Yes yes...I'm still actually working over here in Uganda...thought it might be time to give you all a work-related update :)

​CHAI is supporting the Ministry of Health pilot a 9 month rapid antibody test as part of the EID (early infant diagnosis) testing algorithm. The goal is to identify HIV+ infants as soon as possible so they can start on treatment immediately. 

Currently, the guidelines say that healthcare workers should do a 1st DNA PCR (polymerase chain reaction)at 6 weeks and then a 2nd DNA PCR 6 weeks after the mother stops breastfeeding (usually just over a year). While the infants are young, they carry maternal antibodies, so the tests look at an infant's DNA directly. At or after 18 months, infants will be given a rapid antibody test which is the same test an adult would receive. 

Rapid tests are cheaper and easier to perform compared to DNA PCR tests which require removal of hemoglobin from the blood in order to obtain leukocytes from which purified genomic DNA is isolated. While facilities can perform their own rapid tests, DNA PCR test samples are collected at the facilities, delivered by hub riders to the local post office and run in the central lab in Kampala. The turn around time (TAT) for results is approximately 2 weeks. While the TAT has decreased over the past few years thanks to some hard work from our labs team, any TAT at all increases the risk of mothers and caregivers not coming back to pick up their results.
 
Introducing a 9 month test between the 1st and 2nd DNA PCR would help identify exposed infants who seroconvert (basically means they weren't showing signs of the virus but now are) after a negative 1st DNA PCR. Additionally, there have been some studies showing that maternal antibodies usually clear by 9-12 months (though they can remain until 18 months and in mothers who continue to breast feed). Lastly, the uptake of the measles vaccine, which is administered at 9 months, is around 95% in Uganda, so the hope is to capitalize on the fact that mothers are bringing their children to the facilities already.
 
The pilot will help us gain insights into the operational challenges we will encounter (and yes, there will be many) so that we can apply lessons learned to the scale-up process. We trained healthcare workers in February and are doing some data collection right now so hopefully we'll see strong uptake of the 9 month test!

Here are the current (left) and proposed (right) testing algorithms in case you're interested.

After a 1:45 AM wake-up call to watch the Superbowl, I spent the day at Buwama Health Center III.
 
I am working to support a National Technical Support Supervision where members of the MOH and other IPs are visiting about 100 facilities across the country. We have a 30+ page questionnaire that we go through at each site to understand to extent at which facilities are using nationally provided tools, supplies, and recommended patient flow / patient care processes. We then wrap up the visit by debriefing with the available facility staff and developing an action plan with owners and deadlines (#PMOmg). So far, I’ve been to five facilities and it’s been incredibly eye opening. It’s easy to back up pilot recommendations or national roll-out strategies with some data, but actually seeing how things are done (or not done) on the ground has provided invaluable context to the work I’m doing. The quantitative and (potentially more impactful) qualitative data we are collecting will be compiled and shared with DHOs (district health officers) nationally in the coming months.
 
The first two facilities we went to were doing a great job. The staff was engaged, open to our suggestions, and seemed to be doing all they could to provide high quality care to the large volume of patients that arrived each day. While that was awesome to see, it almost discouraged me a bit about the strengthening work we are doing. It made me feel like without hiring a lot more staff and building more rooms to see patients, we’re grasping at straws hoping we get lucky that the infants or children we test are from the frequently cited unidentified HIV+ population.
 
The third facility, which was pretty rural, was not performing at the same standards at all. Their in-charge seemed detached and unaware of all the problems in his facility. The majority patients they were able to identify were not being retained on ART treatment. My program manager tried to express the gravity of this situation by explaining that the poor healthcare and follow-up services would have a much greater impact on the surrounding villages than they may think. The CD4 cells of those who take 1st line ARVs and then stop after a few months or even a few years, will mutate and become resistant to the drugs. That means that if the patient starts the same treatment regimen again, the drugs will not be as successful in suppressing the virus. The next step would be to put the patient on 2nd line ARVs, but the side effects are much worse. There are 3rd line ARVs but they are not available in Uganda as PEPFAR does not support them. All that being said, having poor retention rates for those initiated on care, means that there are HIV+ people in the local community who are not virally suppressed and likely spreading HIV to other people. Those people are getting a mutated strain of HIV that is already resistant to treatment – so if and when they seek treatment, it will not be as successful.
 
