HS#2017-3512, Adaptive Interventions for Optimizing Malaria Control: A Cluster-Randomized SMART Trial

June 29, 2021 updated by: University of California, Irvine

Environmental Modifications in Sub-Saharan Africa: Changing Epidemiology, Transmission and Pathogenesis of Plasmodium Falciparum and P. Vivax Malaria

In the past decade, massive scale-up of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) have led to significant reductions in malaria mortality and morbidity. Nonetheless, malaria burden remains high, and a dozen countries in Africa show a trend of increasing malaria incidence over the past several years. The high malaria burden in many areas of Africa underscores the need to improve the effectiveness of intervention tools by optimizing first-line intervention tools and integrating newly approved products into control programs. Vector control is an important component of the national malaria control strategy in Africa. Because transmission settings and vector ecologies vary among countries or among districts within a country, interventions that work in one setting may not work well in all settings. Malaria interventions should be adapted and re-adapted over time in response to evolving malaria risks and changing vector ecology and behavior. The central objective of this application is to design optimal adaptive combinations of vector control interventions to maximize reductions in malaria burden based on local malaria transmission risks, changing vector ecology, and available mix of interventions approved by the Ministry of Health in each target country. The central hypothesis is that an adaptive approach based on local malaria risk and changing vector ecology will lead to significant reductions in malaria incidence and transmission risk. The aim of this study is to use a cluster-randomized sequential, multiple assignment randomized trial (SMART) design to compare various vector control methods implemented by the Ministry of Health of Kenya in reducing malaria incidence and infection, and develop an optimal intervention strategy tailored toward to local epidemiological and vector conditions.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

In the past decade, massive scale-up of long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS) in Africa have led to significant reductions in malaria mortality and mobility. However, current first-line interventions are not sufficient to eliminate malaria in most countries. The widespread use of pyrethroid insecticides has resulted in resistant vector populations, and high coverage of LLINs and IRS has led to increased outdoor human feeding behavior and resting behavior. These changes in vector ecology and behaviors have significantly limited the effectiveness of current first-line interventions that target indoor biting and resting mosquitoes. Furthermore, as a result of ecological changes and intervention measures, malaria risk in a locality is dynamic, and the utility of malaria intervention tools may vary as new tools are being approved and introduced and the cost of each tool differs among locations and over time. Such variations in malaria risk, vector ecology, and utility of intervention tools exemplify the need to develop optimal adaptive interventions tailored to local malaria risks, vector ecology and supply chains. The central objective of this application is to design optimal adaptive combinations of vector control interventions to maximize reductions in malaria burden based on local malaria transmission risks, changing vector ecology, and available mix of interventions approved by the Ministry of Health in each target country. The central hypothesis is that an adaptive approach based on local malaria risk and changing vector ecology will lead to significant reductions in malaria incidence and transmission risk. To accomplish this objective, we propose the following three specific aims:

  1. Measure malaria incidence and predict risk using environmental, biological, social, and climatic features with machine learning approaches. Hypothesis: Malaria risk prediction can be improved through the use of machine learning techniques that include environmental, biological, socio-economic, and climatic features. Approach: Each site will measure malaria incidence, prevalence and social economic factors through community surveys. Classification-based and regression-based approaches will be used to develop malaria risk predictive models, and model performance will be validated. Outcome: This Aim will establish improved malaria risk prediction models and lay an important foundation for developing intervention strategies adaptive to local vector ecology and future malaria risks using reinforced machine learning approaches.
  2. Use a cluster-randomized sequential, multiple assignment randomized trial (SMART) design to develop an optimal adaptive intervention strategy. Hypothesis: Malaria control interventions that are adapted to local malaria risk and vector ecology and are cost effective can be identified using a cluster-randomized SMART design. Approach: Cluster-randomized SMART design will be used in a high transmission areas in Kenya to evaluate the impact of adaptive interventions that involve sequential and combinational use of next-generation nets, indoor spraying of non-pyrethroid insecticides, and larval source management for malaria control.
  3. Evaluate the cost-effectiveness and impact of an adaptive intervention approach on secondary endpoints related to malaria risk and transmission. Hypothesis: Intervention strategies adapted to local malaria risk and vector ecology will be more cost-effective in reducing malaria incidence and transmission risk than the currently-used LLIN intervention. Approach: The economic costs of individual interventions or combinations thereof will be assessed from both a provider and societal perspective using standard economic evaluation methodologies. Cost-effectiveness will be measured in terms of cost per person protected. The study will examine changes in drug and insecticide resistance and infection prevalence attributable to the adaptive interventions.

