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A 'Poker Trial' of alternative approaches to search a city for Triatomine vectors of Chagas Disease

Last registered on May 13, 2019

Pre-Trial

Trial Information

General Information

Title
A 'Poker Trial' of alternative approaches to search a city for Triatomine vectors of Chagas Disease
RCT ID
AEARCTR-0004127
Initial registration date
May 05, 2019

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
May 13, 2019, 11:28 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
University of Pennsylvania

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2019-05-06
End date
2019-07-15
Secondary IDs
Abstract
The trial will compare three perspectives on guiding the search for households infested with Triatoma infestans, a vector of Chagas disease.
Arm 1. Raw Data-- raw data (historical infestation, participation in insecticide application campaigns) will be presented to searchers.
Arm 2. Risk Map (Vectorpoint) and incentives for spatial coverage and visit to higher risk households.
Arm 3. Optimization -- households are identified, including alternatives, and assigned to searchers
External Link(s)

Registration Citation

Citation
Levy, Michael. 2019. "A 'Poker Trial' of alternative approaches to search a city for Triatomine vectors of Chagas Disease." AEA RCT Registry. May 13. https://doi.org/10.1257/rct.4127-1.0
Former Citation
Levy, Michael. 2019. "A 'Poker Trial' of alternative approaches to search a city for Triatomine vectors of Chagas Disease." AEA RCT Registry. May 13. https://www.socialscienceregistry.org/trials/4127/history/46350
Experimental Details

Interventions

Intervention(s)
Three approaches to spatial search for triatomine bugs are compared:

I. Vectorpoint: an app that shows a risk map, based on a spatial temporal INLA model. Risk levels are presented as quintiles. Spatial coverage of the search zone is measured using delauney triangulation, in which each inspected household forms a node of triangles. The largest triangle (in terms of number of un-inspected households within the triangle) is our measure of coverage.

II. Control: An app which shows historical data on households, including prior infestation status and participation in the 'attack' phase of the vector control campaign.

III. Optimization: an app which assigns inspectors to households sequentially. The assigned household is shown in a blue dot. The optimization algorithm behind this application balances spatial coverage and visits to higher-risk households (as defined via the same model behind vectorpoint)

Intervention Start Date
2019-05-06
Intervention End Date
2019-07-15

Primary Outcomes

Primary Outcomes (end points)
We are running a 'Poker Trial' in which arms compete directly with the control on a set of paired intervention areas. The 'hands' are valued as follows:

Infestation: If an inspector uncovers an infested household. Base points = 500 with an additional 50 points for each additional infested house discovered

Risk & Coverage: If the average risk of searched households >=4 (of a 5-point scale) and the spatial coverage is less than or equal to 5% of the total number of households. Base points = 300 additional points: 5 per reduction of 1 house in the largest triangle, 1,2,3,4,5 for visits to houses in risk quintiles 1-5 respectively.

Risk alone: Mean risk of households visited >=4, but spatial coverage is not less than 5% of the total number of houses. Base points= 100, additional points 1,2,3,4,5 for each risk level.

Spatial coverage alone: Largest delauney triangle is <5% of total number of houses. Base points = 100, 5 additional for each reduction in size of the largest triangle.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Difference in the average estimated probability of infestation of households before and after inspections.
Secondary Outcomes (explanation)
The spatial-temporal model predicts the probability of infestation for each house, conditional on covariates (prior infestation, prior participation in insecticide campaigns), spatial position (a spatially correlated random effect estimated through INLA) and an intercept.

Experimental Design

Experimental Design
Inspectors have all previously been trained in entomological search in Arequipa and the use of the three apps. Each is allowed to search a search zone for one week (6 hours/day, 30 hours/week). In the Vectorpoint arm they are provided points (as described above) which can be used for paid time off (1000 points = a day off). In the control and optimization apps they receive points only for identifying infested households. Personnel are also instructed to assess infestation with bed bugs and are provide 50 points for each confirmed identification.

Searchers are interviewed once under each arm at the end of the week to record their search strategies under each approach.

All infestations are confirmed by the field manager and reported immediately to the Ministry of Health for treatment in the case of triatomine infestations.
Experimental Design Details
Randomization Method
Search areas were matched (into triplets) on two covariates: number of previously infested houses in the zone and district in which the zone lies. Optimal tripartite matching algorithms were run in r.
Randomization Unit
Search zones consisted of approximately 250 (210-280) households. These were defined, blinded to arms, based on political and geophysical barriers in the landscape.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
9 searchers
Sample size: planned number of observations
54 search zones. Observations are on the level of search zone.
Sample size (or number of clusters) by treatment arms
18
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For the poker trial we are comparing simply which arm wins (although we try 3 interventions together we compare them individually). The outcome is a simple 0/1 for each 'hand', if an intervention beat the control at least 13 out of 18 hands the p-value will be <.05. Considering multiple comparisons an arm would have to beat any other arm at least 13 times (p=0.015).
IRB

Institutional Review Boards (IRBs)

IRB Name
University o Pennsylvania
IRB Approval Date
2019-04-24
IRB Approval Number
824603
IRB Name
Universidad Peruana Cayetano Heredia
IRB Approval Date
2018-06-26
IRB Approval Number
66427

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials