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The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with clinical manifestation cases that are almost similar to those of common respiratory viral infections. This study determined the prevalence of SARS-CoV-2 and other acute respiratory viruses among patients with flu-like symptoms in Bukavu city, Democratic Republic of Congo. We screened 1352 individuals with flu-like illnesses seeking treatment in 10 health facilities. Nasopharyngeal swab specimens were collected to detect SARS-CoV-2 using real-time reverse transcription-polymerase chain reaction (RT-PCR), and 10 common respiratory viruses were detected by multiplex reverse transcription-polymerase chain reaction assay. Overall, 13.9% (188/1352) of patients were confirmed positive for SARS-CoV-2. Influenza A 5.6% (56/1352) and Influenza B 0.9% (12/1352) were the most common respiratory viruses detected. Overall, more than two cases of the other acute respiratory viruses were detected. Frequently observed symptoms associated with SARS-CoV-2 positivity were shivering (47.8%; OR = 1.8; CI: 0.88–1.35), cough (89.6%; OR = 6.5, CI: 2.16–28.2), and myalgia and dizziness (59.7%; OR = 2.7; CI: 1.36–5.85). Moreover, coinfection was observed in 12 (11.5%) specimens. SARS-CoV-2 and influenza A were the most cooccurring infections, accounting for 33.3% of all positive cases. This study demonstrates cases of COVID-19 infections cooccurring with other acute respiratory infections in Bukavu city during the ongoing outbreak of COVID-19. Therefore, testing for respiratory viruses should be performed in all patients with flu-like symptoms for effective surveillance of the transmission patterns in the COVID-19 affected areas for optimal treatment and effective disease management.

Climate-smart agriculture (CSA) is one of the innovative approaches for sustainably increasing the agricultural productivity, improving livelihoods and incomes of farmers, while at the same time improving resilience and contributing to climate change mitigation. In spite of the fact that there is neither explicit policy nor practices branded as CSA in Democratic Republic of Congo (DRC), farmers are utilizing an array of farming practices whose attributes meet the CSA criteria. However, the intensity, distribution, efficiency, and dynamics of use as well as the sources of these technologies are not sufficiently documented. Therefore, this review paper provides a comprehensive evidence of CSA-associated farming practices in DRC, public and private efforts to promote CSA practices, and the associated benefits accruing from the practices as deployed by farmers in the DRC. We find evidence of progress among farming communities in the use of practices that can be classified as CSA. Communities using these practices are building on the traditional knowledge systems and adaptation of introduced technologies to suit the local conditions. Reported returns on use of these practices are promising, pointing to their potential continued use into the future. While progressive returns on investment are reported, they are relatively lower than those reported from other areas in sub-Saharan Africa deploying similar approaches. We recommend for strategic support for capacity building at various levels, including public institutions for policy development and guidance, extension and community level to support uptake of technologies and higher education institutions for mainstreaming CSA into curricula and training a generation of CSA sensitive human resources.

The coronavirus 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with clinical manifestation cases are almost similar to those of common respiratory viral infections. This study determined the prevalence of SARS-CoV-2 and other acute respiratory viruses among patients with flu-like symptoms in Bukavu city Democratic republic of Congo. We screened 1352 individuals with flu-like illnesses seeking treatment in 10 health facilities. Nasopharyngeal swabs specimens were collected to detect SARS-CoV-2 using real-time reverse transcription-polymerase chain reaction (RT-PCR) and 10 common respiratory viruses were detected by multiplex reverse transcription polymerase chain reaction assay. Overall, 13.9% (188/1352) patients were confirmed positive for SARS-CoV-2. Influenza A 5.6% (56/1352), and Influenza B 0.9% (12/1352) were the most common respiratory viruses detected. Overall more than two cases of the other acute respiratory viruses were detected. Frequently observed symptoms associated with SARS-CoV-2 positivity were shivering (47.8%; OR= 1.8; CI: 0.88-1.35), cough (89.6%; OR=6.5, CI: 2.16-28.2), myalgia and dizziness (59.7%; OR=2.7; CI: 1.36-5.85). Moreover, coinfection was observed in 12 (11.5%) specimens. SARS-CoV-2, and Influenza A were the most co-occurring infections, accounting for 33.3% of all positive cases. This study demonstrates cases of COVID-19 infections co-occurring with other acute respiratory infections in Bukavu city during the ongoing outbreak of COVID-19. These data emphasize the need for routine testing of multiple viral pathogens for better prevention and treatment plans. Keywords: SARS-CoV-2, respiratory viruses, flu-like symptoms, coinfection; Bukavu city.

In order to study the biodiversity of Cameroon indigenous Djallonke sheep, a study was conducted between July and September 2016 in the Sudano-Guinean zone of Cameroon. A total of 280 adult sheep (24 months old) including 77 males and 203 females from 112 farms in 13 districts of 4 divisions was measured and analyzed. The variance analysis showed variability in the population. According to the principal components analysis, the body length, chest circumference, withers height and the live weight were potentially discriminating characters of the ovine population studied. The discriminant analysis revealed a population made of three genetic types with genetic type I having the highest characteristics. The phylogenetic analysis showed that type II and III are closer and type I and III are genetically more distant. High intra-genetic variability was observed within the population studied. The linearregression equation (LW = 0.8092CG + 58.923) with a coefficient of determination (R2 = 0.66) predicts better the live weight. This results offer possibilities for genetic improvement. Characterization, leading to conservation and sustainable use of indigenous sheep genetic resources in Cameroon’s smallholder production system. The possible threats to the current potentials may be genetic erosion, climate change, low productivity and disease susceptibility.