Data and Diagnostics – Two Interesting Conversations

My Professor Friend and I went to meet the Chairman of Central Pollution Control Board (CPCB) in India. The Chairman was busy conducting a meeting with the Delhi Pollution Control Committee (DPCC), Professors from reputed Academic institutions such as IIT Delhi, Environmental NGOs like the Centre for Science and Environment, Medical Professionals etc.

Although we had barged in without prior appointment, Chairman welcomed us and requested to join the meeting. We were offered seats at the long elliptic table in the conference room. Tea with sugar and cashew nuts were served.  Around 20 experts were present on that cold and smoggy day.

The Senior Environmental Engineer at CPCB was making a presentation about the air pollution in Delhi.

“We have today real-time air quality monitoring at 10 automated stations that generate data on 8 parameters every 15 min. This data is transmitted to the server of CPCB for visualization and analysis”

He showed us pictures of the stations, some “data flow” diagrams that had steps of data quality control and assurance. The stations seemed to work.

I whispered to the Professor “Very impressive – this means in a year there will be nearly 3 million digits of “information” available on Delhi’s air quality. This should be really useful for the “diagnosis” of the “problem””.

Professor did not seem to be impressed. He said, “Do you think that we ever link data with diagnosis and decisions when it comes to  managing environment? Decisions are often ad-hoc and an exercise so rhetoric”. He had a smirk on his face.

” All we get from this online data is information on mean, max, min, extent of violations over standards etc. and the plots. Next, this data is crunched into an Air Quality Index (AQI). The AQI essentially adds up the “effect” of each pollutant independently or in “isolation” without considering any “interaction” between pollutants. When air pollution hits your health, both particulates and gaseous pollutants act “simultaneously”. The formula for AQI does not recognize this complexity. So, this AQI is really a bit of “fooling around”.”

I thought Professor was becoming overly critical. “But can we ever address this limitation? If we start dissecting the crudeness of the AQI and disclose its various limitations, then what will the National Green Tribunal (NGT) do? And AQI is so sensational today in the media as “breaking news””

Air Quality Index

A Professor from a reputed academic institution was the next presenter.

“We just completed a source apportionment study sponsored by CPCB using a Chemical Balance Model (CMB). In this project, we collected nearly 1000 samples of Particulate Matter (PM) and for each sample 12 constituents were analyzed. Now we have a fair idea on which group of emissions influence Delhi’s ambient air quality and where to prioritize. In this process, the conventional CMB model was modified. Our work will soon be published in an international research journal”

I was really impressed when I saw the graphs, pie charts and outputs of the modified CMB that was called CMB-Plus. Indeed, there were considerable assumptions made in reaching to the final conclusions but isn’t this usual? Unfortunately, the outcomes of the work appeared a bit trivial and sometimes a bit far-fetched. I thought that many of the actions could have been taken without waiting for the results of the CMB. It was now Professor’s turn to whisper

“Dr Modak, I am glad to see that in the process of generating such huge data, at least a research publication could be made”. Once again, I saw that he had a smirk on his face.

A Professor from a Research Unit of a famous Medical Hospital in Delhi presented results of “long term” (2 years) survey on air pollution and health. This survey was carried out over 2000 patients who were tracked over a period of 2 years and an extensive data was collected on the symptoms, respiratory illness, loss in working days and costs paid for medical treatment and consultation. This data was correlated with the ambient air quality data reported at the monitoring stations of CPCB and DPCC. The results concluded that air pollution affects human health, and more so to children and aged people. The economic costs are also significant. (We could not disagree with these important conclusions). The study however provided new statistics on morbidity and disability-adjusted life year (DALY) and some of these numbers were rather alarming.

While we all were appreciative of the painstaking work that was done, one gentleman asked (I think he was a retired bureaucrat as a bureaucrat generally speaks sense only after retirement!)

“Professor Doctor, did you consider indoor air quality at all in your attempt to correlate respiratory illness with air pollution? You are aware that we spent more than 70% of the time indoors. And to draw conclusions on DALY, don’t you think that 2 years data is rather short”

We left the meeting a bit earlier as we had another event to attend.


