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Background In drug trials, clinical adverse events (AEs), concomitant medication and laboratory safety outcomes are repeatedly collected to support drug safety evidence. Despite the potential correlation of these outcomes, they are typically analysed separately, potentially leading to misinformation and inefficient estimates due to partial assessment of safety data. Using joint modelling, we investigated whether clinical AEs vary by treatment and how laboratory outcomes (alanine amino-transferase, total bilirubin) and concomitant medication are associated with clinical AEs over time following artemisinin-based antimalarial therapy. Methods We used data from a trial of artemisinin-based treatments for malaria during pregnancy that randomized 870 women to receive artemether–lumefantrine (AL), amodiaquine–artesunate (ASAQ) and dihydroartemisinin–piperaquine (DHAPQ). We fitted a joint model containing four sub-models from four outcomes: longitudinal sub-model for alanine aminotransferase, longitudinal sub-model for total bilirubin, Poisson sub-model for concomitant medication and Poisson sub-model for clinical AEs. Since the clinical AEs was our primary outcome, the longitudinal sub-models and concomitant medication sub-model were linked to the clinical AEs sub-model via current value and random effects association structures respectively. We fitted a conventional Poisson model for clinical AEs to assess if the effect of treatment on clinical AEs (i.e. incidence rate ratio (IRR)) estimates differed between the conventional Poisson and the joint models, where AL was reference treatment. Results Out of the 870 women, 564 (65%) experienced at least one AE. Using joint model, AEs were associated with the concomitant medication (log IRR 1.7487; 95% CI: 1.5471, 1.9503; p p = 0.906) and alanine aminotransferase (log IRR: 0.1153; 95% CI: − 0.0889, 0.3194; p = 0.269). The Poisson model underestimated the effects of treatment on AE incidence such that log IRR for ASAQ was 0.2118 (95% CI: 0.0082, 0.4154; p = 0.041) for joint model compared to 0.1838 (95% CI: 0.0574, 0.3102; p = 0.004) for Poisson model. Conclusion We demonstrated that although the AEs did not vary across the treatments, the joint model yielded efficient AE incidence estimates compared to the Poisson model. The joint model showed a positive relationship between the AEs and concomitant medication but not with laboratory outcomes. Trial registration ClinicalTrials.gov: NCT00852423

Background Drug safety assessments in clinical trials present unique analytical challenges. Some of these include adjusting for individual follow-up time, repeated measurements of multiple outcomes and missing data among others. Furthermore, pre-specifying appropriate analysis becomes difficult as some safety endpoints are unexpected. Although existing guidelines such as CONSORT encourage thorough reporting of adverse events (AEs) in clinical trials, they provide limited details for safety data analysis. The limited guidelines may influence suboptimal analysis by failing to account for some analysis challenges above. A typical example where such challenges exist are trials of anti-malarial drugs for malaria prevention during pregnancy. Lack of proper standardized evaluation of the safety of antimalarial drugs has limited the ability to draw conclusions about safety. Therefore, a systematic review was conducted to establish the current practice in statistical analysis for preventive antimalarial drug safety in pregnancy. Methods The search included five databases (PubMed, Embase, Scopus, Malaria in Pregnancy Library and Cochrane Central Register of Controlled Trials) to identify original English articles reporting Phase III randomized controlled trials (RCTs) on anti-malarial drugs for malaria prevention in pregnancy published from January 2010 to July 2019. Results Eighteen trials were included in this review that collected multiple longitudinal safety outcomes including AEs. Statistical analysis and reporting of the safety outcomes in all the trials used descriptive statistics; proportions/counts (n = 18, 100%) and mean/median (n = 2, 11.1%). Results presentation included tabular (n = 16, 88.9%) and text description (n = 2, 11.1%). Univariate inferential methods were reported in most trials (n = 16, 88.9%); including Chi square/Fisher’s exact test (n = 12, 66.7%), t test (n = 2, 11.1%) and Mann–Whitney/Wilcoxon test (n = 1, 5.6%). Multivariable methods, including Poisson and negative binomial were reported in few trials (n = 3, 16.7%). Assessment of a potential link between missing efficacy data and safety outcomes was not reported in any of the trials that reported efficacy missing data (n = 7, 38.9%). Conclusion The review demonstrated that statistical analysis of safety data in anti-malarial drugs for malarial chemoprevention in pregnancy RCTs is inadequate. The analyses insufficiently account for multiple safety outcomes potential dependence, follow-up time and informative missing data which can compromise anti-malarial drug safety evidence development, based on the available data.

