Dataset for: Hepcidin in Tanzanian children with sickle cell disease

An anonymised dataset of 199 pediatric patients aged 3-18 years of age, enrolled in the prospective Muhimbili Sickle Cohort (MSC), (Makani et al. PloS ONE 2011), whose parent or guardian consented to participate, which included having blood and DNA samples archived for studies relating to understanding the pathophysiology of sickle cell disease in Tanzanian patients. The dataset contains variables on age, sex, sickle phenotype (derived from electrophoresis and high performance liquid chromatography), history of previous blood transfusion and averaged steady state hemoglobin concentrations over the previous year prior to the samples included in this analysis. Samples included in this analysis were collected at scheduled routine clinic visits at which children were assessed by the attending physician as “clinically well” with no current pain, no fever and were malaria test (smear and or rapid test) negative, and had no reported or recorded hospitalization in the previous month. Laboratory data from the analysed samples include complete blood count data, clinical chemistry values, inflammatory markers, iron markers, erythropoietin and hepcidin. Alpha thalassaemia 3.7 deletion and glucose-6-phosphate dehydrogenase deficiency as potentially disease modifying genotypes are also included

ONLINE VISIBILITY OF PHARMACY RESEARCH IN TANZANIA: A SCIENTOMETRIC STUDY

Objective: This scientometric analysis was carried out to map the online visibility of pharmacy research at Muhimbili University of Health and Allied Sciences (MUHAS) from 1981 to 2016.Methods: Publish or Perish software was used to collect data for 33 scientists from the School of Pharmacy at MUHAS. We retrieved data on scholars' publications, citation counts, the number of authors per publication, average citations per paper, average citations per year, h-index, g-index, contemporary H-index (Hc index) and the HI-norm index.Results: A total of 499 publications were recorded for all scholars and the most (61; 12.2%) productive was 2013. The whole study period recorded the mean relative growth rate (RGR) and doubling time (Dt) of 1.62 and 0.46 respectively. A great majority (484; 97%) of the publications were multiple-authored with nearly one third (157; 31.5%) of these being jointly contributed by six or more authors. The maximum number of citations received in a single publication was 241. The degree of collaboration among scientists was as high as 0.97. The top ranked pharmacy researchers showed variation in various metrics.Conclusion: The study findings indicate a continuous growth of pharmacy publications at MUHAS since 1981. There is a high level of collaboration among scholars and many publications have made a great impact through citations.Â

Comparison of common adverse neonatal outcomes among preterm and term infants at the National Referral Hospital in Tanzania: a case-control study

Background: Neonatal period is a critical period in a child’s heath because it is associated with higher risk of adverse health outcomes. The objective of this study was to assess common adverse health outcomes and compare the risk of such outcomes between preterm and term neonates, in Tanzania. Methods: This was a case-control study involving infants admitted at Muhimbili National Hospital between August and October 2020. About 222 pairs of preterm and term infants were followed until discharge. Logistic regression was used to compare risk of health outcomes. Statistical significance was achieved at p–value < 0.05 and 95% confidence interval. Result: Preterm neonates had increased risk of mortality (OR = 7.2, 95% CI: 3.4-15.1), apnea (OR = 4.7, 95% CI: 3.4 – 15.1), respiratory distress syndrome (OR = 10.9, 95% CI: 6.1 – 19.6), necrotizing enterocolitis (OR = 5.5, 95% CI: 1.2 – 25.3), anemia (OR = 4.3, 95% CI: 2.8 – 6.6), pneumonia (OR = 2.7, 95% CI: 1.6 – 4.6) and sepsis (OR = 2.6, 95% CI: 1.7 – 3.9). No difference in risk of intraventricular hemorrhage, patent ductus arteriosus and jaundice was observed. Conclusion: For promoting neonates' health, prevention and treatment of the higher risk adverse neonatal outcomes should be prioritized

Editorial: Building capacity for sickle cell disease research and healthcare.

