Malaria vaccines: lessons from field trials

Measuring the efficacy of a vaccine during an epidemic

The urgency to develop vaccines during the COVID-19 pandemic has resulted in the acceleration of clinical trials. Specifically, a broad spectrum of efficacy levels has been reported for various vaccines based on phase III cohort studies. Our study demonstrates that conducting large cohort phase III clinical trials during the peak of an epidemic leads to a significant underestimation of vaccine efficacy, even in the absence of confounding factors. Furthermore, we find that this underestimation increases with the proportion of infectious individuals in the population during the experiment and the severity of the epidemic, as measured by its basic reproduction number.

Time-dependent vaccine efficacy estimation quantified by a mathematical model

In this paper we calculate the variation of the estimated vaccine efficacy (VE) due to the time-dependent force of infection resulting from the difference between the moment the Clinical Trial (CT) begins and the peak in the outbreak intensity. Using a simple mathematical model we tested the hypothesis that the time difference between the moment the CT begins and the peak in the outbreak intensity determines substantially different values for VE. We exemplify the method with the case of the VE efficacy estimation for one of the vaccines against the new coronavirus SARS-CoV-2.

Challenges of evaluating and modelling vaccination in emerging infectious diseases

Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.

Simulations for designing and interpreting intervention trials in infectious diseases

BACKGROUND

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods.

DISCUSSION

Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects.

CONCLUSION

Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

Estimating strain-specific and overall efficacy of polyvalent vaccines against recurrent pathogens from a cross-sectional study

Evaluating vaccine efficacy for protection against colonization with bacterial pathogens is an area of growing interest. Colonization of the nasopharynx is an asymptomatic carrier state responsible for person-to-person transmission. It differs from most clinical outcomes in that it is common, recurrent, and observed only in its prevalent state. To estimate rates of acquisition and clearance of colonization requires repeated active sampling of the same individuals over time, an expensive and invasive undertaking. Motivated by feasibility constraints in efficacy trials with colonization endpoints, investigators have been estimating vaccine efficacy from cross-sectional studies without principled methods. We present two examples of vaccine studies estimating vaccine efficacy from cross-sectional data on nasopharyngeal colonization by Streptococcus pneumoniae (pneumococcus). This study presents a framework for defining and estimating strain-specific and overall vaccine efficacy for susceptibility to acquisition of colonization (VE(acq)) when there is a large number of strains with mutual interactions and recurrent dynamics of colonization. We develop estimators based on one observation of the current status per study subject, evaluate their robustness, and re-analyze the two vaccine trials. Methodologically, the proposed estimators are closely related to case-control studies with prevalent cases, with appropriate consideration of the at-risk time in choosing the controls.

Estimation of vaccine efficacy in a repeated measures study under heterogeneity of exposure or susceptibility to infection

Vaccine efficacy (VE) is commonly estimated through proportional hazards modelling of the time to first infection or disease, even when the event of interest can recur. These methods can result in biased estimates when VE is heterogeneous across levels of exposure and susceptibility in subjects. These two factors are important sources of unmeasured heterogeneity, since they vary within and across areas, and often cannot be individually quantified. We propose an estimator of VE per exposure that accounts for heterogeneous susceptibility and exposure for a repeated measures study with binary recurrent outcomes. The estimator requires only information about the probability distribution of environmental exposures. Through simulation studies, we compare the properties of this estimator with proportional hazards estimation under the heterogeneity of exposure. The methods are applied to a reanalysis of a malaria vaccine trial in Brazil.

Targeted screening strategies to detect Trypanosoma cruzi infection in children

BACKGROUND

Millions of people are infected with Trypanosoma cruzi, the causative agent of Chagas disease in Latin America. Anti-trypanosomal drug therapy can cure infected individuals, but treatment efficacy is highest early in infection. Vector control campaigns disrupt transmission of T. cruzi, but without timely diagnosis, children infected prior to vector control often miss the window of opportunity for effective chemotherapy.

METHODS AND FINDINGS

We performed a serological survey in children 2-18 years old living in a peri-urban community of Arequipa, Peru, and linked the results to entomologic, spatial and census data gathered during a vector control campaign. 23 of 433 (5.3% [95% CI 3.4-7.9]) children were confirmed seropositive for T. cruzi infection by two methods. Spatial analysis revealed that households with infected children were very tightly clustered within looser clusters of households with parasite-infected vectors. Bayesian hierarchical mixed models, which controlled for clustering of infection, showed that a child's risk of being seropositive increased by 20% per year of age and 4% per vector captured within the child's house. Receiver operator characteristic (ROC) plots of best-fit models suggest that more than 83% of infected children could be identified while testing only 22% of eligible children.

CONCLUSIONS

We found evidence of spatially-focal vector-borne T. cruzi transmission in peri-urban Arequipa. Ongoing vector control campaigns, in addition to preventing further parasite transmission, facilitate the collection of data essential to identifying children at high risk of T. cruzi infection. Targeted screening strategies could make integration of diagnosis and treatment of children into Chagas disease control programs feasible in lower-resource settings.

Randomization and baseline transmission in vaccine field trials

In randomized trials, the treatment assignment mechanism is independent of the outcome of interest and other covariates thought to be relevant in determining this outcome. It also allows, on average, for a balanced distribution of these covariates in the vaccine and placebo groups. Randomization, however, does not guarantee that the estimated effect is an unbiased estimate of the biological effect of interest. We show how exposure to infection can be a confounder even in randomized vaccine field trials. Based on a simple model of the biological efficacy of interest, we extend the arguments on comparability and collapsibility to examine the limits of randomization to control for unmeasured covariates. Estimates from randomized, placebo-controlled Phase III vaccine field trials that differ in baseline transmission are not comparable unless explicit control for baseline transmission is taken into account.

Overview of Vaccine Field Studies: Types of Effects and Designs

Vaccination produces many different types of effects in individuals and in populations. The scientific and public health questions of interest determine the choice of measures of effect and study designs. Here we review some of the various measures and study designs for evaluating different effects of vaccination.

SPf66 vaccine trial in Brazil: conceptual framework study design and analytical approach

This paper describes the study population and the study design of the phase III field trail of the SPf66 vaccine in Brazil. Assessment of validity and precision principles necessary for the appropriate evaluation of the protective effect of the vaccine are discussed, as well as the results of the preliminary analyses of the gathered data. The analytical approach for the estimation of the protective effect of the vaccine is presented. This paper provides the conceptual framework for future publications.