuing a Master of Science in Epidemiology at the Johns Hopkins Bloomberg School of Public Health. I grew up seeing how health outcomes in many communities depend not only on medicine, but on whether systems exist to detect risks early and respond effectively. That reality shaped my decision to pursue public health and continues to drive the work I do today. I come from a modest background, and pursuing graduate education abroad required overcoming significant financial barriers. Although I was fortunate to receive a Public Health Grant and a Merit Tuition Scholarship from Johns Hopkins, financing graduate education as an international student remains challenging. These obstacles, however, have strengthened my determination to succeed and to ensure that the opportunities I have been given translate into meaningful impact for others. Service has always been central to my work. Before coming to the United States, I worked with the Mo Dewji Foundation, where I supported health outreach programs serving underserved communities. During these programs I saw firsthand how difficult it was for clinical teams to track patients and evaluate outcomes using paper records. To help address this challenge, I developed a digital system that allowed outreach teams to collect and monitor clinical data in real time during health camps. What had previously been fragmented and delayed reporting became a tool that helped teams make faster and more informed decisions about patient care. Experiences like this reinforced my belief that public health progress depends not only on compassion but also on strong data systems that allow limited resources to be used more effectively. My research now focuses on population health analytics and disease prevention. I have contributed to peer reviewed work examining environmental health risks and emerging disease patterns, and I aim to continue developing analytical tools that help health systems detect risks earlier and respond more effectively. Ultimately, my goal is to help strengthen data driven public health systems in Tanzania and across Africa. I want to contribute to a future where health systems do not simply react to disease after it spreads, but anticipate risks and prevent them before communities suffer the consequences. Support from the ADP Scholarship would help ease the financial pressures of graduate school and allow me to focus fully on the work I am committed to: using science, data, and service to improve the health of communities that need it most.