Mosquito bed net use and associated factors among pregnant women in Rwanda: A nationwide survey

Background In malaria-endemic countries such as Rwanda, the appropriate use of mosquito bed nets is an effective intervention for malaria prevention. Despite being one of the demographics most impacted by malaria, there is a dearth of literature on the usage of mosquito bed nets by pregnant women in Rwanda. The study aimed to assess the prevalence and associated factors for mosquito bed net use among pregnant women in Rwanda Methods We used weighted data from the 2020 Rwanda Demographic and Health Survey of 870 pregnant women, and multistage stratified sampling was used to select participants. Multivariable logistic regression was conducted to determine the factors associated with mosquito bed net use, using SPSS (version 26). Results Of the 870 pregnant women, 57.9% (95%CI: 54.6–61.1) used mosquito bed nets. However, 16.7% did not use bed nets among those owning bed nets. On one hand, older age (AOR = 1.59, 95%CI: 1.04–2.44), primary education (AOR = 1.18, 95%CI: 1.07–2.23), being married (AOR = 2.17, 95%CI: 1.43–3.20), being from Kigali region (AOR = 1.97, 95%CI: 1.19–3.91), partner’s education (AOR = 1.22, 95%CI: 1.13–3.41), having recently visited a health facility (AOR = 2.07, 95%CI: 1.35–3.18), and being in the third pregnancy trimester (AOR = 2.14, 95%CI: 1.44–3.18) were positively associated with mosquito bed net use. On the other hand, low wealth index (AOR = 0.13, 95%CI: 0.07–0.24), and being from Eastern region (AOR = 0.42, 95% CI: 0.26–0.66) had a negative association. Conclusions About half of the pregnant women in Rwanda used mosquito bed nets and the usage was associated with various socio-demographics. There is a need for appropriate risk communication and continuous sensitisation to improve mosquito net use among pregnant women. Early antenatal care attendance and partner engagement in malaria prevention and mosquito net use, as well as consideration of household dynamics, are also crucial in improving not only mosquito net coverage but also utilization

Comparing the efficiency of base and multiplicative selection indices for yield and quality traits in Cassava: Article Retracted by the Authors

The efficiency of two selection indices; base index and the multiplicative index was compared to determine the effectiveness of each in identifying superior genotypes in cassava (Manihot esculent Crantz) population. Genotypic data on various yield and quality traits among 570 cassava genotypes were used to construct these selection indices. The efficiency of these indices was compared by determining the performance means of each genotype for studied traits and computing selection differentials of each index. Best linear unbiased predictions (BLUPs) for dry matter content and harvest index were also used for comparison of the two selection indices.  The base index produced high-performance means of all five studied traits and proved to be more efficient compared to the multiplicative index in the improvement of cassava genotypes. In addition, the base index produced high selection differentials for three out of five studied traits. It was concluded that the base index is useful in cassava germplasm selectio

Field evaluation of selected cassava genotypes for cassava brown streak disease based on symptom expression and virus load

Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread

Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages

Open Access Article; Published online: 11 Dec 2019Assembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs. In this study, we examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This is the first genomic selection and genome‐wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. The use of clones in the same stage to construct TPs provided higher trait prediction accuracy than TPs with a mixture of clones from multiple breeding stages. Moreover, clones in the early breeding stage provided more reliable trait prediction accuracy and are better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, in this study, adding clones from Kibaha to those from Ukiriguru and vice versa did not improve the prediction accuracy of either population. Including the Ugandan TP in either population did not improve trait prediction accuracy. This study applied genomic prediction to understand the implications of constructing TP from clones at different breeding stages pooled from different locations on trait accuracy

Identification of F1 cassava (Manihot esculenta Crantz) progeny using microsatellite markers and capillary electrophoresis

Generation of genetic diversity is necessary in improving on the potential of cassava when faced with various biotic and abiotic challenges. Presently, cassava breeders are breeding for a number of traits, such as drought tolerance, early root bulking, yield, starch, beta-carotene, protein, dry matter, pest and disease resistance, by relying on genetic diversity that exists in manihot esculenta germplasm. Controlled pollination is one of the main methods used to generate genetic diversity in cassava. However, the process of controlled pollination especially in an open field is prone to contamination by illegitimate pollen right from the time of pollination, seed collection, nursery bed establishment to planting of the trials. Therefore, authentication of the progeny obtained from cas-sava crosses is very important for genetic studies. Twelve informative microsatellite markers were used to verify the authenticity of 364 F1 progeny thought to come from four controlled parental crosses. The transmission of each allele at nine microsatellite loci was tracked from parents to progeny in each of the four Namikonga-derived F1 cassava families. Out of the 364 F1 progeny, 317 (87.1%) were true-to-type, 44 (12.1%) were a product of self-pollination and 3 (0.8%) were a product of open pollination. The consistency of the results obtained using microsatellite markers makes this technique a reliable tool for assessing the purity of progeny generated from cassava crosses

Sexual violence and associated factors among women of reproductive age in Rwanda: A 2020 nationwide cross-sectional survey

Background; Sexual violence against women is a global public health issue with both short- and long-term effects on the physical and mental health of women. This study aimed to determine the prevalence of sexual violence and its associated factors among women of reproductive age in Rwanda. Methods: We used secondary data from the 2020 Rwanda Demographic and Health Survey of 1,700 participants, who were selected using multistage stratified sampling. Multivariable logistic regression was conducted to explore factors associated with sexual violence using SPSS (version 25). Results: Of the 1,700 women of reproductive age, 12.4% (95%CI: 11.0–14.1) had experienced sexual violence. Justified beating (AOR = 1.34, 95%CI: 1.16–1.65), not having health insurance (AOR = 1.46, 95%CI: 1.26–2.40), not being involved in healthcare decision-making (AOR = 1.64, 95%CI: 1.99–2.70), having a husband/partner with primary (AOR = 1.70, 95%CI: 5.47–6.21) or no education (AOR = 1.84, 95%CI: 1.21–3.37), as well as having a husband/partner who sometimes (AOR = 3.37, 95%CI: 1.56–7.30) or often (AOR = 12.87, 95%CI: 5.64–29.38) gets drunk were positively associated with sexual violence. However, women from male-headed households (AOR = 0.52, 95%CI: 0.29–0.92) were less likely to experience sexual violence. Conclusions: There is a need to demystify negative culturally-rooted beliefs favouring sexual violence, such as justified beating, as well as increase efforts to promote women’s empowerment and healthcare access. Moreover, engaging men in anti-sexual violence strategies is paramount to addressing male-related issues that expose women to sexual violence

solGS: a webbased tool for genomic selection

Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program