No abstract

Tinea capitis is a common and endemic dermatophytosis among school age children in Africa. However, the true burden of the disease is unknown in Africa. We aimed to estimate the burden of tinea capitis among children <18 years of age in Africa. A systematic review was performed using Embase, MEDLINE and the Cochrane Library of Systematic Reviews to identify articles on tinea capitis among children in Africa published between January 1990 and October 2020. The United Nation's Population data (2019) were used to identify the number of children at risk of tinea capitis in each African country. Using the pooled prevalence, the country‐specific and total burden of tinea capitis was calculated. Forty studies involving a total of 229,086 children from 17/54 African countries were identified and included in the analysis. The pooled prevalence of tinea capitis was 23% (95% CI, 17%–29%) mostly caused by Trichophyton species. With a population of 600 million (46%) children, the total number of cases of tinea capitis in Africa was estimated at 138.1 (95% CI, 102.0–174.1) million cases. Over 96% (132.6 million) cases occur in sub‐Saharan Africa alone. Nigeria and Ethiopia with the highest population of children contributed 16.4% (n = 98.7 million) and 8.5% (n = 52.2 million) of cases, respectively. Majority of the participants were primary school children with a mean age of 10 years. Cases are mostly diagnosed clinically. There was a large discrepancy between the clinical and mycological diagnosis. About one in every five children in Africa has tinea capitis making it one of the most common childhood conditions in the region. A precise quantification of the burden of this neglected tropical disease is required to inform clinical and public health intervention strategies.

The interpretation of DNA profiles typically starts with an assessment of the number of contributors. In the last two decades, several methods have been proposed to assist with this assessment. We describe a relatively simple method using decision trees, that is fast to run and fully transparent to a forensic analyst. We use mixtures from the publicly available PROVEDIt dataset to demonstrate the performance of the method. We show that the performance of the method crucially depends on the performance of filters for stutter and other artefacts. We compare the performance of the decision tree method with other published methods for the same dataset.

Until recently, forensic DNA profile interpretation was predominantly a manual, time-consuming process undertaken by analysts using heuristics to determine those genotype combinations that could reasonably explain a recovered profile. Probabilistic genotyping (PG) has now become commonplace in the interpretation of DNA profiling evidence. As the complexity of PG necessitates the use of algorithms and modern computing power it has been dubbed by some critics as a "black box" approach. Here we discuss the wealth of information that is provided within the output of STRmix™, one example of a continuous PG system. We discuss how this information can be evaluated by analysts either to give confidence in the results or to indicate that further interpretation may be warranted. Specifically, we discuss the "primary" and "secondary" diagnostics output by STRmix™ and give some context to the values that may be observed.

Objectives: To determine the prevalence, clinical characteristics and outcomes of HIV and severe acute respiratory syndrome coronavirus 2 (SARS−CoV−2) co−infection. Methods: We searched Medline, Embase, Cochrane and Web of Science databases and grey literature for studies reporting epidemiological and clinical data of patients with HIV and SARS−CoV−2 co−infection. Eligible studies were all observational or interventional studies and commentaries in English language that reported patient data on HIV/SARS−CoV−2 co−infection. We used random effect meta−analysis to determine the pooled prevalence and mortality. Results: Of the 17 eligible studies, there were 3 retrospective cohorts, 1 survey, 5 case series, 7 case reports and 1 commentary that reported on a total of 146 HIV infected individuals. The pooled prevalence of HIV among individuals with SARS−CoV−2 infection was 1.0% (95% CI: 0.0 − 3.0, I2 = 79.3%, p=0.01), whereas the prevalence of SARS−CoV−2 among HIV patients was 0.68% (95% CI: 0.34 − 1.34). There were 110 (83.8%) HIV/ SARS−CoV−2 co−infected males, and the age (range) of the co−infected was 30 − 60 years. A total of 129 (97.0%) were anti−retroviral therapy experienced, and 113 (85.6%) had a suppressed HIV viral load. The CD4 count (range) was 298 − 670 cells/mm3 (n = 107). The commonest symptoms were fever (73.5%, n=75) and cough (57.8%, n = 59). Sixty−two (65.3%) patients had at least one other comorbid condition, of which hypertension (26.4%, n = 38) was the commonest. Chest radiological imaging abnormalities were found in 46 (54.1%) cases. Twenty-eight cases (56.0%) were reported as mild. Recovery occurred in 120 (88.9%) cases, and the pooled mortality was 9% (95% CI: 3.0 − 15.0, I2 = 25.6%, p =0.24). Conclusion: The prevalence of HIV/SARS−CoV−2 co−infection was low. The clinical characteristics and outcomes of HIV/SARS−CoV−2 co−infection are comparable to those reported among HIV negative SARS−CoV−2 cases.