Assessment of Striga hermonthica infestation and effectiveness of current management strategies in maize-based cropping systems in eastern Uganda

Striga is a major constraint to cereal production in the tropics, particularly on soils of low fertility. Striga causes 30 to 80% cereal crop losses in sub-Saharan Africa. The objective of this study was to assess farmers’ perception of level of infestation and efficacy of current management options of Striga (Striga hermonthica (Delile) Benth) in maize-based cropping systems in eastern Uganda. A survey was conducted in Iganga district in eastern Uganda, involving 360 households. On the basis of the survey outputs, on-farm trials were conducted to assess the efficacy of a herbicide seed-coating technology, imazapyr herbicide resistant maize (IR-maize) variety, either as a sole crop or intercropped with soybean (Glycine max) or common beans (Phaseolus vulgaris L). The study revealed that S. hermonthica caused more than 50% maize (Zea mays) yield loss and farmers were dissatisfied with the existing control practices. Farmers’ knowledge about Striga was mainly sourced from agricultural extension service providers. The on-farm trials revealed that IR-maize provided effective protection against S. hermonthica infestation. Also, intercropping Longe 6H maize variety with either soybean or common beans significantly reduced Striga infestation in farmers’ fields. Longe 6H-soybean intercropping reduced Striga infestation by 32%; while Longe 6H-common bean intercropping reduced Striga infestation by 14%. Intercropping either IR-maize or Longe 6H hybrid (farmer-preferred) with the aforementioned legumes, reduced S. hermonthica infestation (30–50%) and improved maize yield parameters (20-30%). For effective management of S. hermonthica in the maize-based cropping systems in eastern Uganda, farmers should be encouraged to adopt the improved IR-maize and intercrop farmer-preferred maize varieties with legumes in order to improve maize yields

Corrigendum to “Counting adolescents in: the development of an adolescent health indicator framework for population-based settings”

The authors were recently made aware of an oversight such that parts of the text in the Introduction and Methods sections, which describe shortcomings in the existing literature and the methods in this work to identify frameworks and indicators, were missing attribution to published work cited elsewhere in the manuscript. To clarify, we adjust the relevant sections to fully attribute the prior work in three areas, as described below. Underlined text is additional to the original: While both school- and community-based modalities can provide nationally representative data among eligible adolescents, several shortcomings in adolescent health measurement in LMICs were noted by the GAMA Advisory Group (Reference 13 as in the original paper). First, these measurements do not equally cover all adolescent subgroups, with evidence gaps being largest for males, younger adolescents aged 10–14 years, adolescents of diverse genders, ethnicities, and religions, as well as those out of school and migrants. Second, age-disaggregated data are often lacking—due in part to incomplete age coverage—limiting their use for program planning. Third, several aspects of adolescent health are inadequately covered including mental health, substance use, injury, sexual and reproductive health among unmarried adolescents, and positive aspects of adolescent health and well-being. Fourth, the definitions and assessment methods used across adolescent health indicator frameworks are inconsistent. For example, adolescent overweight and obesity—a major cause of non-communicable diseases and a public health risk for future and intergeneration health—is inconsistently captured across indicator frameworks and strikingly absent from the SDGs (Reference 13 as in the original paper). Additional shortcomings include, current adolescent health data systems often lack intersectoral coordination beyond health (e.g., with education, water and sanitation, and social protection systems) and suffer from irregularities in coverage and timing (Reference 6 as in the original paper). Broadly, these indicator frameworks and strategy documents captured disease burden, health risks, and prominent social determinants of health during adolescence. To be congruent with the existing global recommendations and guidelines (References 3–7 as in the original paper) and global measurement efforts (References 10 and 16 as in the original paper), the indicator framework documents had to meet three inclusion criteria, as laid out by the GAMA Advisory Group (Reference 14 as in the original paper): (1) provide recommendations about the measurement of adolescents' health and well-being; (2) include indicators for “adolescents” covering the adolescent age range (10–19 years) in the whole or part; and (3) be global or regional in scope. Using the GAMA's approach (Reference 13 as in the original paper), the recommendations of Lancet Adolescent Health Commission (Reference 6 as in the original paper), and several other guidelines (References 7, 9, 12, 17–19 as in the original paper), we selected adolescent health and well-being domains based on four key aspects of adolescents in LMICs: a) population trends; b) disease burden; c) drivers of health inequality; and d) opportunity for interventions

