Thursday, July 23, 2020

Randomised Control Trials and the Alleviation of Poverty in India

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Sattva Vasavada

Article Title

Randomised Control Trials and the Alleviation of Poverty in India

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Global Views 360

Publication Date

July 23, 2020

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Poverty in India — A Representative Image

Poverty in India — A Representative Image | Source: Atul Kumar via Unsplash

Abhijit Banerjee and Esther Duflo won the 2019 Nobel Prize in Economics for their “experimental approach in alleviating global poverty”. Their experimental approach encompassed a variety of novel methods to understand and analyse interventions and Randomised Control Trials (RCTs). Their research has been used by policy makers to make informed policy decisions to best help the marginalised.

What are RCTs?

To understand the effect of a policy, intervention, or medicine, decision makers try to measure the efficacy of the treatment. Do deworming pills given to children improve test scores? Does providing chlorinated water improve the health and economic outcomes of villages? These are some causal (read causal, i.e. caused by, not casual) questions researchers are interested in. The best way to analyse causal effects is to randomise the selection of people in the treatment and the control group (for example: children who are given deworming pills versus children who are not given the pills). This random selection of the two groups removes many statistical biases that might affect the results.

RCTs in India:

Many of the RCTs performed by Banerjee and Duflo were in India. They involved short- and long-term impact assessments of various interventions, policies, models, and treatments. We look at a few RCTs implemented in India:

Teacher absenteeism rates:

Troubled by the low attendance rates (or high absence rates) of public-school teachers in India, Duflo assessed the impact of financial incentives on the absence rates of teachers in Rajasthan. The study monitored teacher attendance by cameras, which was tied to a financial incentive if the attendance was high. From a baseline absence rate of 44%, teacher absenteeism in the treatment group fell by 21%, relative to the control group. High teacher attendance caused child test scores to improve too.

COVID-19 and health-seeking behaviour:

In the context of COVID-19, Banerjee tested the effect of sending messages via SMS that promoted health preserving behaviour. The results were very positive. By sending a short, 2.5-minute clip to 25 million randomly selected individuals in West Bengal, the intervention i) found a two-fold increase in symptom reporting to village health workers, ii) increased hand washing rates by 7%, and iii) increased mask-wearing by 2%. While mask-wearing rates increased only marginally, the spillover effects (wearing a mask stops the virus from infecting more people) were moderately high and positive.

Asset Transfers and the Notion of Poverty:

An RCT by Banerjee in West Bengal involving a productive asset transfer accompanied with training found large and persistent effects on monthly consumption and other variables. The treatment group reported 25% higher consumption levels relative to the control group, who did not receive the asset transfer and training. Implications of such RCTs are huge. The notion that the poor are lazy and unwilling to perform strenuous labour is falsified by this RCT. Often, what the poor lack are opportunities that are hard to come by, given their financial status. A small nudge, like the asset transfer, can cause large and positive effects on their well-being.  

Salt fortification to reduce anaemia:

RCTs also help rule out less cost-effective interventions. Duflo and Banerjee evaluated an RCT which distributed fortified salt in 400 villages of Bihar, to reduce the prevalence of anaemia. However, this intervention found no statistically significant impact on health outcomes like anaemia, hemoglobin, etc.  Thus, while RCTs help introduce novel methods of impacting the lives of the poor, they also help in ruling out in-effective measures. A policy maker might try other alternatives to reduce the prevalence of anaemia.

Are RCTs the gold standard?

Maybe. Extrapolating results from a regional RCT to national policies could present problems. Contextuality matters. A study that indicates positive gains for one region might present different, and rather adverse effects for another region. Nation wide effects might not be as prominent as regional results of a single RCT. The good part is that Banerjee and Duflo have a solution. Just perform more RCTs!

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July 19, 2021 11:59 AM

Detecting The Ultra-High Energy Cosmic Rays With Smartphones

Smartphones have become the most commonplace objects in our daily lives. The unimaginable power that we hold in our hands is unrealized by most of us and, more importantly, untapped. Its creativity often gets misused but one can only hope that it’s fascinating abilities would be utilized. For example, did you know that the millions of phones around the globe can be connected to form a particle detector? The following article covers the CRAYFIS (Cosmic RAYs Found in Smartphones) phone-based application developed by the physicists from the University of California—Daniel Whiteson, Michael Mulhearn, and their team. CRAYFIS aims to take advantage of the large network of smartphones around the world and detect the cosmic or gamma rays bursts which enter the Earth’s atmosphere almost constantly.

What Are Cosmic Rays?

Cosmic rays are high velocity subatomic particles bombarding the Earth’s upper atmosphere continuously. Cosmic ray bursts have the highest energy compared to all forms of electro-magnetic radiation. When we say ultra-high energy particles (energy more than 10<sup>18</sup> eV), we mean two million times more energetic than the ones that can be produced by the particle colliders on Earth.  These rays are thought to be more powerful than typical supernovae and can release trillions of times more energy than the Sun. They are also highly unpredictable as they can enter Earth’s atmosphere from any direction and the bursts can last for any period of time ranging from a few thousand seconds to several minutes.