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Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in sickle cell disease in Tanzania

Background Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common genetic variants which differ across populations and hence do not fully account for HbF variation. Methods We investigated rare and common genetic variants that influence HbF levels in 14 SCD patients to elucidate variants and pathways in SCD patients with extreme HbF levels (≥7.7% for high HbF) and (≤2.5% for low HbF) in Tanzania. We performed targeted next generation sequencing (Illumina_Miseq) covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. Results Results revealed a range of genetic variants, including bi-allelic and multi-allelic SNPs, frameshift insertions and deletions, some of which have functional importance. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletions in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. Conclusions This study provides new insights in selecting essential variants and identifying potential biological pathways associated with extreme HbF levels in SCD interrogating multiple genomic variants associated with HbF in SCD

Pharmacy refill adherence outperforms self-reported methods in predicting HIV therapy outcome in resource-limited settings

BACKGROUND: Optimal adherence to antiretroviral therapy is critical to prevent HIV drug resistance (HIVDR) epidemic. The objective of the study was to investigate the best performing adherence assessment method for predicting virological failure in resource-limited settings (RLS). METHOD: This study was a single-centre prospective cohort, enrolling 220 HIV-infected adult patients attending an HIV/AIDS Care and Treatment Centre in Dar es Salaam, Tanzania, in 2010. Pharmacy refill, self-report (via visual analog scale [VAS] and the Swiss HIV Cohort study-adherence questionnaire), pill count, and appointment keeping adherence measurements were taken. Univariate logistic regression (LR) was done to explore a cut-off that gives a better trade-off between sensitivity and specificity, and a higher area under the curve (AUC) based on receiver operating characteristic curve in predicting virological failure. Additionally, the adherence models were evaluated by fitting multivariate LR with stepwise functions, decision trees, and random forests models, assessing 10-fold multiple cross validation (MCV). Patient factors associated with virological failure were determined using LR. RESULTS: Viral load measurements at baseline and one year after recruitment were available for 162 patients, of whom 55 (34%) had detectable viral load and 17 (10.5%) had immunological failure at one year after recruitment. The optimal cut-off points significantly predictive of virological failure were 95%, 80%, 95% and 90% for VAS, appointment keeping, pharmacy refill, and pill count adherence respectively. The AUC for these methods ranged from 0.52 to 0.61, with pharmacy refill giving the best performance at AUC 0.61. Multivariate logistic regression with boost stepwise MCV had higher AUC (0.64) compared to all univariate adherence models, except pharmacy refill adherence univariate model, which was comparable to the multivariate model (AUC = 0.64). Decision trees and random forests models were inferior to boost stepwise model. Pharmacy refill adherence (<95%) emerged as the best method for predicting virological failure. Other significant predictors in multivariate LR were having a baseline CD4 T lymphocytes count < 200 cells/μl, being unable to recall the diagnosis date, and a higher weight. CONCLUSION: Pharmacy refill has the potential to predict virological failure and to identify patients to be considered for viral load monitoring and HIVDR testing in RLS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2458-14-1035) contains supplementary material, which is available to authorized users

