Authors : Emil Ivan; Patrick Gad Iradukunda; Pierre Gashema; Ingabire Angelique; Alice Kabanda; Enatha Mukantwari; Anicet Rucogoza; Jules Christian Ishimwe; Kamwesiga Julius; Emile Musoni; Eliah Shema; Tafadzwa Dzinamarira; Eugene Mutimura
Volume/Issue : Volume 6 - 2021, Issue 2 - February
Google Scholar : http://bitly.ws/9nMw
Scribd : https://bit.ly/2OQKdGP
The coronavirus disease 2019 (COVID-19) has
challenged health systems globally. In low and middleincome countries, a unique challenge ensuring the
widespread testing that is critical to the response toward
the pandemic has persisted. The pandemic has
accentuated the need for rapid scale-up of real-time
polymerase chain reaction (RT-PCR), a molecular testing
technique that was often used for research purposes only,
especially in limited-resource settings. Rwanda is a lowincome country that has managed to scale up RT-PCR
laboratory testing capacity by 15-fold within the first
four-month of the COVID-19 pandemic.
Rwanda has been in line with the measures to
contain COVID-19 even before 14th March 2020, when
the first case of COVID-19 was detected. Due to the
transmission of the infection, the scale-up was
immediately in place, relying on public, private, nongovernmental, and voluntary students from universities
to boost the surveillance of the pandemic in the
population. In COVID-19 testing, this scale-up relied on
population and government goodwill; research-based
actions that included adopting a pooling strategy;
optimized use of available human resources; and the use
of limited resource funding models to support the
established health system governance structure. Initially,
the national reference laboratory was the only testing site
for COVID-19; however, later, the country implemented
decentralized testing, setting up COVID-19 testing
centers countrywide. In this article, we highlight the
lessons learned from the Rwandan COVID-19 laboratory
testing response to guide effective laboratory response in
limited-resource settings.
We recommend an appropriate epidemic response
algorithm to be developed to classify cases based on
epidemiological, clinical, and laboratory information in
line with diagnosis methods and sustain quality.
Keywords : NCOVID-19, SARSCOVI-2, SCALING UP, RTPCR, RWANDA