Assessment of the socioeconomic impact of COVID-19 in Rwanda: Findings from a country-wide community survey (preprint)

The COVID-19 pandemic disrupted socioeconomic situation worldwide, and particularly in Rwanda which was rebuilding its economy in the aftermath of the 1994 Genocide against the Tutsi. Recent studies documented the macro-level socio-economic pandemic impact but the impact on a household’s daily life has been scarcely documented especially in low-and-middle income countries. This work reports a country-wide longitudinal community survey and describes the interplay between multiple factors to assess the socio-economic impact of COVID-19 on the Rwandan population at micro-level (household). The survey was conducted in Rwanda between December 2021 and March 2022 and data used comprised a total of 26,412 response forms received from around 4400 participants surveyed in 6 recurrent bi-weekly phases. This study revealed that the income of 57.7% of respondents has decreased and 15.5% of respondents received support to overcome the consequences. The univariate analysis results indicate that the decrease in income is more seen for females than males. The other most affected group is of daily laborer or small business (77.1%), people living in urban area (63.7%), retired people (66.4%), and people with primary school education level (62.0%). The multivariable findings highlighted that vulnerable groups: income-poor households with low socio-economic categories and females living in rural regions are among the most impacted in terms of food security, electricity, water and transport. The findings from this research will be used by policy makers to design and implement preventive and responsive measures for future pandemics that should be multifactorial and tailored to transversal parameters like gender and residence.

Leveraging Artificial Intelligence and Data Science Techniques in Harmonizing, Sharing, Accessing and Analyzing SARS-COV-2/COVID-19 Data in Rwanda (LAISDAR Project): Study design and rationale (preprint)

Background: Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be used to improve understanding of the disease, monitor its progress, and generate evidence to guide prevention measures. The objective of this project is to leverage the artificial intelligence (AI) and data science techniques in harmonizing datasets to support Rwandan government needs in monitoring and predicting the COVID-19 burden, including the hospital admissions and overall infection rates.Methods: The project will gather the existing data including hospital electronic health records (EHRs), the COVID-19 testing data and will link with longitudinal data from community surveys. The open-source tools from Observational Health Data Sciences and Informatics (OHDSI) will be used to harmonize hospital EHRs through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The project will also leverage other OHDSI tools for data analytics and network integration, as well as R Studio and Python. The network will include up to 15 health facilities in Rwanda, whose EHR data will be harmonized to OMOP CDM.Expected results: This study will yield a technical infrastructure where the 15 participating hospitals and health centres will have EHR data in OMOP CDM format on a local Mac Mini (“data node”), together with a set of OHDSI open-source tools. A central server, or portal, will contain a data catalogue of participating sites, as well as the OHDSI tools that are used to define and manage distributed studies. The central server will also integrate the information from the national Covid-19 registry, as well as the results of the community surveys. The ultimate project outcome is the dynamic prediction modelling for COVID-19 pandemic in Rwanda.Discussion: The project is the first on the African continent leveraging AI and implementation of an OMOP CDM based federated data network for data harmonization. Such infrastructure is scalable for other pandemics monitoring, outcomes predictions, and tailored response planning.

SARS-CoV-2-positive patients display considerable differences in proteome diversity in urine, nasopharyngeal, gargle solution and bronchoalveolar lavage fluid samples (preprint)