Despite many theoretical hypotheses, the sources of these ultra-high energy cosmic rays are still a mystery to us even after many decades of their discovery. These rays were initially discovered in the 1960’s by the U.S. military when they were doing background checks for gamma rays after nuclear weapon testing. Cosmologists suggest that these bursts could be the result of super massive stars collapsing - leading to hypernova; or can be retraced to collisions of black holes with other black holes or neutron stars.

How Do We Detect Them?

When the high-energy particles collide with the Earth’s atmosphere, the air and the gas molecules cause them to break apart and create massive showers of relatively low-energy particles. Aurora borealis i.e., the Northern and the Southern lights are the lights that are emitted when these cosmic rays interact with the Earth’s magnetic field. Currently, these particles are hitting the Earth at a rate of about one per square meter per second. The showers get scattered to a radius of one or two kilometers consisting mostly of high-energy photons, electrons, positrons and muons. But the fact that these particles can hit the Earth anytime and anywhere is where the problem arises. Since the Earth has a massive area, it is not possible to place a detector everywhere and catch them at the exact moment.

Energetic charged particles known as cosmic rays hit our atmosphere, where they collide with air molecules to produce a shower of secondary particle | Source: CERN

Detecting such a shower requires a very big telescope, which logically means a network of individual particle detectors distributed over a mile or two-wide radius and connected to each other. The Pierre Auger Observatory in South America is the only such arrangement where 1,600 particle detectors have been scattered on 3,000 square kilometers of land. But the construction cost of the same was about $100 million. Yet, only a few cosmic ray particles could be detected using this arrangement. How do we spread this network around the Earth?

In addition to being cost-effective, such a setup must also be feasible. The Earth’s surface cannot possibly be dotted with particle detectors which cost huge fortunes. This is where smartphones come into the picture.

Detecting The Particles Using Smartphones

Smartphones are the most appropriate devices required to solve the problem. They have planet wide coverage, are affordable by most people and are being actively used by more than 1.5 billion users around the planet. Individually, these devices are low and inefficient; but a considerably dense network of such devices can give us a chance to detect cosmic ray showers belonging to the highest energy range.

Previous research has shown that smartphones have the capability of detecting ionizing radiation. The camera is the most sensitive part of the smartphone and is just the device required to meet our expectations. A CMOS (Complementary Metal Oxide Semiconductor) device is present in the camera- in which silicon photodiode pixels produce electron-hole pairs when struck by visible photons (when photons are detected by the CMOS device, it leaves traces of weakly activated pixels). The incoming rays are also laced with other noises and interference from the surroundings.  Although these devices are made to detect visible light, they still have the capability of detecting higher-energy photons and also low-ionizing particles such as the muons.

A screenshot from the app which shows the exposure time, the events- the number of particles recorded and other properties

To avoid normal light, the CRAYFIS application is to be run during nighttime with the camera facing down. As the phone processor runs the application it collects data from its surroundings using a camera as its detector element. The megapixel images (i.e., the incoming particles) are scanned at a speed of 5 to 15 frames per second, depending on the frame-processing speed of the device. Scientists expect that signals from the cosmic rays would occur rarely, i.e., around one in 500 frames. Also, there is the job of removing background data. An algorithm was created to tune the incoming particle shower by setting a threshold frequency at around 0.1 frames per second. Frames containing pixels above the threshold are stored and passed to the second stage which examines the stored frames, saving only the pixels above a second, lower threshold.

The CRAYFIS app is designed to run when the phone is not being used and when it is connected to a power source. The actual performance would be widely affected by the geometry of the smartphone’s camera and the conditions in which the data is being collected. Further, once the application is installed and is in the operating mode, no participation is required from the user, which is required to achieve wide-scale participation. When a Wifi connection is available the collected data would be uploaded to the central server so that it could be interpreted.

There is much complicated math used to trace back the information collected from the application. The most important parameters for the app are the local density of incoming particles, the detection area of the phone and the particle identification efficiency. These parameters are used to find the mean number of candidates (photons or muons) being detected. Further, the probability that a phone will detect no candidates or the probability that a phone will detect one or more candidates is given by Poisson distribution. The density of the shower is directly proportional to the incident particle energy with a distribution in x and y sensitive to the direction in which the particle came from. An Unbinned Likelihood (it is the probability of obtaining a certain data- in this case the distribution of the cosmic rays including their energy and direction, the obtained data is arranged into bins which are very, very small) analysis is used to determine the incident particle energy and direction. To eliminate background interference, a benchmark requirement has been set that at least 5 phones must detect and register a hit to be considered as a candidate.

It is impossible to express just how mind-blowing this innovation is. As the days pass, Science and Technology around us keep on surprising us and challenge us to rack our brains for more and more unique ways to deal with complex problems. The CRAYFIS app is simply beautiful and it would be a dream-come-true to the scientists if the project works out and we are able to detect these high energy, super intimidating cosmic rays with smartphones from our backyard.

Further Reading

The paper by Daniel Whiteson and team can be found here.

An exciting book “We Have No Idea” by Daniel Whiteson and cartoonist Jorge Cham can be found here.

The CRAYFIS app can be found here.

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