the interplay of two wicked problems

Funding Information: This work was funded by VLIR-UOS, grant numbers TZ2019SIN263 and TZ2020JOI032A101. Publisher Copyright: ©Concern is justified observing the link between the AIDS and COVID-19 pandemics. COVID-19 outcomes are significantly worse in many people living with HIV (PLHIV), even when vaccinated, because of their impaired immune system. Moreover, CD4 T-cells are affected by both HIV and SARS-CoV-2.1-3 SARS-CoV-2 variants can evolve in immunosuppressed patients due to prolonged viral replication in the context of an inadequate immune response.4 Accelerated intrahost evolution of SARS-CoV-2 was reported in a South African HIV patient with antiretroviral therapy (ART) failure.5 6 With 25 million HIV patients in sub-Saharan Africa (SSA) of whom an estimated 8 million are not virologically suppressed, this potentially creates a reservoir for future variants. Such variants, arising in PLHIV anywhere in the world, can spread to other continents, as has been reported for variants of concern (VoCs) (Beta, Omicron) and variants of interest (B.1.6.20, B.1.640.2) that arose in Africa.7-9 Conversely, the COVID-19 pandemic impacts HIV treatment programmes, due to supply chain issues, overburdening of healthcare systems, limiting access to testing, treatment and prevention programmes and further increasing inequalities.10 Modelled COVID-19 disruptions of HIV programmes in SSA included decreased functionality of HIV prevention programmes, HIV testing and treatment, healthcare services such as viral load testing, adherence counselling, drug regimen switches and ART interruptions, which may lead to selection of drug-resistant HIV.11 A 6-month interruption affecting 50% of the population would lead to a median number of excess deaths of 296 000, during 1 year. Scientists advocate for the AIDS and COVID-19 pandemics in Africa to be addressed simultaneously, by increasing African access to COVID-19 vaccines, prioritising research on the interaction between HIV care and COVID-19, maintaining high-quality HIV services and integrating health services for both viruses.7 Both the COVID-19 and the AIDS pandemic, more specifically the issue of HIV drug resistance (HIVDR), have previously been described as wicked problems which are best studied as complex adaptive systems (CASs).12-15Wicked problems consist of diverse interconnected factors and require complexity-informed and locally adapted solutions rather than one solution that fits all. We recently designed a qualitative model of all known factors influencing HIVDR in SSA and analysed its complexity.13 Our detailed systems map featured three main feedback loops driving HIVDR, representing (1) the alternation between adherence and non-adherence, (2) the impact of an overburdened healthcare system and (3) the importance of sustaining global efforts of tackling HIVDR even when new antiretroviral drugs with high genetic barriers become available. These HIV-related feedback loops are interconnected with COVID-19 pandemic impact (in yellow, figure 1). The loop starts from PLHIV with an unsuppressed viral load, which weakens the immune system and may in turn slow down immune clearance of SARS-CoV-2, allowing prolonged replication and mutation of the virus in the context of an inadequate immune response. Prolonged viral clearance facilitates the selection of immune escape SARS-CoV-2 variants. Variants may emerge that have a selective advantage and therefore may spread through populations due to increased transmissibility (with possibly increased virulence), thereby creating an additional burden on the healthcare system, putting the overall healthcare system and the HIV care at risk. These stressors on the healthcare system lead to a higher risk of unsuppressed viral load in PLHIV, increasing the risk of HIVDR. Figure 1 shows the need to address both wicked problems simultaneously and to do so in a complexity-informed manner as they are inevitably linked and influence each other. Evidently, the exact interconnections between both pandemics need to be locally assessed. For instance, a study in South Africa showed that while lockdown severely impacted HIV testing and ART initiation, ART provision was largely maintained, indicating that the strength of the connection between the virological suppression-related loop and the pandemic, indicated in figure 1, are context-dependent.16publishersversionpublishe

conceptual mapping of a complex adaptive system based on multi-disciplinary expert insights

Funding Information: This study was partially funded by VLIR-UOS. The study sponsors had no role in the study design, the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Publisher Copyright: © 2022, The Author(s).Background: HIV drug resistance (HIVDR) continues to threaten the effectiveness of worldwide antiretroviral therapy (ART). Emergence and transmission of HIVDR are driven by several interconnected factors. Though much has been done to uncover factors influencing HIVDR, overall interconnectedness between these factors remains unclear and African policy makers encounter difficulties setting priorities combating HIVDR. By viewing HIVDR as a complex adaptive system, through the eyes of multi-disciplinary HIVDR experts, we aimed to make a first attempt to linking different influencing factors and gaining a deeper understanding of the complexity of the system. Methods: We designed a detailed systems map of factors influencing HIVDR based on semi-structured interviews with 15 international HIVDR experts from or with experience in sub-Saharan Africa, from different disciplinary backgrounds and affiliated with different types of institutions. The resulting detailed system map was conceptualized into three main HIVDR feedback loops and further strengthened with literature evidence. Results: Factors influencing HIVDR in sub-Saharan Africa and their interactions were sorted in five categories: biology, individual, social context, healthcare system and ‘overarching’. We identified three causal loops cross-cutting these layers, which relate to three interconnected subsystems of mechanisms influencing HIVDR. The ‘adherence motivation’ subsystem concerns the interplay of factors influencing people living with HIV to alternate between adherence and non-adherence. The ‘healthcare burden’ subsystem is a reinforcing loop leading to an increase in HIVDR at local population level. The ‘ART overreliance’ subsystem is a balancing feedback loop leading to complacency among program managers when there is overreliance on ART with a perceived low risk to drug resistance. The three subsystems are interconnected at different levels. Conclusions: Interconnectedness of the three subsystems underlines the need to act on the entire system of factors surrounding HIVDR in sub-Saharan Africa in order to target interventions and to prevent unwanted effects on other parts of the system. The three theories that emerged while studying HIVDR as a complex adaptive system form a starting point for further qualitative and quantitative investigation.publishersversionpublishe

