BackgroundPlasmodium falciparum variant surface antigens (VSAs) contribute to malaria pathogenesis by mediating cytoadhesion of infected red blood cells to the microvasculature endothelium. In this study, we investigated the association between anti-VSA antibodies and clinical outcome in a controlled human malaria infection (CHMI) study.MethodWe used flow cytometry and ELISA to measure levels of IgG antibodies to VSAs of five heterologous and one homologous P. falciparum parasite isolates, and to two PfEMP1 DBLβ domains in blood samples collected a day before the challenge and 14 days after infection. We also measured the ability of an individual’s plasma to inhibit the interaction between PfEMP1 and ICAM1 using competition ELISA. We then assessed the association between the antibody levels, function, and CHMI defined clinical outcome during a 21-day follow-up period post infection using Cox proportional hazards regression.ResultsAntibody levels to the individual isolate VSAs, or to two ICAM1-binding DBLβ domains of PfEMP1, were not associated with a significantly reduced risk of developing parasitemia or of meeting treatment criteria after the challenge after adjusting for exposure. However, anti-VSA antibody breadth (i.e., cumulative response to all the isolates) was a significant predictor of reduced risk of requiring treatment [HR 0.23 (0.10-0.50) p= 0.0002].ConclusionThe breadth of IgG antibodies to VSAs, but not to individual isolate VSAs, is associated with protection in CHMI.

Background: Globally, malnutrition underlies 45% of under-5 s mortality, mainly from potentiating common infections such as diarrhoea and pneumonia. Malnutrition as a public health problem is not evenly disbursed because of disparities in food insecurity and health, and children commonly suffer recurrent episodes of opportunistic infections. We aimed to understand better the spatial and temporal structure of multiple paediatric hospital admissions associated with malnutrition-related illnesses. This paper aimed to investigate the spatialtemporal variations in malnutrition-related recurrent morbidity of children under-5 years from the Kilifi County in Kenya between 2002 and 2015. Methods: The study included data from children under-5 years old who had more than one admission to a rural district hospital in Kenya within the Kilifi Health and Demographic Surveillance System (KHDSS). The primary outcome was a malnutrition-related admission, based on wasting (WHZ <-2) or nutritional oedema. Individual, household and environmental level covariates were examined as exposures. We first fitted a SARIMA model for the temporality, and the Moran's Index affirmed spatial clustering in malnutrition admissions. Kulldorf Statistics using SaTScan were applied to detect hotspots. Then, bivariate analysis was done using repeated values tabulation and analysis of covariance (ANCOVA). Inferential analysis was done using a mixed effect multivariable negative-binomial regression model, adjusting for spatiotemporal random effects. Results: A total of 2821 children were admitted more than once, giving a total of 6375 admissions. Of these 6375 admissions, 1866 were malnutrition-related, and 3.9% (109/2821) of the children with repeat admissions died. There was a seasonal pattern of re-admissions, peaking from May to July over the years. Hotspots were found in both the Northern and Southern areas of the KHDSS, while the areas near Kilifi Town were least affected. We found that disease severity was most likely associated with a malnutrition re-admission to the hospital. Conclusion: Disease severity was strongly associated with admission with malnutrition but its effect reduced after adjusting for the spatial and temporal random effects. Adjusting for clustering in space and in time (spatialtemporal) in models helps to improve the understanding of recurrent hospitalisations involving malnutrition.

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