Malaria attributable fractions with changing transmission intensity: Bayesian latent class vs logistic models.

BACKGROUND: Asymptomatic carriage of malaria parasites is common in high transmission intensity areas and confounds clinical case definitions for research studies. This is important for investigations that aim to identify immune correlates of protection from clinical malaria. The proportion of fevers attributable to malaria parasites is widely used to define different thresholds of parasite density associated with febrile episodes. The varying intensity of malaria transmission was investigated to check whether it had a significant impact on the parasite density thresholds. The same dataset was used to explore an alternative statistical approach, using the probability of developing fevers as a choice over threshold cut-offs. The former has been reported to increase predictive power. METHODS: Data from children monitored longitudinally between 2005 and 2017 from Junju and Chonyi in Kilifi, Kenya were used. Performance comparison of Bayesian-latent class and logistic power models in estimating malaria attributable fractions and probabilities of having fever given a parasite density with changing malaria transmission intensity was done using Junju cohort. Zero-inflated beta regressions were used to assess the impact of using probabilities to evaluate anti-merozoite antibodies as correlates of protection, compared with multilevel binary regression using data from Chonyi and Junju. RESULTS: Malaria transmission intensity declined from over 49% to 5% between 2006 and 2017, respectively. During this period, malaria attributable fraction varied between 27-59% using logistic regression compared to 10-36% with the Bayesian latent class approach. Both models estimated similar patterns of fevers attributable to malaria with changing transmission intensities. The Bayesian latent class model performed well in estimating the probabilities of having fever, while the latter was efficient in determining the parasite density threshold. However, compared to the logistic power model, the Bayesian algorithm yielded lower estimates for both attributable fractions and probabilities of fever. In modelling the association of merozoite antibodies and clinical malaria, both approaches resulted in comparable estimates, but the utilization of probabilities had a better statistical fit. CONCLUSIONS: Malaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.

protGear: A protein microarray data pre-processing suite.

Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data. Published guidelines to limit technical variability whilst maintaining important biological variation favour DNA-based microarrays that often differ fundamentally in their experimental design. Rigorous tools to guide background correction, the quantification of within-sample variation, normalisation, and batch correction specifically for protein microarrays are limited, require extensive investigation and are not centrally accessible. Here, we develop a generic one-stop-shop pre-processing suite for protein microarrays that is compatible with data from the major protein microarray scanners. Our graphical and tabular interfaces facilitate a detailed inspection of data and are coupled with supporting guidelines that enable users to select the most appropriate algorithms to systematically address bias arising in customized experiments. The localization and distribution of background signal intensities determine the optimal correction strategy. A novel function overcomes the limitations in the interpretation of the coefficient of variation when signal intensities are at the lower end of the detection threshold. We demonstrate essential considerations in the experimental design and their impact on a range of algorithms for normalization and minimization of batch effects. Our user-friendly interactive web-based platform eliminates the need for prowess in programming. The open-source R interface includes illustrative examples, generates an auditable record, enables reproducibility, and can incorporate additional custom scripts through its online repository. This versatility will enhance its broad uptake in the infectious disease and vaccine development community.

KILchip v1.0: A Novel Plasmodium falciparum Merozoite Protein Microarray to Facilitate Malaria Vaccine Candidate Prioritization.

Passive transfer studies in humans clearly demonstrated the protective role of IgG antibodies against malaria. Identifying the precise parasite antigens that mediate immunity is essential for vaccine design, but has proved difficult. Completion of the Plasmodium falciparum genome revealed thousands of potential vaccine candidates, but a significant bottleneck remains in their validation and prioritization for further evaluation in clinical trials. Focusing initially on the Plasmodium falciparum merozoite proteome, we used peer-reviewed publications, multiple proteomic and bioinformatic approaches, to select and prioritize potential immune targets. We expressed 109 P. falciparum recombinant proteins, the majority of which were obtained using a mammalian expression system that has been shown to produce biologically functional extracellular proteins, and used them to create KILchip v1.0: a novel protein microarray to facilitate high-throughput multiplexed antibody detection from individual samples. The microarray assay was highly specific; antibodies against P. falciparum proteins were detected exclusively in sera from malaria-exposed but not malaria-naïve individuals. The intensity of antibody reactivity varied as expected from strong to weak across well-studied antigens such as AMA1 and RH5 (Kruskal-Wallis H test for trend: p < 0.0001). The inter-assay and intra-assay variability was minimal, with reproducible results obtained in re-assays using the same chip over a duration of 3 months. Antibodies quantified using the multiplexed format in KILchip v1.0 were highly correlated with those measured in the gold-standard monoplex ELISA [median (range) Spearman's R of 0.84 (0.65-0.95)]. KILchip v1.0 is a robust, scalable and adaptable protein microarray that has broad applicability to studies of naturally acquired immunity against malaria by providing a standardized tool for the detection of antibody correlates of protection. It will facilitate rapid high-throughput validation and prioritization of potential Plasmodium falciparum merozoite-stage antigens paving the way for urgently needed clinical trials for the next generation of malaria vaccines.

Risk of Injection-Site Abscess among Infants Receiving a Preservative-Free, Two-Dose Vial Formulation of Pneumococcal Conjugate Vaccine in Kenya.

There is a theoretical risk of adverse events following immunization with a preservative-free, 2-dose vial formulation of 10-valent-pneumococcal conjugate vaccine (PCV10). We set out to measure this risk. Four population-based surveillance sites in Kenya (total annual birth cohort of 11,500 infants) were used to conduct a 2-year post-introduction vaccine safety study of PCV10. Injection-site abscesses occurring within 7 days following vaccine administration were clinically diagnosed in all study sites (passive facility-based surveillance) and, also, detected by caregiver-reported symptoms of swelling plus discharge in two sites (active household-based surveillance). Abscess risk was expressed as the number of abscesses per 100,000 injections and was compared for the second vs first vial dose of PCV10 and for PCV10 vs pentavalent vaccine (comparator). A total of 58,288 PCV10 injections were recorded, including 24,054 and 19,702 identified as first and second vial doses, respectively (14,532 unknown vial dose). The risk ratio for abscess following injection with the second (41 per 100,000) vs first (33 per 100,000) vial dose of PCV10 was 1.22 (95% confidence interval [CI] 0.37-4.06). The comparator vaccine was changed from a 2-dose to 10-dose presentation midway through the study. The matched odds ratios for abscess following PCV10 were 1.00 (95% CI 0.12-8.56) and 0.27 (95% CI 0.14-0.54) when compared to the 2-dose and 10-dose pentavalent vaccine presentations, respectively. In Kenya immunization with PCV10 was not associated with an increased risk of injection site abscess, providing confidence that the vaccine may be safely used in Africa. The relatively higher risk of abscess following the 10-dose presentation of pentavalent vaccine merits further study.

Use of participatory, action and research methods in enhancing awareness of mental disorders in Kariobangi, Kenya.

Worldwide, mental disorders affect 450 million people and account for 15% of the overall burden of diseases from all causes (World Health Organization, 2001). Two-thirds of those affected do not receive adequate care owing to stigma, discrimination, neglect and poverty. The World Health Organization (2001) found that only 1% of the total health expenditure went to mental health in most countries.