The World Health Organisation (WHO) recommends that severe wasting and/or oedema should be treated with ready-to-use therapeutic food (RUTF) at a dose of 150–220 kcal/kg/day for 6–8 weeks. Emerging evidence suggests that variations of RUTF dosing regimens from the WHO recommendation are not inferior. We aimed to assess the comparative efficacy and effectiveness of different RUTF doses and durations in comparison with the current WHO RUTF dose recommendation for treating severe wasting and/or oedema among 6–59-month-old children. A systematic literature search identified three studies for inclusion, and the outcomes of interest included anthropometric recovery, anthropometric measures and indices, non-response, time to recovery, readmission, sustained recovery, and mortality. The study was registered with PROSPERO, CRD 42021276757. Only three studies were eligible for analysis. There was an overall high risk of bias for two of the studies and some concerns for the third study. Overall, there were no differences between the reduced and standard RUTF dose groups in all outcomes of interest. Despite the finding of no differences between reduced and standard-dose RUTF, the studies are too few to conclusively declare that reduced RUTF dose was more efficacious than standard RUTF.

We tested the hypotheses that a more mature or diverse gut microbiota will be positively associated with infant growth and inversely associated with inflammation. We characterized gut microbiota from the stool samples of Malawian infants at 6 mo (n = 527), 12 mo (n = 632) and 18 mo (n = 629) of age. Microbiota diversity and maturity measurements were based on Shannon diversity index and microbiota for age Z-score (MAZ), respectively. Growth was calculated as change in Z-scores for weight-for-age (WAZ), length-for-age (LAZ) and head circumference-for-age (HCZ) from 6 to 12 mo and 12 to 18 mo. Biomarkers of inflammation (alpha-1-acid glycoprotein (AGP) and C-reactive protein (CRP)) were measured at 6 and 18 mo. Multivariable models were used to assess the association of each independent variable with each outcome. Microbiota diversity and maturity were related to growth in weight from 6 to 12 mo, but not to growth in length or head circumference or to growth from 12 to 18 mo. Microbiota diversity and maturity may also be linked to inflammation, but findings were inconsistent.

Background In malaria-endemic settings, a small proportion of children suffer repeated malaria infections, contributing to most of the malaria cases, yet underlying factors are not fully understood. This study was aimed to determine whether undernutrition predicts this over-dispersion of malaria infections in children aged 6–18 months in settings of high malaria and undernutrition prevalence. Methods Prospective cohort study, conducted in Mangochi, Malawi. Six-months-old infants were enrolled and had length-for-age z-scores (LAZ), weight-for-age z-scores (WAZ), and weight-for-length z-scores (WLZ) assessed. Data were collected for ‘presumed’, clinical, and rapid diagnostic test (RDT)-confirmed malaria until 18 months. Malaria microscopy was done at 6 and 18 months. Negative binomial regression was used for malaria incidence and modified Poisson regression for malaria prevalence. Results Of the 2723 children enrolled, 2561 (94%) had anthropometry and malaria data. The mean (standard deviation [SD]) of LAZ, WAZ, and WLZ at 6 months were − 1.4 (1.1), − 0.7 (1.2), and 0.3 (1.1), respectively. The mean (SD) incidences of ‘presumed’, clinical, and RDT-confirmed malaria from 6 to 18 months were: 1.1 (1.6), 0.4 (0.8), and 1.3 (2.0) episodes/year, respectively. Prevalence of malaria parasitaemia was 4.8% at 6 months and 9.6% at 18 months. Higher WLZ at 6 months was associated with lower prevalence of malaria parasitaemia at 18 months (prevalence ratio [PR] = 0.80, 95% confidence interval [CI] 0.67 to 0.94, p = 0.007), but not with incidences of ‘presumed’ malaria (incidence rate ratio [IRR] = 0.97, 95% CI 0.92 to 1.02, p = 0.190), clinical malaria (IRR = 1.03, 95% CI 0.94 to 1.12, p = 0.571), RDT-confirmed malaria (IRR = 1.00, 95% CI 0.94 to 1.06, p = 0.950). LAZ and WAZ at 6 months were not associated with malaria outcomes. Household assets, maternal education, and food insecurity were significantly associated with malaria. There were significant variations in hospital-diagnosed malaria by study site. Conclusion In children aged 6–18 months living in malaria-endemic settings, LAZ, WAZ, and WLZ do not predict malaria incidence. However, WLZ may be associated with prevalence of malaria. Socio-economic and micro-geographic factors may explain the variations in malaria, but these require further study. Trial registration NCT00945698. Registered July 24, 2009, https://clinicaltrials.gov/ct2/show/NCT00945698, NCT01239693. Registered Nov 11, 2010, https://clinicaltrials.gov/ct2/show/NCT01239693

