The aim was to minimize the magnitude of bias for the estimates of local malaria prevalence on the risk of malaria infection. To evaluate the discriminatory ability of weighted Betulin local malaria prevalence and log transformed AMA1 and MSP1 antibody levels for malaria infection in the index child the area under the receiver operating characteristic (ROC) curve was determined . A represents the causal diagram for the data Panel B represent causal diagram after 6 step DAG approach and if one conditions on Age, malaria hotspot, spatial transmission factors (distance from infected and uninfected children) and blood stage antibodies (dashed boxes). Dotted lines represent conditional associations.(TIFF) pone.0032929.s004.tif (578K) GUID:?87538CDA-7C7E-4585-9CD2-44384D333394 Table S1: Weighted local prevalence of malaria infection for four monthly follow-up data. Multivariable polynomial fraction showed age has a non linear effect in all the cohorts (see Figure S3).(DOC) Betulin pone.0032929.s005.doc (38K) GUID:?C825D527-65AB-41E1-8415-6BEDAE412B09 Abstract Background Heterogeneity in malaria exposure complicates survival analyses of vaccine efficacy trials and confounds the association between immune correlates of Betulin protection and malaria infection in longitudinal studies. Analysis may be facilitated by taking into account the variability in individual exposure levels, but it is unclear how exposure can be estimated at an individual level. Method and Findings We studied three cohorts (Chonyi, Junju and Ngerenya) in Kilifi District, Kenya to assess measures of malaria exposure. Prospective data were available on malaria episodes, geospatial coordinates, proximity to infected and uninfected individuals and residence in predefined JAM2 malaria hotspots for 2,425 individuals. Antibody levels to the malaria antigens AMA1 and MSP1142 were available for 291 children from Junju. We calculated distance-weighted local prevalence of malaria infection within 1 km radius as a marker of individual’s malaria exposure. We used multivariable modified Poisson regression model to assess the discriminatory power of these markers for malaria infection (i.e. asymptomatic parasitaemia or clinical malaria). The area under the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of the models. Local malaria prevalence within 1 km radius and AMA1 and MSP1142 antibodies levels were independently associated with malaria infection. Weighted local malaria prevalence had an area under ROC curve of 0.72 (95%CI: 0.66C0.73), 0.71 (95%CI: 0.69C0.73) and 0.82 (95%CI: 0.80C0.83) among cohorts in Chonyi, Junju and Ngerenya respectively. In a small subset of children from Junju, a model incorporating weighted local malaria prevalence with AMA1 and MSP1142 antibody levels provided an AUC of 0.83 (95%CI: 0.79C0.88). Conclusion We have proposed an approach to estimating the intensity of an individual’s malaria exposure in the field. The weighted local malaria prevalence can be used as individual marker of malaria exposure in malaria vaccine trials and longitudinal studies of natural immunity to malaria. Introduction Spatial heterogeneity in malaria exposure has been described at a micro-epidemiological level at varying transmission Betulin settings , . It is responsible for variations in disease risk within a small area and is evidenced by geographical clustering of malaria infections. Approximately 80% of transmission occurs within 20% of the population , . It has been attributed to factors such as varying ecologies of local malaria vectors, the pattern of contact between human host and vectors and intrinsic human host factors , . Heterogeneity in malaria exposure may bias estimates of malaria vaccine Betulin efficacy over time in longitudinal studies , . This is predicted by simulations of populations under heterogeneous malaria exposure, where vaccine efficacy is underestimated as a consequence of heterogeneity and apparent waning of efficacy over time is seen even if vaccine protection is maintained . Although a randomized controlled trial may ensure equal distributions of malaria exposure at the start of the trial, if the vaccine is protective then the more highly susceptible individuals will experience earlier clinical malaria episodes in the control group than in the active vaccination group. Their subsequent removal from the at risk set will subsequently unsettle the comparability of vaccinees and non-vaccinees and produce inaccurate estimates of efficacy , . This effect will become more marked as time since randomization increases. Furthermore vaccine efficacy may vary according to the intensity of exposure  and so estimating individual malaria exposure levels would allow.