Project

Back to overview

Design of trials for pathogen elimination

English title Design of trials for pathogen elimination
Applicant Smith Thomas
Number 162837
Funding scheme Project funding (Div. I-III)
Research institution Swiss Tropical and Public Health Institute Medical Services and Diagnostic Universität Basel
Institution of higher education University of Basel - BS
Main discipline Medical Statistics
Start/End 01.01.2016 - 31.12.2019
Approved amount 331'408.00
Show all

All Disciplines (2)

Discipline
Medical Statistics
Infectious Diseases

Keywords (4)

elimination; cluster randomization; malaria; Stepped-wedge design

Lay Summary (German)

Lead
Zur Zeit besteht grosses Interesse an der Eliminierung von Infektionskrankheiten, die durch Mücken oder andere Arthropoden übertragen werden. Beim Testen von Technologien zur Eliminierung solcher Krankheiten muss der Mobilität der Überträger Rechnung getragen werden, was Folgen für Design und Analyse der Studien hat. In dieser Studie werden neue statistische Methoden entwickelt und auf Versuche zu Vektorkontrolle bei Malaria in Afrika angewandt.
Lay summary

In Studien zu medizinischen Verfahren und Technologien können Spill-over-Effekte auf Nachbarn entstehen, insbesondere bei Infektionen. Solche Interventionen werden in clusterrandomisierten Studien getestet, in welchen die Intervention in Gruppen von Personen durchgeführt wird und andere Gruppen als Kontrollgruppen fungieren.

Bei manchen Interventionen ist es entscheidend, dass sie flächendeckend angewandt werden, vor allem, wenn eine Krankheit ganz eliminiert werden soll. Gängige Studiendesigns sagen jedoch nichts über die Folgen flächendeckender Interventionen aus. Eine Möglichkeit flächendeckende Interventionen zu testen besteht darin, die Intervention bei allen Teilnehmern in zufälliger Reihenfolge anzuwenden (Stepped-Wedge-Design).

Spill-over-Effekte erschweren die Auswertung und werden deshalb oft vermieden. Bei der Eliminierung einer Krankheit können Spill-over jedoch ein wichtiger Bestandteil des Gesamteffekts sein und müssen deshalb integriert werden, wenn die Resultate verallgemeinderbar sein sollen.

In diesem Projekt werden mit Hilfe von Daten zu partieller Abdeckung und Spill-over-Effekten Methoden zur Optimierung von Design und Auswertung von Stepped-Wedge Studien entwickelt. Wird in einem Versuch keine vollständige Eliminierung erreicht, so kann mit diesen Methoden ermittelt werden, wie weit der Versuch von einer vollständigen Eliminierung entfernt war. Bei einer erfolgreichen Eliminierung kann festgestellt werden, ob diese zufällig stattgefunden hat, oder ob die Interventionen im Übermass angewandt wurden. Zudem können die Folgen einer partiellen Abdeckung eingeschätzt werden.

Wir werden die entwickelten Methoden verwenden um zwei Feldstudien zur Vektorkontrolle bei Malaria zu untersuchen und zwar (i) die „Solar Power for Malaria Control“ (SolarMal) Studie zur Anwendung von Moskitofallen mit Geruchsködern auf der Insel Rusinga, Lake Victoria Kenya und (ii) die AvecNet Studie zu mit künstlichen Juvenilhormon behandelten Moskitonetzen in Burkina Faso.

Direct link to Lay Summary Last update: 26.10.2015

Lay Summary (English)

Lead
There is currently much interest in eliminating infectious diseases transmitted by mosquitoes or other arthropods. Designs of trials for testing methods for achieving this, need to be adapted to allow for the movement of the disease vectors, which have implications both for the design and analysis. This study will develop relevant statistical methods and apply them to trials of vector control interventions against malaria in Africa.
Lay summary

In randomised controlled trials of health technologies, effects can spill-over from the people receiving them to their neighbours, in particular when the interventions kill mosquitoes, or other animals that transmit disease.  Such interventions are tested via cluster-randomised trials, in which groups of people are all intervened together; other groups of people act as controls.

Sometimes blanket coverage is important, especially if the objective is to eliminate the disease entirely, but standard designs do not say what would happen with universal coverage. One test of universal coverage is to introduce the new intervention to everyone but in a random order.  This is called a stepped wedge trial.

Spill-over benefits complicate analysis and trials usually try to avoid them, but in an elimination trial spill-over can be an important part of the overall effect, and needs to be understood if the results are to be generalized. Introducing interventions in random order provides information about the effect of partial coverage, even if universal coverage is the objective, but this raises new statistical issues. 

This project will develop methods for optimizing the design and analysis of such stepped wedge trials, making use of data about partial coverage and spill-over effects.  If a trial is unsuccessful in achieving elimination, these methods will make it possible to infer how close it came to success.  If the trial is successful, we will be able to assess whether this was fortuitous, or if an overkill was achieved.  We will also be able to use the results to work out the effects of imperfect intervention coverage.

We will use the new methods to analyse two field trials of vector control against malaria, (i) the Solar Power for Malaria Control (SolarMal) trial of the use of odour-baited mosquito traps on Rusinga Island, Lake Victoria, Kenya, and (ii) the AvecNet trial of treating mosquito nets with pyriproxyfen (an insect juvenile hormone mimic) in Burkina Faso.