Gender Differences in HIV Disease Progression and Treatment Outcomes among HIV Patients One Year after Starting Antiretroviral Treatment (ART) in Dar es Salaam, Tanzania.

We investigated gender differences in treatment outcome during first line antiretroviral treatment (ART) in a hospital setting in Tanzania, assessing clinical, social demographic, virological and immunological factors. We conducted a cohort study involving HIV infected patients scheduled to start ART and followed up to 1 year on ART. Structured questionnaires and patients file review were used to collect information and blood was collected for CD4 and viral load testing. Gender differences were assessed using Kruskal-Wallis test and chi-square test for continuous and categorical data respectively. Survival distributions for male and female patients were estimated using the Kaplan-Meier method and compared using Cox proportional hazards models. Of 234 patients recruited in this study, 70% were females. At baseline, women had significantly lower education level; lower monthly income, lower knowledge on ARV, less advanced HIV disease (33% women; 47% men started ART at WHO stage IV, p = 0.04), higher CD4 cell count (median 149 for women, 102 for men, p = 0.02) and higher BMI (p = 0.002). After 1 year of standard ART, a higher proportion of females survived although this was not significant, a significantly higher proportion of females had undetectable plasma viral load (69% women, 45% men, p = 0.003), however females ended at a comparable CD4 cell count (median CD4, 312 women; 321 men) signifying a worse CD4 cell increase (p = 0.05), even though they still had a higher BMI (p = 0.02). The unadjusted relative hazard for death for men compared to women was 1.94. After correcting for confounding factors, the Cox proportional hazards showed no significant difference in the survival rate (relative hazard 1.02). We observed women were starting treatment at a less advanced disease stage, but they had a lower socioeconomical status. After one year, both men and women had similar clinical and immunological conditions. It is not clear why women lose their immunological advantage over men despite a better virological treatment response. We recommend continuous follow up of this and more cohorts of patients to better understand the underlying causes for these differences and whether this will translate also in longer term differences

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations. Epistatic interactions were learned from three different cross-sectional BNs, trained with sequence from patients experienced with indinavir (BNT), all protease inhibitors (PIs) (BNP) or all PI except indinavir (BND). Scaling the fitness landscape was done using cross-sectional data from drug naïve and indinavir experienced patients (Fcross using BNT) and using longitudinal sequences from patients failing indinavir (FlongT using BNT, FlongP using BNP, FlongD using BND). Evaluation to predict the failing sequence and therapy outcome was performed on independent sequences of patients on indinavir. Parameters included estimated fitness (LogF), the number of generations (GF) or mutations (MF) to reach the fitness threshold (average fitness when a major resistance mutation appeared), the number of generations (GR) or mutations (MR) to reach a major resistance mutation and compared to genotypic susceptibility score (GSS) from Rega and HIVdb algorithms. In pairwise FL comparisons we found significant correlation between fitness values for individual sequences, and this correlation improved after correcting for the subtype. Furthermore, FLs could predict the failing sequence under indinavir-containing combinations. At 12 and 48 weeks, all parameters from all FLs and indinavir GSS (both for Rega and HIVdb) were predictive of therapy outcome, except MR for FlongT and FlongP. The fitness landscapes have similar predictive power for treatment response under indinavir-containing regimen as standard rules-based algorithms, and additionally allow predicting genetic evolution under indinavir selective pressure