Pattern of skin disease in Ethiopian HIV‐infected patients on combination antiretroviral therapy: A cross‐sectional study in a dermatology referral hospital

Abstract Background More than 90% of human immunodeficiency virus (HIV)‐infected patients will develop at least one type of skin disorder during the course of the disease. The prevalence and severity of skin disease commonly seen in HIV‐infected patients has decreased in the era of combination antiretroviral therapy (cART). Few studies in Ethiopia have shown the magnitude of skin problems among adult patients on cART. The aim of this study is to describe the pattern of skin disease among adult patients who are on cART. Methods Cross‐sectional observational study at ALERT Hospital from April 2018 to November 2018. Patterns of clinically diagnosed skin diseases were summarized descriptively. Result A total of 572 patients were evaluated. In total, 412 (72%) were female and the mean age of study participants was 40 (SD = 10.4). The median CD4 count at the time of diagnosis and start of cART were 178 (R 5‐2000) and 168 cells/μl (R 5‐1327), respectively. The mean duration of cART was 8 (SD = 3) years. 89.3% of patients were on first line and 7% on second line of cART regimen. Noninfectious inflammatory skin disorders (40.9%) were the most common concomitant diagnosis followed by infectious diseases (34.9%), infestation (7.7%), pigmentary disorders (6.3%) and cutaneous drug eruption (0.7%), respectively. Among the inflammatory skin disorders, 56.5% presented with eczema. One patient had Kaposi sarcoma. Conclusion Noninfectious inflammatory skin disorders are the most common concomitant skin disease in HIV‐infected patients, with eczema being most prevalent. Infectious skin diseases were also common presentations. In our study, AIDS‐defining skin conditions were rare

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide

Complex interactions between malaria and malnutrition: a systematic literature review

Abstract Background Despite substantial improvement in the control of malaria and decreased prevalence of malnutrition over the past two decades, both conditions remain heavy burdens that cause hundreds of thousands of deaths in children in resource-poor countries every year. Better understanding of the complex interactions between malaria and malnutrition is crucial for optimally targeting interventions where both conditions co-exist. This systematic review aimed to assess the evidence of the interplay between malaria and malnutrition. Methods Database searches were conducted in PubMed, Global Health and Cochrane Libraries and articles published in English, French or Spanish between Jan 1980 and Feb 2018 were accessed and screened. The methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale and the risk of bias across studies was assessed using the GRADE approach. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline were followed. Results Of 2945 articles screened from databases, a total of 33 articles were identified looking at the association between malnutrition and risk of malaria and/or the impact of malnutrition in antimalarial treatment efficacy. Large methodological heterogeneity of studies precluded conducting meaningful aggregated data meta-analysis. Divergent results were reported on the effect of malnutrition on malaria risk. While no consistent association between risk of malaria and acute malnutrition was found, chronic malnutrition was relatively consistently associated with severity of malaria such as high-density parasitemia and anaemia. Furthermore, there is little information on the effect of malnutrition on therapeutic responses to artemisinin combination therapies (ACTs) and their pharmacokinetic properties in malnourished children in published literature. Conclusions The evidence on the effect of malnutrition on malaria risk remains inconclusive. Further analyses using individual patient data could provide an important opportunity to better understand the variability observed in publications by standardising both malaria and nutritional metrics. Our findings highlight the need to improve our understanding of the pharmacodynamics and pharmacokinetics of ACTs in malnourished children. Further clarification on malaria-malnutrition interactions would also serve as a basis for designing future trials and provide an opportunity to optimise antimalarial treatment for this large, vulnerable and neglected population. Trial registration PROSPERO CRD42017056934

Neonatal mortality risk of vulnerable newborns : a descriptive analysis of subnational, population‐based birth cohorts for 238 143 live births in low‐ and middle‐income settings from 2000 to 2017

Objective: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low-and middle-income countries (LMICs). Design: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000. Setting: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. Population: Live birth neonates. Methods: We categorically defined five vulnerable newborn types based on size (large-or appropriate-or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies. Main Outcome Measures: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. Results: There were 238 143 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.8, interquartile range [IQR] 2.0–3.2), PT + LGA (median RR 7.3, IQR 2.3–10.4), PT + AGA (median RR 6.0, IQR 4.4–13.2) and PT + SGA (median RR 10.4, IQR 8.6–13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies. Conclusions: Small and/or preterm babies in LIMCs have a considerably increased mortality risk compared with babies born at term and larger. This classification system may advance the understanding of the social determinants and biomedical risk factors along with improved treatment that is critical for newborn health

Vulnerable newborn types: analysis of subnational, population‐based birth cohorts for 541 285 live births in 23 countries, 2000–2021

Setting: Subnational, population-based birth cohort studies (n = 45) in 23 low-and middle-income countries (LMICs) spanning 2000–2021. Population: Liveborn infants. Methods: Subnational, population-based studies with high-quality birth outcome data from LMICs were invited to join the Vulnerable Newborn Measurement Collaboration. We defined distinct newborn types using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], non- LBW) as ten types (using all three outcomes), six types (by excluding the birthweight categorisation), and four types (by collapsing the AGA and LGA categories). We defined small types as those with at least one classification of LBW, PT or SGA. We presented study characteristics, participant characteristics, data missingness, and prevalence of newborn types by region and study. Results: Among 541 285 live births, 476 939 (88.1%) had non-missing and plausible values for gestational age, birthweight and sex required to construct the newborn types. The median prevalences of ten types across studies were T+AGA+nonLBW (58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW (14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%), PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). The median prevalence of small types (six types, 37.6%) varied across studies and within regions and was higher in Southern Asia (52.4%) than in Sub-Saharan Africa (34.9%). Conclusions: Further investigation is needed to describe the mortality risks associated with newborn types and understand the implications of this framework for local targeting of interventions to prevent adverse pregnancy outcomes in LMICs