Malaria interventions adapted to rapidly changing malaria risk and vector ecologies are critically needed to improve the effectiveness of malaria control measures. This study will use new techniques, including machine learning and a novel cluster-randomized SMART design, to develop optimal adaptive malaria intervention strategies.

Study Type

Interventional

Enrollment (Anticipated)

122872

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Kenya
    • Homa Bay County
      • Homa Bay, Homa Bay County, Kenya
        • Recruiting
        • Tom-Mboya University College, Maseno University
        • Contact:
        • Contact:
        • Sub-Investigator:
          • Andrew K Githeko, Ph.D.
        • Sub-Investigator:
          • Gordon Okomo, Ph.D.
  • United States
    • California
      • Irvine, California, United States, 92697
        • Active, not recruiting
        • Program in Public Health

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

6 months and older (Child, Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Household inclusion criteria:

  • Households with residents at the time of survey
  • Agreement of the adult resident to provide informed consent for the intervention and survey

Study subjects inclusion criteria:

  • Passive case detection by health facilities will include all residents in the study clusters; active case detection will include residents of >6 months
  • Agreement of parent/guardian to provide informed consent and minors to provide assent.

Household exclusion criteria:

  • Household vacant
  • No adult resident home on more than 3 occasions

Study subjects exclusion criteria:

• Participants not home on day of survey

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Sequential Assignment
  • Masking: Triple

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Placebo Comparator: Regular long-lasting insecticidal nets
All participants will have LLIN coverage through routine MoH distribution of long-lasting insecticidal nets (LLINs), no other interventions will be applied. Regular LLIN: Olyset nets containing 2% permethrin or PermaNet 2.0 containing 1.8 and 1.4 g/kg, respectively, for 75 and 100 denier yarn.
Other: Regular long-lasting insecticidal nets
Olyset nets: containing 2% permethrin or PermaNet 2.0 containing 1.8 and 1.4 g/kg, respectively, for 75 and 100 denier yarn
Other Names:
  • LLIN
Experimental: Piperonyl butoxide-treated LLIN

All participants will received piperonyl butoxide-treated LLINs (PBO-LLINs) at Stage 1 and Stage 2 interventions provided that PBO-LLINs are effective at Stage 1 interventions. Each household will be provided on PBO-LLIN per two people with appropriate eduction.

