Lessons Learned from Sudan Ebola Virus Disease (SUDV) Preparedness in Rwanda: A Comprehensive Review and Way Forward.

BACKGROUND: Ebola Virus Disease (EVD) is a severe and often fatal illness that affects humans and has significant public health implications, including high mortality rates, strain on healthcare systems, and social and economic disruption. On 20 September 2022, Uganda declared an Ebola disease outbreak caused by the Sudan ebolavirus species. The neighboring countries of Uganda were classified by World Health Organization (WHO) as being at high risk of Sudan Ebola Virus Disease (SUDV) importation. The country of Rwanda implemented different sustainable strategies and activities to prepare and ensure a timely and effective response to SUDV outbreaks once it has arrived in the country. We aimed to highlight the sustainable strategies and activities implemented for SUDV preparedness and the subsequent lessons learnt in Rwanda. METHODS: This paper reviewed the documentation on activities implemented for SUDV preparedness, with a focus on lessons learned from different countries. The paper analyzed the common themes and highlighted the key components of EVD preparedness in Rwanda after declaration of SUDV outbreak in Uganda. RESULTS: The key components of SUDV preparedness include its readiness assessment in Rwanda, effective coordination, collaboration and leadership mechanisms, enhancing the early detection and surveillance system, effective risk communication and community engagement, capacity building of healthcare providers on case management and infection prevention and control (IPC), and continual preparedness. These components were essential to ensure timely and effective preparation and response to SUDV related outbreaks. CONCLUSION: A multi-sectoral approach involving all stakeholders was necessary to ensure timely and effective preparation and response. Continuous investment in preparedness, strengthening of health systems, and the review of preparedness components provided insights into the best practices for SUDV preparedness, which were essential to prevent future outbreaks and minimize their impact. This will inform other countries about the role of timely development of preparedness plans.

Use of trained scent dogs for detection of COVID-19 and evidence of cost-saving.

Background: One of the lessons learned from the coronavirus disease 2019 (COVID-19) pandemic is the importance of early, flexible, and rapidly deployable disease detection methods. Currently, diagnosis of COVID-19 requires the collection of oro/nasopharyngal swabs, nasal turbinate, anterior nares and saliva but as the pandemic continues, disease detection methods that can identify infected individuals earlier and more quickly will be crucial for slowing the spread of the virus. Previous studies have indicated that dogs can be trained to identify volatile organic compounds (VOCs) produced during respiratory infections. We sought to determine whether this approach could be applied for detection of COVID-19 in Rwanda and measured its cost-saving. Methods: Over a period of 5 months, four dogs were trained to detect VOCs in sweat samples collected from human subjects confirmed positive or negative for COVID-19 by reverse transcription polymerase chain reaction (RT-PCR) testing. Dogs were trained using a detection dog training system (DDTS) and in vivo diagnosis. Samples were collected from 5,253 participants using a cotton pad swiped in the underarm to collect sweat samples. Statistical analysis was conducted using R statistical software. Findings: From August to September 2021 during the Delta wave, the sensitivity of the dogs' COVID-19 detection ranged from 75.0 to 89.9% for the lowest- and highest-performing dogs, respectively. Specificity ranged from 96.1 to 98.4%, respectively. In the second phase coinciding with the Omicron wave (January-March 2022), the sensitivity decreased substantially from 36.6 to 41.5%, while specificity remained above 95% for all four dogs. The sensitivity and specificity by any positive sample detected by at least one dog was 83.9, 95% CI: 75.8-90.2 and 94.9%; 95% CI: 93.9-95.8, respectively. The use of scent detection dogs was also found to be cost-saving compared to antigen rapid diagnostic tests, based on a marginal cost of approximately $14,000 USD for testing of the 5,253 samples which makes 2.67 USD per sample. Testing turnaround time was also faster with the scent detection dogs, at 3 h compared to 11 h with routine diagnostic testing. Conclusion: The findings from this study indicate that trained dogs can accurately identify respiratory secretion samples from asymptomatic and symptomatic COVID-19 patients timely and cost-effectively. Our findings recommend further uptake of this approach for COVID-19 detection.

An environmental scan of one health preparedness and response: the case of the Covid-19 pandemic in Rwanda.

BACKGROUND: Over the past decade, 70% of new and re-emerging infectious disease outbreaks in East Africa have originated from the Congo Basin where Rwanda is located. To respond to these increasing risks of disastrous outbreaks, the government began integrating One Health (OH) into its infectious disease response systems in 2011 to strengthen its preparedness and contain outbreaks. The strong performance of Rwanda in responding to the on-going COVID-19 pandemic makes it an excellent example to understand how the structure and principles of OH were applied during this unprecedented situation. METHODS: A rapid environmental scan of published and grey literature was conducted between August and December 2020, to assess Rwanda's OH structure and its response to the COVID-19 pandemic. In total, 132 documents including official government documents, published research, newspaper articles, and policies were analysed using thematic analysis. RESULTS: Rwanda's OH structure consists of multidisciplinary teams from sectors responsible for human, animal, and environmental health. The country has developed OH strategic plans and policies outlining its response to zoonotic infections, integrated OH into university curricula to develop a OH workforce, developed multidisciplinary rapid response teams, and created decentralized laboratories in the animal and human health sectors to strengthen surveillance. To address COVID-19, the country created a preparedness and response plan before its onset, and a multisectoral joint task force was set up to coordinate the response to the pandemic. By leveraging its OH structure, Rwanda was able to rapidly implement a OH-informed response to COVID-19. CONCLUSION: Rwanda's integration of OH into its response systems to infectious diseases and to COVID-19 demonstrates the importance of applying OH principles into the governance of infectious diseases at all levels. Rwanda exemplifies how preparedness and response to outbreaks and pandemics can be strengthened through multisectoral collaboration mechanisms. We do expect limitations in our findings due to the rapid nature of our environmental scan meant to inform the COVID-19 policy response and would encourage a full situational analysis of OH in Rwanda's Coronavirus response.