That discussion was disheartening and reenergizing at the same time. It showed me firsthand that there is so much work to be done. But, it also made me think about what challenges we’re addressing in our work which are mainly process based (testing at more entry points, following-up with patients via SMS / phone calls / home visits, etc.) versus some of the underlying systematic challenges. At the facility I just discussed, the core issue seemed to be the staff. My team told me that basically the in-charge was linked to a MP (member of parliament) which essentially made him (and his two sons he employed to work there) untouchable. Because the community is small and rural, it’s likely most other folks are closely connected as well rendering them untouchable and it’s hard to incentivize people from other areas to move there to work there.
 
But what if we paid health care workers more? In most cases, they already work for close to nothing and meanwhile we are paying MOH staff to come to meetings. For example, last Friday CHAI hosted a meeting about a new testing algorithm that’s being proposed and every government official in attendance received transport reimbursement (even if coming from Kampala) as well as ~$40USD. Apparently, one of the more recent PEPFAR grants tried to ban the payment of per diems to MOH officials since…it’s their job…but that had to be removed as no one would show up to the important meetings. In the same meeting, someone made a comment about all the efforts around follow-up initiatives. He said that the way we are talking about follow-up assumes that forgetfulness is the reason why mothers are not coming back with their children for treatment. However, we are ignoring that many of these patients don’t live close to facilities and transport costs are high (and if the wait is long, they may have to go home without being seen that day). Perhaps we need to instead hire more VHTs (village health teams) to engage communities and bring treatment to the patient instead of vice versa. 
 
On a lighter note, at Buwama today, I saw the newest born baby I’ve ever seen! I remember growing up always visiting my new cousins a day or two after they’re born, but I was sitting in the maternity ward going through some registers when Brenda, one of my colleagues, and I heard a baby crying from the labor suite across the room from us! I had no idea anything was going on because apparently mothers are not allowed to make noise during labor. About 15-20 minutes later, the midwife slowly walked the new mother out and let her rest on a cot in the room. Then another woman brought out the baby for its first feeding! There was no privacy at all, not even curtains. We were sitting maybe 10 feet from her and the door of the room led outside so people were coming in and out frequently. Brenda says she’ll stay there for a night or two before she’s discharged to go home. She had a small suitcase with her with some blankets and clothing. It reminded me of this article another colleague shared last week. What a jarring juxtaposition at the inequity of services and resources mothers-to-be face across the world. As if that isn’t enough…mothers usually will come to the maternity ward when they are in labor…mode of transportation: BODA?!?!
 

Apologies for the silence! All my plans for updating my website and writing about my field visit were foiled by excessive amounts of food, Season 5 of Homeland (read: Taylor Swift movie), and Baby Robert.
 
I’m back in Kampala after a few great weeks at home in California. I felt sort of like I did around Thanksgiving Break freshman year of college. I was excited to return to the comfort and familiarity of home. By comfort, I don’t really even mean unlimited wifi, going places alone in the dark, or stable electricity. I was most looking forward to seeing people that I knew and knew me – making friends is exhausting!
 
The two weeks before traveling home were busy with launching a large data collection exercise for both our Early Infant Diagnosis (EID) and Provider-Initiated Testing and Counseling (PITC) projects. I helped develop a training where we explained the processes and excel templates that we had created. The goal of this exercise (still ongoing) is to collect data on infant and pediatric volumes, testing rates, yields, entry points, and more at select facilities across the country. This data will serve as the baseline that we’ll measure our progress against over the next 3 years (on a quarterly basis). Having just come from a Deloitte project where I was in charge of helping with the cost baselining for a large separation, I’m feeling comfortable with why we’re collecting this data and how we’ll use it. I’ll be in charge of developing a dashboard where we can look at the data dynamically to pull out trends, identify areas where there are some quick wins, and ultimately define the indicators (essentially metrics) that we’ll set in stone to measure against. Most of these we’ve already defined since we needed to understand what data we wanted, but we’ll need to be flexible given the quality / availability of data.
 
I set off to Luwero with two data collectors, Jennifer and Daisy, and our driver, Lastone. We were one of nine teams that traveled between one to six hours to reach health care facilities around the country. With the “jam” (traffic), the 50 mile drive north took between 1.5 – 3 hours. The drive was relaxing and the roads were great (I got lucky with my placement) so in between my naps, I enjoyed the scenery and getting outside the city for the first time.