Counting adolescents in: the development of an adolescent health indicator framework for population-based settings

Changing realities in low- and middle-income countries (LMICs) in terms of inequalities, urbanization, globalization, migration, and economic adversity shape adolescent development and health, as well as successful transitions between adolescence and young adulthood. It is estimated that 90% of adolescents live in LMICs in 2019, but inadequate data exist to inform evidence-based and concerted policies and programs tailored to address the distinctive developmental and health needs of adolescents. Population-based data surveillance such as Health and Demographic Surveillance Systems (HDSS) and school-based surveys provide access to a well-defined population and provide cost-effective opportunities to fill in data gaps about adolescent health and well-being by collecting population-representative longitudinal data. The Africa Research Implementation Science and Education (ARISE) Network, therefore, systematically developed adolescent health and well-being indicators and a questionnaire for measuring these indicators that can be used in population-based LMIC settings. We conducted a multistage collaborative and iterative process led by network members alongside consultation with health-domain and adolescent health experts globally. Seven key domains emerged from this process: socio-demographics, health awareness and behaviors; nutrition; mental health; sexual and reproductive health; substance use; and healthcare utilization. For each domain, we generated a clear definition; rationale for inclusion; sub-domain descriptions, and a set of questions for measurement. The ARISE Network will implement the questionnaire longitudinally (i.e., at two time-points one year apart) at ten sites in seven countries in sub-Saharan Africa and two countries in Asia. Integrating the questionnaire within established population-based data collection platforms such as HDSS and school settings can provide measured experiences of young people to inform policy and program planning and evaluation in LMICs and improve adolescent health and well-being

The Prevalence of Sexually Transmitted Infections in Papua New Guinea: A Systematic Review and Meta-Analysis

Patellofemoral osteoarthritis (PF OA) is more prevalent than previously thought and contributes to patient's suffering from knee OA. Synthesis of prevalence data can provide estimates of the burden of PF OA

Comparison of transcriptome-derived simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for genetic fingerprinting, diversity evaluation, and establishment of relationships in eggplants

[EN] Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers are amongst the most common markers of choice for studies of diversity and relationships in horticultural species. We have used 11 SSR and 35 SNP markers derived from transcriptome sequencing projects to fingerprint 48 accessions of a collection of brinjal (Solanum melongena), gboma (S. macrocarpon) and scarlet (S. aethiopicum) eggplant complexes, which also include their respective wild relatives S. incanum, S. dasyphyllum and S. anguivi. All SSR and SNP markers were polymorphic and 34 and 36 different genetic fingerprints were obtained with SSRs and SNPs, respectively. When combining both markers all accessions but two had different genetic profiles. Although on average SSRs were more informative than SNPs, with a higher number of alleles, genotypes and polymorphic information content (PIC), and expected heterozygosity (He) values, SNPs have proved highly informative in our materials. Low observed heterozygosity (Ho) and high fixation index (f) values confirm the high degree of homozygosity of eggplants. Genetic identities within groups of each complex were higher than with groups of other complexes, although differences in the ranks of genetic identity values among groups were observed between SSR and SNP markers. For low and intermediate values of pair-wise SNP genetic distances, a moderate correlation between SSR and SNP genetic distances was observed (r(2) = 0.592), but for high SNP genetic distances the correlation was low (r(2) = 0.080). The differences among markers resulted in different phenogram topologies, with a different eggplant complex being basal (gboma eggplant for SSRs and brinjal eggplant for SNPs) to the two others. Overall the results reveal that both types of markers are complementary for eggplant fingerprinting and that interpretation of relationships among groups may be greatly affected by the type of marker used.This work has been funded by European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 677379 (G2P-SOL project: Linking genetic resources, genomes and phenotypes of Solanaceous crops) and by Spanish Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional (Grant AGL2015-64755-R from MINECO/FEDER). Pietro Gramazio is grateful to Universitat Politecnica de Valencia for a pre-doctoral contract (Programa FPI de la UPV-Subprograma 1/2013 call). Mariola Plazas is grateful to Spanish Ministerio de Economia, Industria y Competitividad for a post-doctoral grant within the Juan de la Cierva-Formacion programme (FJCI-2015-24835).Gramazio, P.; Prohens Tomás, J.; Borras, D.; Plazas Ávila, MDLO.; Herraiz García, FJ.; Vilanova Navarro, S. 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District-Level Spatial Analysis of Migration Flows in Ghana: Determinants and Implications for Policy

