Extended Follow-Up Following a Phase 2b Randomized Trial of the Candidate Malaria Vaccines FP9 ME-TRAP and MVA ME-TRAP among Children in Kenya

Background. "FFM ME-TRAP'' is sequential immunisation with two attenuated poxvirus vectors (FP9 and modified vaccinia virus Ankara) delivering the pre-erythrocytic malaria antigen ME-TRAP. Over nine months follow-up in our original study, there was no evidence that FFM ME-TRAP provided protection against malaria. The incidence of malaria was slightly higher in children who received FFM ME-TRAP, but this was not statistically significant (hazard ratio 1.5, 95% CI 1.0-2.3). Although the study was unblinded, another nine months follow-up was planned to monitor the incidence of malaria and other serious adverse events. Methods and Findings. 405 children aged 1-6 yrs were initially randomized to vaccination with either FFM ME-TRAP or control (rabies vaccine). 380 children were still available for follow-up after the first nine months. Children were seen weekly and whenever they were unwell for nine months monitoring. The axillary temperature was measured, and blood films taken when febrile. The primary analysis was time to parasitaemia >2,500/mu l. During the second nine months monitoring, 49 events met the primary endpoint (febrile malaria with parasites >2,500/mu l) in the Intention To Treat (ITT) group. 23 events occurred among the 189 children in the FFM ME-TRAP group, and 26 among the 194 children in the control group. In the full 18 months of monitoring, there were 63 events in the FFM ME-TRAP group and 60 in the control group (HR = 1.2, CI 0.84-1.73, p = 0.35). There was no evidence that the HR changed over the 18 months (test for interaction between time and vaccination p = 0.11). Conclusions. Vaccination with FFM ME-TRAP was not protective against malaria in this study. Malaria incidence during 18 months of surveillance was similar in both vaccine groups. Trial Registration. Controlled-Trials. com ISRCTN88335123

Reliable enumeration of malaria parasites in thick blood films using digital image analysis

<p>Abstract</p> <p>Background</p> <p>Quantitation of malaria parasite density is an important component of laboratory diagnosis of malaria. Microscopy of Giemsa-stained thick blood films is the conventional method for parasite enumeration. Accurate and reproducible parasite counts are difficult to achieve, because of inherent technical limitations and human inconsistency. Inaccurate parasite density estimation may have adverse clinical and therapeutic implications for patients, and for endpoints of clinical trials of anti-malarial vaccines or drugs. Digital image analysis provides an opportunity to improve performance of parasite density quantitation.</p> <p>Methods</p> <p>Accurate manual parasite counts were done on 497 images of a range of thick blood films with varying densities of malaria parasites, to establish a uniformly reliable standard against which to assess the digital technique. By utilizing descriptive statistical parameters of parasite size frequency distributions, particle counting algorithms of the digital image analysis programme were semi-automatically adapted to variations in parasite size, shape and staining characteristics, to produce optimum signal/noise ratios.</p> <p>Results</p> <p>A reliable counting process was developed that requires no operator decisions that might bias the outcome. Digital counts were highly correlated with manual counts for medium to high parasite densities, and slightly less well correlated with conventional counts. At low densities (fewer than 6 parasites per analysed image) signal/noise ratios were compromised and correlation between digital and manual counts was poor. Conventional counts were consistently lower than both digital and manual counts.</p> <p>Conclusion</p> <p>Using open-access software and avoiding custom programming or any special operator intervention, accurate digital counts were obtained, particularly at high parasite densities that are difficult to count conventionally. The technique is potentially useful for laboratories that routinely perform malaria parasite enumeration. The requirements of a digital microscope camera, personal computer and good quality staining of slides are potentially reasonably easy to meet.</p