I was facing a problem of stomach acidity for a while. Antacids worked but I did not want to take them overly long. My GP (General Physician) was on leave and so I went to Hinduja Hospital and sought an appointment with a Senior doctor in the department of Gastroenterology. The doctor examined me and wrote down on a paper a number of tests that he wanted me to get done.

“Dr Modak, we must first build data around your “problem” and “diagnose” accordingly. Come with your reports in a week and I will see you then”. I liked his style of building data for diagnosis. As I was about to leave, he said “now that you are going to do these tests, we might as well get some more tests done – perhaps a good idea to do a MRI and a 2-D Echo cardiogram too as you mentioned about frequent heart burn you get due to acid reflux. Let us not take any chances”. He smiled and took back the note he had given and scribbled some more tests.

I spent the next week making visits to a Path clinic and a MRI Centre. I got the 2-D echo done too. I walked to the room of Gastroenterologist with a large “paper bag” that had all the reports/plates and a CD. The doctor looked through all the “outputs”.

He removed his spectacles and said “Dr Modak, I was checking for the disorders like inflammatory bowel disease, irritable bowel syndrome, peptic ulcer and reflux disease. These appear to be absent with a minor case of acid reflux. However, I need to check now possibilities like chronic liver disease and bilio-pancreatic disorder. And I also want to rule out malignancies”. He said this in a caring tone.

I thought this data collection exercise was now getting rather too much with no diagnosis for timely action. I left the Hospital.

My GP had just returned then from his vacation. I went to meet him with all the data that was generated – thanks to the Gastroenterologist.

“Oh, Dr Modak, I don’t need all this stuff. I will see this later but let me examine you first”

He asked me to show my tongue. He then put a stethoscope on my back. Checked my pulse and asked some simple questions like what I eat, do I take a walk every day or exercise, am I constipated and how well do I sleep. I thought these questions were rather basic and appeared “traditional” and not so much “data driven”.

“Nothing to worry Dr Modak. I will solve your problem” He yelled at his assistant or the “compounder” and instructed him for my medicines.

I was given a paper sachet of colorful tablets with 2 x 1 x 2 written on it. The assistant explained the numbers. I listened obediently. “This dose is for 3 days” he said.

“Come back after 3 days and see me. And don’t eat too much spicy food now – at least for the next 2 weeks” He said this patting on my back.

I realized that I would have to miss the wada-pav (bread with a spicy patty) that I used to relish every other day at the street food stall next to my office. Oh, was that the reason?


We sometimes collect too much data just because we have the technology. We rarely connect with the nature to make observations and use our traditional knowledge on “bio-indicators”. They often offer inexpensive, instinctive, participatory and communicative ways to get forewarned and interpret the situation. How many of us for instance observe the movement of frogs around a lake that message about the status of the lake ecosystem? Tribals do not need data from Automated Weather Stations (AWS) to estimate the onset of rain. They watch the movement of insects instead.

Doctors have no time today to converse with patients to understand the “symptoms” or the burgeoning “problem” to diagnose the “root cause” and “hit on the spot”. They talk about possibilities. A lot of expensive data is collected in the process but it often lands into poor diagnostic.

These types of doctors and the “modern” environmental scientists and engineers are no different.

Striking a balance is the key. The stress and disruptions to the environment and our disconnect with nature & traditional knowledge – are making the diagnostic rather difficult.

We seem to be data rich but with a “foggy” understanding – unable to face the world of tomorrow.


Cover image based on

https://www.dreamstime.com/stock-photo-diagnostics-data-numbers-ball-measure-problem-find-solution-image38259320


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2 thoughts on “Data and Diagnostics – Two Interesting Conversations

  1. Dear Prasad, I do agree with your observations about too much stress on data.  Especially in medical field, it has become a business rather than a profession.Intutive and diagnosis based on experience is missing. Regards, Ashok Paranjape

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