Background: Proteome profile changes post-severe acute respiratory syndrome coronavirus 2 (post-SARS-CoV-2) infection in different body sites of humans remains an active scientific investigation whose solutions stand a chance of providing more information on what constitutes SARS-CoV-2 pathogenesis. While proteomics has been used to understand SARS-CoV-2 pathogenesis, there are limited data about the status of proteome profile in different human body sites infected by sarscov2 virus. To bridge this gap, our study aims to profile the proteins secreted in urine, bronchoalveolar lavage fluid (BALF), gargle solution, and nasopharyngeal samples and assess the proteome differences in these body samples collected from SARS-CoV-2-positive patients. Materials and methods: We downloaded publicly available proteomic data from (https://www.ebi.ac.uk/pride/). The data we downloaded had the following identifiers: i) PXD019423, n=3 from Charles Tanford Protein Center in Germany. ii) PXD018970, n=15 from Beijing Proteome Research Centre, China. iii)PXD022085, n=5 from Huazhong University of Science and Technology, China, and iv) PXD022889, n=18 from Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA. MaxQuant was used for the peptide spectral matching using human and SARS-CoV-2 downloaded from UniProt database (access date 13th October 2021). Results: The individuals infected with SARS-CoV-2 viruses displayed a different proteome diversity from the different body sites we investigated. Overally, we identified 1809 proteins across the four different sample types we compared. Urine and BALF samples had significantly more abundant SARS-CoV-2 proteins than the other body sites we compared. Urine samples had 257(33.7%) unique proteins followed by nasopharyngeal with 250(32.8%) unique proteins. Garlge solution and BALF had 38(5%) and 73(9.6%) unique proteins respectively. Conclusions: Urine, gargle solution, nasopharyngeal, and bronchoalveolar lavage fluid samples have different protein diversity in individuals infected with SARS-CoV-2. Moreover, our data also demonstrated that a given body site is characterized by a unique set of proteins in SARS-CoV-2 seropositive individuals. Key words: SARS-CoV-2, body sites,urine,gargle solution, BALF,nasopharyngeal

The Impact of Covid-19 on Malaria Services in Three High Endemic Districts in Rwanda – A Mixed-Method Study (preprint)

Background: Rwanda has achieved impressive reductions in malaria morbidity and mortality over the past two decades. However, the disruption of essential services due to the current Covid-19 pandemic can lead to a reversal of these gains in malaria control unless targeted, evidence-based interventions are implemented to mitigate the impact of the pandemic. The extent to which malaria services have been disrupted has not been fully characterized. In this study, we thus assessed the impact of Covid-19 on malaria services in Rwanda. Methods: We conducted a mixed-methods study in three purposively selected districts in Rwanda. The quantitative data included malaria aggregated data reported at the health facility level and the community level. The data included the number of malaria tests, uncomplicated malaria cases, severe malaria cases, and malaria deaths. We collected qualitative data using focus group discussions with community members and community health workers, as well as in-depth interviews with health care providers and staff working in the malaria program. We conducted interrupted time series analysis to compare changes in malaria presentations between the pre-Covid-19 period (January 2019 to February 2020) and Covid-19 periods (from March 2020 to November 2020). We used the constant comparative method in qualitative thematic analysis. Results: Compared to pre-Covid-19 period, there was a monthly reduction in patients tested in health facilities of 5.09 per 1000 population and a monthly increase in patients tested in the community of 3.13 per 1000 population during the Covid-19 period. There was no change in presentation rate for uncomplicated malaria or severe malaria. Additionally, although healthcare providers continued to provide malaria services, they were fearful that this would expose them and their families to Covid-19. Covid-19 mitigation measures limited the availability of transportation options for the community to seek care in health facilities and delayed the implementation of some key malaria interventions. The focus on Covid-19-related communication also reduced the amount of health information for other diseases provided to community members. Conclusion The Covid-19 pandemic resulted in patients increasingly seeking care in the community and poses challenges to maintaining delivery of malaria services in Rwanda. Interventions to mitigate these challenges should focus on strengthening programming for community and home-based care models and integrating malaria messages into Covid-19-related communication. Additionally, implementation of the interrupted interventions should be timed and overlap with the malaria transmission season to mitigate Covid-19 consequences on malaria.

