ABSTRACT
Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries, which experience the highest burden of AMR. Critical to combatting AMR is ensuring there are effective, accessible diagnostic networks in place to diagnose, monitor and prevent AMR, but many low- and middle-income countries lack such networks. Consequently, there is substantial need for approaches that can inform the design of efficient AMR laboratory networks and sample referral systems in lower-resource countries. Diagnostic network optimization (DNO) is a geospatial network analytics approach to plan diagnostic networks and ensure greatest access to and coverage of services, while maximizing the overall efficiency of the system. In this intervention, DNO was applied to strengthen bacteriology and AMR surveillance network design in Kenya and Nepal for human and animal health, by informing linkages between health facilities and bacteriology testing services and sample referral routes between farms, health facilities and laboratories. Data collected from the target settings in each country were entered into the open-access DNO tool OptiDx, to generate baseline scenarios, which depicted the current state of AMR laboratory networks and sample referral systems in the countries. Subsequently, baselines were adjusted to evaluate changing factors such as samples flows, transport frequency, transport costs, and service distances. Country stakeholders then compared resulting future scenarios to identify the most feasible solution for their context. The DNO analyses enabled a wealth of insights that will facilitate strengthening of AMR laboratory and surveillance networks in both countries. Overall, the project highlights the benefits of using a data-driven approach for designing efficient diagnostic networks, to ensure better health resource allocation while maximizing the impact and equity of health interventions. Given the critical need to strengthen AMR laboratory and surveillance capacity, DNO should be considered an integral part of diagnostic strategic planning in the future.
ABSTRACT
Background: Antimicrobial resistance (AMR) is an increasingly severe threat to global public health that requires action across different sectors. Selection of appropriate antimicrobials is an urgent challenge due to the emergence of drug resistance. In 2017, Kenya developed an AMR policy and National Action Plan to drive prevention and containment of AMR. A priority activity under AMR surveillance strategic objective was to develop a national AMR training curriculum for in-service healthcare workers. In this paper we discuss the development process, gains achieved through implementation across the country and lessons learned. Methods: An initial stakeholders' forum was convened to brainstorm on the process for developing the curriculum and some issues deliberated upon include the design approach, development roadmap, curriculum outline and scope, delivery, and evaluation methodologies. A dedicated team of subject matter experts (SMEs), drawn from the project and government ministries, compiled the initial draft of the curriculum and later the training materials. A series of other stakeholders' meetings were convened to review these materials. The National Antimicrobial Stewardship Interagency Committee (NASIC) of the MOH in Kenya identified a team of experts from academia, research, and government to work with the SMEs in reviewing and providing valuable inputs to the curriculum. Additionally, principles of adult learning and a One Health approach for development were considered as AMR has drivers and impacts across sectors. A validation workshop was held to finalize the documents with a formal launch conducted during the World Antibiotics Awareness Week of 2020. Results: A multisectoral AMR surveillance training curriculum and facilitator and trainee manuals were developed and endorsed by MOH and Ministry of Agriculture, Livestock, Fisheries and Cooperatives within one year. Over 500 healthcare workers in 19 counties were trained, with overwhelming adoption by other stakeholders in Kenya and beyond. Conclusion: This curriculum was developed to standardize training for AMR detection and surveillance. The central role played by the MOH ensured expeditious development and roll-out of this curriculum. The in-service curriculum, now available on an e-learning platform, provides a ready opportunity to build capacity of healthcare professionals. Additional resources are needed to standardize and scale these efforts to reach all healthcare workers.
ABSTRACT
BACKGROUND: Drug susceptibility testing for Mycobacterium tuberculosis (MTB) is difficult to perform in resource-limited settings where Acid Fast Bacilli (AFB) smears are commonly used for disease diagnosis and monitoring. We developed a simple method for extraction of MTB DNA from AFB smears for sequencing-based detection of mutations associated with resistance to all first and several second-line anti-tuberculosis drugs. METHODS: We isolated MTB DNA by boiling smear content in a Chelex solution, followed by column purification. We sequenced PCR-amplified segments of the rpoB, katG, embB, gyrA, gyrB, rpsL, and rrs genes, the inhA, eis, and pncA promoters and the entire pncA gene. RESULTS: We tested our assay on 1,208 clinically obtained AFB smears from Ghana (n = 379), Kenya (n = 517), Uganda (n = 262), and Zambia (n = 50). Coverage depth varied by target and slide smear grade, ranging from 300X to 12000X on average. Coverage of ≥20X was obtained for all targets in 870 (72%) slides overall. Mono-resistance (5.9%), multi-drug resistance (1.8%), and poly-resistance (2.4%) mutation profiles were detected in 10% of slides overall, and in over 32% of retreatment and follow-up cases. CONCLUSION: This rapid AFB smear DNA-based method for determining drug resistance may be useful for the diagnosis and surveillance of drug-resistant tuberculosis.