The present study investigates the determinants of inter-district migration flows over the 1995-2000 period in Ghana. A combination of socio-economic, natural and spatial ‘district-level’ attributes are considered as potential variables explaining the direction of migration flows. In addition to the ‘net’ migration model, ‘in’ and ‘out’ migration models are also employed within the context of the gravity model. Results in the three models consistently show that people move out of districts with less employment and choose districts with high employment rate as destinations. While shorter distance to roads encourages out-migration, districts with better water access seem to attract migrants. Generally, people move out of predominantly agrarian districts to relatively more urbanized districts

Integrating HIV, Diabetes, and Hypertension services in Africa: study protocol for a cluster randomized trial in Tanzania and Uganda.

Introduction: HIV programmes in sub-Saharan Africa are well-funded but programmes for diabetes and hypertension are weak with only a small proportion of patients in regular care. Health care provision is organised from stand-alone clinics. In this cluster-randomised trial, we are evaluating a concept of integrated care for people with HIV-infection, diabetes or hypertension from a single point of care. Methods and Analysis: 32 primary care health facilities in Dar es Salaam and Kampala regions were randomised to either integrated or standard vertical care. In the integrated care arm, services are organised from a single clinic where patients with either HIV-infection, diabetes, or hypertension are managed by the same clinical and counselling teams. They use the same pharmacy and laboratory and have the same style of patient records. Standard care involves separate pathways, i.e. separate clinics, waiting and counselling areas, a separate pharmacy and separate medical records. The trial has 2 primary endpoints: retention in care of people with hypertension or diabetes and plasma viral load suppression. Recruitment is expected to take 6 months and follow-up is for 12 months. With 100 participants enrolled in each facility with diabetes or hypertension, the trial will provide 90% power to detect an absolute difference in retention of 15% between the study arms (at the 5% two-sided significance level). If 100 participants with HIV-infection are also enrolled in each facility, we will have 90% power to show non-inferiority in virological suppression to a delta=10% margin (i.e. that the upper limit of the one-sided 95% confidence interval of the difference between the two arms will not exceed 10%). To allow for loss to follow-up, the trial will enrol over 220 persons per facility. This is the only trial of its kind evaluating the concept of a single integrated clinic for chronic conditions in Africa Ethics and Dissemination: The protocol has been approved by ethics committee of The AIDS Support Organisation, National Institute of Medical Research and the Liverpool School of Tropical Medicine. Dissemination of findings will be done through journal publications and meetings involving study participants, health care providers and other stakeholders. Trial registration: ISRCTN43896688 Strengths of this trial • This is the largest trial of its kind with replication in over 30 health facilities and 2 countries. • It was designed, implemented and is being monitored in partnership with patient representatives, health care providers, policy makers and other stakeholders. • The trial is measuring objective markers of effectiveness and is multidisciplinary. Limitations of this trial • The trial has a relatively short follow-up of 12 months and cannot estimate effect against mortality or other longer-term outcomes. • The trial cannot be blinded – both health care providers and patients know the intervention being delivered at each health facility