PBO-LLIN: Olyset Plus, containing 2% permethrin and 1% PBO.
Other: LLIN plus Piperonyl butoxide-treated LLIN
Olyset Plus: containing 2% permethrin and 1% PBO
Other Names:
  • PBO-LLIN
Experimental: PBO-LLIN plus larval source management
All participants will received piperonyl butoxide-treated LLINs (PBO-LLINs) at Stage 1, however, Stage 1 intervention is not effective. All participants will received PBO-LLINs plus larval source management (LSM) at Stage 2. LSM will be implemented in selected clusters, including both physical and chemical methods by physical filling or removal of temporary larval habitats and larviciding of semi-permanent and permanent habitats, per the National Malaria Strategic Plan of Kenya. We will use the long-lasting microbial larvicides manufactured by Central Life Sciences. Semi-permanent and permanent habitats will be treated with FourStar® 180-day Briquets using the recommended dosage of 100 ft2 water surface per briquet.
Other: LLIN plus Piperonyl butoxide-treated LLIN
Olyset Plus: containing 2% permethrin and 1% PBO
Other Names:
  • PBO-LLIN
Other: Long-lasting microbial larvicide
Semi-permanent and permanent habitats will be treated with FourStar® 180-day Briquets using the recommended dosage of 100 ft2 water surface per briquet
Other Names:
  • FourStar® 180-day Briquets
Experimental: PBO-LLIN plus enhanced methods
All participants will received piperonyl butoxide-treated LLINs (PBO-LLINs) at Stage 1, however, Stage 1 intervention is not effective. All participants will received PBO-LLINs plus an enhanced intervention at Stage 2. The enhanced intervention is determined by machine learning method.
Other: LLIN plus Piperonyl butoxide-treated LLIN
Olyset Plus: containing 2% permethrin and 1% PBO
Other Names:
  • PBO-LLIN
Experimental: LLIN plus indoor residual spraying
All participants will received regular LLINs plus indoor residual spraying (IRS) (LLIN+IRS) at Stage 1 and Stage 2 interventions provided that LLIN+IRS is effective at Stage 1 interventions. For LLIN+IRS clusters, each dwelling's interior walls and ceilings will be sprayed with micro-encapsulated pirimiphos-methyl (Actellic 300CS) at the recommended dosage of 1g/m² and at the recommended frequency of once a year.
Other: Regular long-lasting insecticidal nets
Olyset nets: containing 2% permethrin or PermaNet 2.0 containing 1.8 and 1.4 g/kg, respectively, for 75 and 100 denier yarn
Other Names:
  • LLIN
Other: Indoor residual spraying with micro-encapsulated pirimiphos-methyl
each dwelling's interior walls and ceilings will be sprayed with micro-encapsulated pirimiphos-methyl at the recommended dosage of 1g/m² and at the recommended frequency of once a year
Other Names:
  • Actellic 300CS
Experimental: LLIN+IRS+LSM
All participants will received regular LLINs plus IRS at Stage 1, provided that LLIN+IRS is not effective. LSM will be added on these clusters at Stage 2 interventions. LSM at Stage 2 will be the long-lasting microbial larvicides manufactured by Central Life Sciences. Semi-permanent and permanent habitats will be treated with FourStar® 180-day Briquets using the recommended dosage of 100 ft2 water surface per briquet.
Other: Regular long-lasting insecticidal nets
Olyset nets: containing 2% permethrin or PermaNet 2.0 containing 1.8 and 1.4 g/kg, respectively, for 75 and 100 denier yarn
Other Names:
  • LLIN
Other: Long-lasting microbial larvicide
Semi-permanent and permanent habitats will be treated with FourStar® 180-day Briquets using the recommended dosage of 100 ft2 water surface per briquet
Other Names:
  • FourStar® 180-day Briquets
Other: Indoor residual spraying with micro-encapsulated pirimiphos-methyl
each dwelling's interior walls and ceilings will be sprayed with micro-encapsulated pirimiphos-methyl at the recommended dosage of 1g/m² and at the recommended frequency of once a year
Other Names:
  • Actellic 300CS
Experimental: LLIN+IRS plus enhanced method
All participants will received regular LLINs plus IRS at Stage 1, provided that LLIN+IRS is not effective. Enhanced method will be added on these clusters at Stage 2 interventions.The enhanced intervention is determined by machine learning method.
Other: Regular long-lasting insecticidal nets
Olyset nets: containing 2% permethrin or PermaNet 2.0 containing 1.8 and 1.4 g/kg, respectively, for 75 and 100 denier yarn
Other Names:
  • LLIN
Other: Indoor residual spraying with micro-encapsulated pirimiphos-methyl
each dwelling's interior walls and ceilings will be sprayed with micro-encapsulated pirimiphos-methyl at the recommended dosage of 1g/m² and at the recommended frequency of once a year
Other Names:
  • Actellic 300CS

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Annual clinical malaria incidence rate
Time Frame: Clinical malaria will be monitored for up to 60 months
To compare clinical malaria incidence rates among different intervention arms
Clinical malaria will be monitored for up to 60 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Malaria infection prevalence
Time Frame: Infection prevalence will be monitored for up to 60 months
To compare infection prevalence rates among different intervention arms using microscopic, RDT and molecular diagnostic methods
Infection prevalence will be monitored for up to 60 months
Malaria vector density
Time Frame: Vector density will be monitored for up to 60 months
To compare malaria vector densities between different intervention arms
Vector density will be monitored for up to 60 months
Malaria transmission intensity
Time Frame: Entomological inoculation rate will be examined for up to 60 months
To compare entomological inoculation rates between different intervention arms
Entomological inoculation rate will be examined for up to 60 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of California, Irvine

Investigators

  • Study Director: John Githure, Ph.D., Tom-Mboya University, Kenya

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 1, 2019

Primary Completion (Anticipated)

March 31, 2024

Study Completion (Anticipated)

March 31, 2024

Study Registration Dates

First Submitted

November 25, 2019

First Submitted That Met QC Criteria

November 26, 2019

First Posted (Actual)

December 2, 2019

Study Record Updates

Last Update Posted (Actual)

July 1, 2021

Last Update Submitted That Met QC Criteria

June 29, 2021

Last Verified

June 1, 2021

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • U19AI129326-03S1 (U.S. NIH Grant/Contract)

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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