 
Direct link to Lay Summary Last update: 26.10.2015

Responsible applicant and co-applicants

Employees

Publications

Publication
Modeling the impact of sterile males on an Aedes aegypti population with optimal control
Multerer Lea, Smith Thomas, Chitnis Nakul (2019), Modeling the impact of sterile males on an Aedes aegypti population with optimal control, in Mathematical Biosciences, 311, 91-102.
Spatial Effects of Permethrin-Impregnated Bed Nets on Child Mortality: 26 Years on, a Spatial Reanalysis of a Cluster Randomized Trial.
CI Jarvis, L Multerer, D Lewis, F Binka, WJ Edmunds, N Alexander, TA Smith (2019), Spatial Effects of Permethrin-Impregnated Bed Nets on Child Mortality: 26 Years on, a Spatial Reanalysis of a Cluster Randomized Trial., in The American journal of tropical medicine and hygiene, 101 (6), 1434-1441.
Efficacy of Olyset Duo, a bednet containing pyriproxyfen and permethrin, versus a permethrin-only net against clinical malaria in an area with highly pyrethroid-resistant vectors in rural Burkina Faso: a cluster-randomised controlled trial
Tiono Alfred B, Ouédraogo Alphonse, Ouattara Daouda, Bougouma Edith C, Coulibaly Sam, Diarra Amidou, Faragher Brian, Guelbeogo Moussa W, Grisales Nelson, Ouédraogo Issa N, Ouédraogo Zininwindé Amidou, Pinder Margaret, Sanon Souleymane, Smith Tom, Vanobberghen Fiona, Sagnon N'Fale, Ranson Hilary, Lindsay Steve W (2018), Efficacy of Olyset Duo, a bednet containing pyriproxyfen and permethrin, versus a permethrin-only net against clinical malaria in an area with highly pyrethroid-resistant vectors in rural Burkina Faso: a cluster-randomised controlled trial, in The Lancet, 392(10147), 569-580.
Simulations for designing and interpreting intervention trials in infectious diseases
Halloran M. Elizabeth, Auranen Kari, Baird Sarah, Basta Nicole E., Bellan Steven E., Brookmeyer Ron, Cooper Ben S., DeGruttola Victor, Hughes James P., Lessler Justin, Lofgren Eric T., Longini Ira M., Onnela Jukka-Pekka, Özler Berk, Seage George R., Smith Thomas A., Vespignani Alessandro, Vynnycky Emilia, Lipsitch Marc (2017), Simulations for designing and interpreting intervention trials in infectious diseases, in BMC Medicine, 15(1), 223-223.

Collaboration

Group / person Country
Types of collaboration
London School of Hygiene and Tropical Medicine Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Center for Statistics and Quantitative Infectious Diseases, University of Washington United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Malaria Modelling Consortium meeting on vector control modeling Talk given at a conference Analysis of cluster randomised trials allowing for mosquito movement 15.01.2019 Basel, Switzerland Smith Thomas;
Simulating Intervention Trials in Infectious Diseases Talk given at a conference Simulating a stepped wedge trial of odour-baited traps against malaria vectors 24.08.2016 University of Washington, Seattle, United States of America Smith Thomas;


Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
9th Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID) Workshop 10.07.2017 University of Washington, Seattle, United States of America Multerer Lea;


Associated projects

Number Title Start Funding scheme
105994 Predicting efficacy and cost-effectiveness of malaria control interventions in Africa using dynamic models 01.10.2004 Project funding (Div. I-III)

Abstract

Cluster-randomized trials (CRTs) are used to evaluate health interventions that have effects at the community level. In such trials, the effects of the intervention may spill-over into adjacent areas of control clusters leading to contamination effects. Trials of interventions against infectious diseases increasingly aim to evaluate the potential to interrupt pathogen transmission at maximum scale-up. To achieve this, there is a need for stepped-wedge designs. In stepped-wedge cluster-randomised trials (SWCRTs), assignment of clusters to the intervention, and hence the contamination effects, are time dependent. Established statistical methods seek to minimize effects of contamination, and hence neither measure it, nor exploit the information that it provides. Rather than aiming to avoid contamination, we propose that contamination effects may provide valuable evidence about the intervention effectiveness. Contamination, assessed via sub-cluster spatial variation in outcomes and patterns of outcomes across cluster boundaries, should be both measured as a trial outcome and used to make inferences about the properties of the intervention when deployed in non-trial settings. However, while intervention assignment in such trials is randomly assigned, spatial configuration is not. Measures of the contamination effect therefore depend jointly on factors over which trial participants are randomized and factors where randomization plays no role, and this raises novel issues in causal inference. This project will develop the required statistical methods for allowing for contamination in trial design, for analyzing the extent of contamination and using this for causal inference, and generalization of intervention impacts to non-trial settings. This methodological development will entail deriving:1.Point and interval estimates of the extent of contamination in CRTs and SWCRTs based on measuring gradients in outcomes across boundaries between trial arms. Some trials have assessed these gradients but without accounting for the correlation structure of the data. There is a need for practicable analytical approaches that account for this correlation structure in both estimating the gradient, and in estimating power to test if the gradient is non-zero. 2.Algorithm(s) for optimising cluster size and randomization strategies for CRTs and SWCRTs in the presence of contamination. These will be based both on considerations of statistical power of outcome measures, including measures of contamination effect, and in the case of SWCRTs, of how the evidence for causality is influenced by stratification in the trial randomization. The novel analytical approaches will be applied to two field trials of vector control interventions against malaria, (i) the Solar Power for Malaria Control (SolarMal) trial of the use of odour-baited mosquito traps to eliminate Plasmodium falciparum malaria from Rusinga Island, Lake Victoria, Kenya, and (ii) the AvecNet trial which is assessing the impact of treating mosquito nets with pyriproxyfen (an insect juvenile hormone mimic) in an area of rural Burkina Faso. Methods will be developed for generalising these trial results to settings where the interventions are implemented with different patterns of transmission and of intervention coverage from those in the trials. In particular, the estimates of contamination effects in SWCRTs will be used in parameterising mathematical models for predicting the impact of these interventions on unmeasured outcomes (such as mortality) over longer timelines than those in the trials.
-