Serum zinc concentration (SZC) is used widely to assess population-level zinc status. Its concentration decreases during inflammatory responses, which can affect the interpretation of the results. This study aimed to re-estimate the prevalence of zinc deficiency in Malawi based on the 2015&ndash, 2016 Malawi Micronutrient Survey (MNS) data, by adjusting SZC measures with markers of inflammation. SZC and inflammation data from 2760 participants were analysed. Adjustments were made using: (1) The Internal Correction Factor (ICF) method which used geometric means, and (2) The Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) method, which used linear regression. Mean SZC values increased significantly when adjustments were made by either ICF or BRINDA (p &lt, 0.001). The national prevalence of zinc deficiency decreased from 62% to 59%, after ICF adjustment, and to 52% after BRINDA adjustment. ICF and BRINDA values of SZC were highly correlated (p &lt, 0.001, r = 0.99), but a Bland&ndash, Altman plot showed a lack of agreement between the two methods (bias of 2.07 &micro, g/dL). There was no association between the adjusted SZC and stunting, which is a proxy indicator for zinc deficiency. Inflammation adjustment of SZC, using ICF or BRINDA, produces lower estimates of zinc deficiency prevalence, but the lack of agreement between the adjustment methods warrants further research. Furthermore, the lack of association between SZC and stunting highlights the need to explore other biomarkers and proxies of population zinc assessment. This study demonstrates the importance of considering inflammatory confounders when reporting SZC, to ensure accuracy and to support policy decision making.

Author(s): Kamng'ona, Arox W; Young, Rebecca; Arnold, Charles D; Patson, Noel; Jorgensen, Josh M; Kortekangas, Emma; Chaima, David; Malamba, Chikondi; Ashorn, Ulla; Cheung, Yin B; Ashorn, Per; Maleta, Kenneth; Dewey, Kathryn G | Abstract: BACKGROUND:Diet may alter the configuration of gut microbiota, but the impact of prenatal and postnatal nutritional interventions on infant gut microbiota has not been investigated. OBJECTIVE:We evaluated whether providing lipid-based nutrient supplements (LNSs) to mother-infant dyads promotes a more diverse and mature infant gut microbiota, compared to maternal supplementation with multiple micronutrients (MMN) or iron and folic acid (IFA). METHODS:We enrolled 869 pregnant women in a randomized trial in Malawi. There were 3 study groups, with women receiving 1 MMN capsule daily during pregnancy and 6nmo postpartum, or 1 LNS sachet (20 g) daily during pregnancy and 6nmo postpartum, or 1 IFA capsule daily (during pregnancy) then a placebo daily (postpartum). Infants in the LNS group received LNS from 6 to 18nmo; infants in the other groups did not receive supplements. The infants' fecal microbiota were characterized by PCR amplification and sequencing of the bacterial 16S rRNA gene (variable region 4). The primary outcomes were microbiota α diversity and maturation [as microbiota-for-age z score (MAZ)]. Specific associations of taxa with intervention were established with indicator species analysis (ISA). RESULTS:Primary outcomes did not differ between IFA and MMN groups, so these groups were combined (IFAn+nMMN). Meann±nSD α diversity was higher in the LNS group at 18nmo for Shannon index [3.01n±n0.57 (LNS) compared with 2.91n±n0.60 (IFAn+nMMN), Pn=n0.032] and Pielou's evenness index [0.61n±n0.08 (LNS) compared with 0.60n±n0.09 (IFAn+nMMN), Pn=n0.043]; no significant differences were observed at 1, 6, 12, or 30nmo. MAZ and β diversity did not differ at any age. We found 10 and 3 operational taxonomic units (OTUs) positively associated with LNS and IFAn+nMMN, respectively; however, these associations became nonsignificant following false discovery rate correction at 10%. CONCLUSIONS:Prenatal and postnatal LNS intake promoted infant gut microbiota diversity at 18nmo, after 12nmo of child supplementation, but did not alter microbiota maturation. This trial was registered at clinicaltrials.gov as NCT01239693.

