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Striga is one of most notorious weeds devastating crop production in the dry savannas of northern Nigeria. The weed attacks most cultivated cereals and legumes with crop losses as high as 100% when no control measure is employed. Studies conducted in the dry savannas of Nigeria indicated that Striga seedbank is strongly related to soil and climate properties. This study was conducted to model Striga hermonthica seedbank zones in the dry savannas of Nigeria based on soil and climate properties of the areas. Using multi‐stage spatial sampling, 169 soil samples were collected at the centroids of 25 × 25 km grids across the study area and analysed for physico‐chemical properties. The number of Striga seeds were counted from the soil samples using water elutriator and potassium bicarbonate method. Daily temperature, relative humidity and rainfall for each point were downloaded from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Minimum and maximum temperatures, and relative humidity were accessed from National Aeronautics and Space Administration (NASA POWER). Thresholds of various soil and climate variables for optimum concentration of Striga seedbank were analysed using boundary line analysis (BLA). From the BLA, optimum amount of rainfall for high Striga seedbank was 549 mm per annum. While temperature has a wide suitability range for Striga seedbank development. Principal component analysis was used to reduce dimensionality of the dataset into principal components (PCs). Seven PCs which explained 75.6% variation in the data were retained and used in the weighed overlay modelling (WOM). The weighted overlay map produced five distinct Striga seedbank zones; very low, low, moderate, high and very high. More than 60% of the study area had moderate to high Striga seedbanks. The zones vary mostly based on soil, climate and Striga seed count. The establishment of the optimum levels of the environmental factors at which Striga seedbank is favoured will assist in designing a more site‐specific Striga management. However, for scalability purpose, adoption of the Striga zoning approach can be useful. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity, defined as having two or more chronic diseases, has a major impact on public health and Sustainable Development Goals (SDG). This study aims to assess the prevalence of medication adherence and associated factors among patients with multimorbidity. Methods: A questionnaire-based, cross-sectional survey was conducted by a trained interviewer across patients with multimorbidity attending outpatient clinics in two tertiary referral hospitals in the United Arab Emirates (UAE). Demographic and social variables and the outcome (self-reported adherence to long-term medication) were measured using the General Medication Adherence Scale (GMAS). Multiple logistic regression was used to assess medication adherence and associated factors. Results: From a total of 630 participants included in this study, the estimated prevalence of high medication adherence is 78.57% (± 1.63478) with a 95% confidence interval (CI) [75.19, 81.61]. The odds of high medication adherence increased with age. The odds of high medication adherence for patients aged 66 years and older than those aged 19– 35 years is adjusted odds ratio (AOR) = 3.880, with a 95% CI [1.124, 13.390]. Patients with income more than 50,000 had the odds, AOR = 5.169 with a 95% CI [1.282, 20.843], compared to those earning less than 10,000 Dirhams (AED). Patients aged 36– 65 with health insurance coverage had higher medication adherence than groups on the other end. The number of current medications is significantly (p-value = 0.027) associated with high medication adherence with the odds of high medication adherence, AOR = 4.529 with a 95% CI [1.184, 17.326], the highest for those currently taking four medications. Conclusion: This study highlights younger population having multimorbidity in the context of an increasing life expectancy and suboptimal therapeutic outcomes. Furthermore, the study highlights multimorbidity is associated with low medication adherence and out-of-pocket payment, and non-availability of insurance is a major hindrance to medication adherence. [ABSTRACT FROM AUTHOR]