Mutation Landscape of SARS COV2 in Africa (preprint)

COVID-19 disease has had a relatively less severe impact in Africa. To understand the role of SARS CoV2 mutations on COVID-19 disease in Africa, we analysed 282 complete nucleotide sequences from African isolates deposited in the NCBI Virus Database. Sequences were aligned against the prototype Wuhan sequence (GenBank accession: NC_045512.2) in BWA v. 0.7.17. SAM and BAM files were created, sorted and indexed in SAMtools v. 1.10 and marked for duplicates using Picard v. 2.23.4. Variants were called with mpileup in BCFtools v. 1.11. Phylograms were created using Mr. Bayes v 3.2.6. A total of 2,349 single nucleotide polymorphism (SNP) profiles across 294 sites were identified. Clades associated with severe disease in the United States, France, Italy, and Brazil had low frequencies in Africa (L84S=2.5%, L3606F=1.4%, L3606F/V378I/=0.35, G251V=2%). Sub Saharan Africa (SSA) accounted for only 3% of P323L and 4% of Q57H mutations in Africa. Comparatively low infections in SSA were attributed to the low frequency of the D614G clade in earlier samples (25% vs 67% global). Higher disease burden occurred in countries with higher D614G frequencies (Egypt=98%, Morocco=90%, Tunisia=52%, South Africa) with D614G as the first confirmed case. V367F, D364Y, V483A and G476S mutations associated with efficient ACE2 receptor binding and severe disease were not observed in Africa. 95% of all RdRp mutations were deaminations leading to CpG depletion and possible attenuation of virulence. More genomic and experimental studies are needed to increase our understanding of the temporal evolution of the virus in Africa, clarify our findings, and reveal hot spots that may undermine successful therapeutic and vaccine interventions.

RPA-Based Method For The Detection Of SARS-CoV2 (preprint)

Background: Coronavirus disease 2019 (COVID-19) is a highly infectious disease with significant mortality, morbidity, and far-reaching economic and social disruptions. Testing is key in the fight against COVID-19 disease. The gold standard for COVID-19 testing is the reverse transcription polymerase chain reaction (RT-PCR) test. RT-PCR requires highly specialized, expensive, and advanced bulky equipment that is difficult to use in the field or in a point of care setting. There is need for a simpler, inexpensive, convenient, portable and accurate test. Our aims were to: (i) design primer-probe pairs for use in isothermal amplification of the S1, ORF3 and ORF8 regions of the SARS-CoV2 virus; (ii) optimize the recombinase polymerase amplification (RPA) assay for the isothermal amplification of the named SARS-COV2 regions; (iii) detect amplification products on a lateral flow device. and (ii) perform a pilot field validation of RPA on RNA extracted from nasopharyngeal swabs. Results: Assay validation was done at the National Reference Lab (NRL) at the Rwanda Biomedical Center (RBC) in Rwanda. Results were compared to an established, WHO-approved rRT-PCR laboratory protocol. The assay provides a faster and cheaper alternative to rRT-PCR with 100% sensitivity, 93% specificity, and positive and negative predictive agreements of 100% and 93% respectively. Conclusion: To the best of our knowledge, this is the first in-field and comparative laboratory validation of RPA for COVID-19 disease in low resource settings. Further standardization will be required for deployment of the RPA assay in field settings. Keywords: Recombinase Polymerase Amplification, COVID-19

A strategy for finding people infected with SARS-CoV-2: optimizing pooled testing at low prevalence (preprint)

Suppressing SARS-CoV-2 will likely require the rapid identification and isolation of infected individuals, on an ongoing basis. RT-PCR (reverse transcription polymerase chain reaction) tests are accurate but costly, making regular testing of every individual expensive. The costs are a challenge for all countries and particularly for developing countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups. We propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, uniquely identifies infected individuals in a small number of tests. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof of concept experiments in which a positive subsample was detected even when diluted a hundred-fold with negative subsamples. Using these methods, the costs of mass testing could be reduced by a large factor. If infected individuals are quickly and effectively quarantined, the prevalence will fall and so will the cost of regular, mass testing. Such a strategy provides a possible pathway to the longterm elimination of SARS-CoV-2. Field trials of our approach are now under way in Rwanda.