Seven-Year Efficacy of RTS,S/AS01 Malaria Vaccine among Young African Children

Background The RTS,S/AS01 malaria vaccine candidate is being evaluated for implementation. Methods We conducted 7 years follow-up of children who were randomized at age 5 to 17 months to receive three doses of either the RTS,S/AS01 vaccine or control vaccine (rabies). The endpoint was clinical malaria (temperature ≥37.5°C and infection with Plasmodium falciparum of ≥2500 parasites per µl). Each child’s malaria exposure was estimated using the prevalence of malaria among residents within a 2km radius of their homestead. Vaccine efficacy was defined as 1 minus the hazard ratio (HR) or incidence rate ratios (IRR) of the RTS,S/AS01 vaccinated versus rabies vaccinated groups. Results We identified 1002 clinical malaria episodes among 223 children randomized to RTS,S/AS01 and 992 clinical malaria episodes among 224 children randomized to control vaccination over seven years follow-up. Intention-to-treat vaccine efficacy (VE) was 4.4% (95%CI: -17 to 21.9, p value=0.67) and per-protocol VE was 7.0% (95%CI -14.5 to 24.6%, p=0.5) by negative binomial regression. VE waned over time (p=0.006 for the interaction between vaccination and time), including negative efficacy during the fifth year among children at higher malaria parasite exposure (-43.5%, 95%CI: -100.3 to -2.8, p value=0.033 by intention-to-treat and -56.8%, 95%CI -118.7 to -12.3, p=0.008 per-protocol). Conclusion A 3-dose vaccination with RTS,S/AS01 is initially protective against clinical malaria, but this is offset by rebound in later years in areas with higher malaria parasite exposure. Further data are needed on longer-term outcomes following four-dose vaccinations. </p

Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field

BACKGROUND: Heterogeneity in malaria exposure complicates survival analyses of vaccine efficacy trials and confounds the association between immune correlates of 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 malaria hotspots for 2,425 individuals. Antibody levels to the malaria antigens AMA1 and MSP1(142) 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 MSP1(142) antibodies levels were independently associated with malaria infection. Weighted local malaria prevalence had an area under ROC curve of 0.72 (95%CI: 0.66-0.73), 0.71 (95%CI: 0.69-0.73) and 0.82 (95%CI: 0.80-0.83) 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 MSP1(142) antibody levels provided an AUC of 0.83 (95%CI: 0.79-0.88). 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

An unsupported preference for intravenous antibiotics

Antibiotics that are well absorbed after oral administration are available, and the best current evidence suggests they are safe and effective for many conditions. Belief in the superiority of intravenous antibiotics is widespread among health professionals and patients, but it is not supported by good evidence. Expanding the evidence base will provide patients and clinicians with further reassurance in specific situations, but reasons for the belief in the strength of intravenous therapy also need to be understood and addressed. Trials expanding the evidence base might follow noninferiority designs, based on the precedent of widespread intravenous use. For many indications, the theoretical reasons for preferring intravenous therapy are not strong, and the risks of intravenous therapy are well established. It would be more logical for many indications to regard oral antibiotics as the default position and require trial designs to test the superiority of intravenous therapy. Clarity regarding the harms and benefits of intravenous antibiotics is needed. There is potential to change global clinical practice for the better, reducing health care costs and minimizing harm to patients

Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya

Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.5 km (95% CI 0.3-1.5), for a distribution with 68% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes

Effect of strikes by health workers on mortality between 2010 and 2016 in Kilifi, Kenya: a population-based cohort analysis

BACKGROUND: Health workers' strikes are a global occurrence. Kenya has had several strikes by health workers in recent years but their effect on mortality is unknown. We assessed the effect on mortality of six strikes by health workers that occurred from 2010 to 2016 in Kilifi, Kenya. METHODS: Using daily mortality data obtained from the Kilifi Health and Demographic Surveillance System, we fitted a negative binomial regression model to estimate the change in mortality during strike periods and in the 2 weeks immediately after strikes. We did subgroup analyses by age, cause of death, and strike week. FINDINGS: Between Jan 1, 2010, and Nov 30, 2016, we recorded 1 829 929 person-years of observation, 6396 deaths, and 128 strike days (median duration of strikes, 18·5 days [range 9-42]). In the primary analysis, no change in all-cause mortality was noted during strike periods (adjusted rate ratio [RR] 0·93, 95% CI 0·81-1·08; p=0·34). Weak evidence was recorded of variation in mortality rates by age group, with an apparent decrease among infants aged 1-11 months (adjusted RR 0·58, 95% CI 0·33-1·03; p=0·064) and an increase among children aged 12-59 months (1·75, 1·11-2·76; p=0·016). No change was noted in mortality rates in post-strike periods and for any category of cause of death. INTERPRETATION: The brief strikes by health workers during the period 2010-16 were not associated with obvious changes in overall mortality in Kilifi. The combined effects of private (and some public) health care during strike periods, a high proportion of out-of-hospital deaths, and a low number of events might have led us to underestimate the effect. FUNDING: Wellcome Trust and MRC Tropical Epidemiology Group