From The Conversation
They say timing is everything. And in sub-Saharan Africa, where roughly a third of untreated HIV infected babies die before they reach the age of one, a timely diagnosis is everything.
According to the latest UNAIDS data, 150, 000 children are infected with HIV in sub-Saharan Africa, annually. Due to the high number of children dying, diagnosing babies with HIV as early as possible is critical.
Public health officials have been grappling with this for many years. How can they reduce the time it takes to get newborns’ blood samples to the diagnostic lab and the test results back? This matters because it determines how soon babies can start medical treatment. The average turnaround time in sub-Saharan Africa often range from one to three months.
In general, shorter turnaround times can be achieved by improving the clinic-to-lab supply chain. This can happen through increasing the number of vehicles equipped to transport samples, hiring enough drivers, training enough medical personnel, buying the right type of diagnostic equipment, and improving communication systems.
African countries like Malawi and Nigeria have done this, with impressive results.
But as we show in our new study improving the day-to-day operations of clinic-to-lab supply chains is simply not enough. Sometimes the opportunities lie in the structure of the supply chain itself.
We came to this conclusion after evaluating the early infant diagnosis network in Mozambique. It’s one of many sub-Saharan African nations struggling to improve its turnaround time for HIV testing.
We examined tens of thousands of cases in Mozambique right down to the original time stamps on samples and the return dates of test results. Then we developed a tool to streamline this supply chain system. We found that some simple changes could improve the turnaround time and increase the number of infants starting treatment.
An inefficient system
One of the biggest barriers to faster test turnaround times in Mozambique has to do with the network structure of laboratories and clinics. There are about 400 clinics in the country. These are assigned to laboratories based on governmental administrative districts. But these boundaries are drawn for political reasons instead of public health reasons.
As a result one administrative district may be densely populated while another is sparsely populated. And this means that the workload at the various diagnostic laboratories differs according to the size of their surrounding populations.
Read the full post at The Conversation
Jónas Oddur Jónasson is an Assistant Professor of Operations Management at the MIT Sloan School of Management.