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Halimium, Cistaceae, is a genus of shrubs restricted to the western part of the Mediterranean basin, where it thrives in diverse habitats. Despite this ecological adaptability, little attention has been devoted to understanding the mycorrhizal biology of Halimium. Through the examination of both sporocarps and ectomycorrhizal root tip collections, together with a thorough study of data previously reported in the relevant literature, we revealed a rich diversity of ectomycorrhizal mycobiota associated with Halimium spp. In this study, we describe the noteworthy diversity of the basidiomycetous family Inocybaceae in Halimium stands. Some 17 species of Inocybe and Pseudosperma are currently reported as linked to Halimium spp., mostly on the basis of sporocarp occurrence in the proximity of the potential host plant. Of these species, over 40% (7 of 17) come from our own study based on observations in pure Halimium stands in southwestern Sardinia, Italy. We also describe two new species of Inocybe, I. halimiphila sp. nov. and Inocybe rupribes sp. nov., that were collected under Halimium and demonstrated to establish ectomycorrhizal symbiosis with the shrub. We discuss the main morphological and ecological characteristics that distinguish the new species, unveiling their evolutionary relationships by inferring a phylogeny based on multiple loci.

Abstract Background Healthcare systems in low-resource settings need simple, low-cost interventions to improve services and address gaps in care. Though routine data provide opportunities to guide these efforts, frontline providers are rarely engaged in analyzing them for facility-level decision making. The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages providers in use of facility-level data to promote systems-level thinking and quality improvement (QI) efforts within multi-step care cascades. SAIA was originally developed to address HIV care in resource-limited settings but has since been adapted to a variety of clinical care systems including cervical cancer screening, mental health treatment, and hypertension management, among others; and across a variety of settings in sub-Saharan Africa and the USA. We aimed to extend the growing body of SAIA research by defining the core elements of SAIA using established specification approaches and thus improve reproducibility, guide future adaptations, and lay the groundwork to define its mechanisms of action. Methods Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA-researchers, implementing agents and stakeholders using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor’s recommendations for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects. Results Based on this review and clarification of the operational definitions of the components of the SAIA, the four components of SAIA were mapped to 13 ERIC strategies. SAIA strategy meetings encompassed external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to three ERIC strategies: facilitating relay of clinical data to providers, use of audit and feedback of routine data with healthcare teams, and modeling and simulation of change. Process mapping matched to local needs assessment, local consensus discussions and assessment of readiness and identification of barriers and facilitators. Finally, continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change, and purposefully re-examining the implementation process. Conclusions Specifying the components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings.

Abstract Background This study assessed the prevalence of suicidal behavior and associated risk factors in public primary health care in Mozambique. Methods The Mini International Neuropsychiatric Interview was used to evaluate suicidal behavior among 502 adults attending three Primary Health Care (PHC) settings. Results In the past month, 13% (n = 63) of PHC attendees expressed suicidal ideation, 8% (n = 40) had made a suicide plan, 4% (n = 20) had made a suicide attempt, and 5% (n = 25) reported a lifetime suicide attempt. Females had 2.8-fold increased odds of suicide plan (95% CI: 1.5, 5.5) and 3.3-fold increased odds of suicide attempt in the past month (95% CI: 1.2, 9.1). Each 10-year increase in age was associated with 0.61-fold the odds of suicide plan (95% CI: 0.38, 0.98) and 0.09-fold the odds of suicide attempt (95% CI: 0.01, 0.69) in the past month. People living with HIV (PLWHA) had 2.2-fold increased adjusted odds of past month suicide attempt (CI: 1.1, 4.1). Conclusion Suicidal behaviors are common among adults attending PHC clinics in Mozambique. Screening and linkage to effective preventive interventions are urgently needed in PHC settings. Females, younger individuals, and PLWHA are at elevated risk for suicidal behavior in PHC.

Background In Mozambique, the prevalence of common mental illness in primary care is not well established. Aims This study aimed to assess the prevalence of, and associated factors for, common mental illness in patients accessing primary care services in three Ministry of Health clinics in Mozambique. Method Adult patients were recruited from the waiting rooms of prenatal, postpartum and general out-patient consultations. A mental health professional administered a diagnostic interview to examine prevalence of major depressive disorder (MDD), generalised anxiety disorder (GAD), post-traumatic stress disorder (PTSD) and any substance misuse or dependence. Generalised linear mixed models were used to examine the odds of each disorder and sociodemographic associations. Results Of 502 patients interviewed, 74.1% were female (n = 372) and the average age was 27.8 years (s.d. = 7.4). Of all participants, 23.9% (n = 120) met diagnostic criteria for at least one common mental disorder; 8.6% were positive for MDD (n = 43), 13.3% were positive for GAD (n = 67), 4.8% were positive for PTSD (n = 24) and 4.0% were positive for any substance misuse or dependence (n = 20). Patients attending prenatal or postpartum consultations had significantly lower odds of any common mental disorder than patients attending out-patient primary care. Age was negatively associated with MDD, but positively associated with substance misuse or dependence. Conclusions Over 20% of patients attending primary care in Mozambique may have common mental disorders. A specific focus on patients attending general out-patient visits, young people for depression, and older people and men for substance misuse/dependence would provide a targeted response to high-risk demographics.

Abstract Background Depression is one of the leading causes of disability in Mozambique; however, few patients with depression are identified in primary care. To our knowledge, there are no validated tools for depression screening in Mozambique. The aim of this study was to validate the Patient Health Questionnaire-9 (PHQ-9) for use in primary care settings in Mozambique. Methods The PHQ-9 was adapted using a structured multi-phase process led by a team of bilingual experts followed by a review by lay individuals and pilot-testing including cognitive interviews. The final Mozambican PHQ-9 (PHQ-9-MZ) was applied among 502 individuals randomly selected from antenatal, postpartum, and general outpatient consultations in three Ministry of Health primary healthcare clinics in Sofala Province, Mozambique. The PHQ-9-MZ was evaluated against the MINI 5.0-MZ as a gold standard diagnostic tool. Results The majority of participants were female (74%), with a mean age of 28. Using the MINI 5.0-MZ, 43 (9%) of the sample tested positive for major depressive disorder. Items of the PHQ-9-MZ showed good discrimination and factor loadings. One latent factor of depression explained 54% of the variance in scores. Questions 3 (sleep) and 5 (appetite) had the lowest item discrimination and factor loadings. The PHQ-9-MZ showed good internal consistency, with a Cronbach’s alpha of 0.84, and an area under the receiver operating characteristic curve (AUROC) of 0.81 (95% CI: 0.73, 0.89). The PHQ-2-MZ had an AUROC of 0.78 (95% CI: 0.70, 0.85). Using a cut-point of ≥9, the PHQ-9-MZ had a sensitivity of 46.5% and a specificity of 93.5%. Using a cut-point of ≥2, the PHQ-2-MZ had a sensitivity of 74.4% and a specificity of 71.7%. Increasing the cut-point to ≥3, the PHQ-2-MZ has a sensitivity of 32.6% and a specificity of 94.6%. Conclusions The PHQ-9-MZ and PHQ-2-MZ emerge as two valid alternatives for screening for depression in primary health care settings in Mozambique. Depending on program needs and weighing the value of minimizing false positives and false negatives, the PHQ-9-MZ can be employed with cut-points ranging from ≥8 to ≥11, and the PHQ-2-MZ with cut-points ranging from ≥2 to ≥3.

Abstract Background Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique. Methods Mozambique’s most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106 km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard “random walk” procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters. Results Civil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age). Conclusions Other implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery.

An amendment to this paper has been published and can be accessed via the original article.