Although poor complementary feeding is associated with poor child growth, nutrition interventions only have modest impact on child growth, due to high burden of infections. We aimed to assess the association of malaria with linear growth, hemoglobin, iron status, and development in children aged 6–18 months in a setting of high malaria and undernutrition prevalence. Prospective cohort study, conducted in Mangochi district, Malawi. We enrolled six-months-old infants and collected weekly data for ‘presumed’ malaria, diarrhea, and acute respiratory infections (ARI) until age 18 months. Change in length-for-age z-scores (LAZ), stunting, hemoglobin, iron status, and development were assessed at age 18 months. We used ordinary least squares regression for continuous outcomes and modified Poisson regression for categorical outcomes. Of the 2723 children enrolled, 2016 (74.0%) had complete measurements. The mean (standard deviation) incidences of ‘presumed’ malaria, diarrhea, and ARI, respectively were: 1.4 (2.0), 4.6 (10.1), and 8.3 (5.0) episodes/child year. Prevalence of stunting increased from 27.4 to 41.5% from 6 to 18 months. ‘Presumed’ malaria incidence was associated with higher risk of stunting (risk ratio [RR] = 1.04, 95% confidence interval [CI] = 1.01 to 1.07, p = 0.023), anemia (RR = 1.02, 95%CI = 1.00 to 1.04, p = 0.014) and better socio-emotional scores (B = − 0.21, 95%CI = − 0.39 to − 0.03, p = 0.041), but not with change in LAZ, haemoglobin, iron status or other developmental outcomes. Diarrhea incidence was associated with change in LAZ (B = − 0.02; 95% CI = − 0.03 to − 0.01; p = 0.009), stunting (RR = 1.02; 95% CI = 1.01 to 1.03; p = 0.005), and slower motor development. ARI incidence was not associated with any outcome except for poorer socio-emotional scores. In this population of young children living in a malaria-endemic setting, with active surveillance and treatment, ‘presumed’ malaria is not associated with change in LAZ, hemoglobin, or iron status, but could be associated with stunting and anemia. Diarrhea was more consistently associated with growth than was malaria or ARI. The findings may be different in contexts where active malaria surveillance and treatment is not provided. NCT00945698 (July 24, 2009) and NCT01239693 (November 11, 2010).

Traditional methods for depicting directed graphs are inadequate when the number of vertices and edges are too large. Also underlying geographical coordinates are generally not considered. A new visualisation method is presented which transforms graphs into a 3D surface which can be shown as a contour map superimposed over a geographical region thereby preserving the underlying geographical details.

The large volumes of information that arise from telecommunications and cyberspace systems can be represented by massive digraphs. The size of these graphs are so huge that they are unable to be processed by current technologies. The graphs require new and innovative methods of processing and visualizing. Graph surfaces of hierarchical graph slices have been suggested as a way of representing massive digraphs. In this chapter an approach is presented which involves encoding Lipschitz functions into monotone k-logic functions using symmetric chain decompositions (SCD). This approach proposes to address some of the issues concerning huge graphs by providing memory minimization techniques that can be applied to storing graph surfaces.

An approach is investigated to identify an invariant in a simulated robot soccer team’s dynamics in order to characterize the teams’ global behaviour. The invariant is being studied with the view of using fuzzy logic as a possible means for developing intelligent strategies in robot soccer. A conjecture by Korotkich that the eigenvalue spectrum of matrices associated with the dynamics of a robot soccer team is a solid invariant that may serve as a global characteristic was tested. This required setting up a virtual simulation and computation laboratory. This laboratory had to be developed ‘from scratch’ as this approach has never been applied to understanding robot soccer team dynamics before in the world. It is analogous to the approach physicists take when searching for a theoretical particle. The many tools that have been established through this research will be used together with fuzzy logic principles to develop winning team strategies.

An approach is investigated to identify an invariant in the team's behavior in order to characterize the global behavior of a robot soccer team. The existence of such an invariant confirmed by computational evidence is reported in this paper. The invariant is being studied with the view of using it as a possible means for developing intelligent strategies in robot soccer. ...