Measuring the epidemic

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 Measuring the epidemic

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• Freedom to manage: States got freedom to manage their pandemic affairs about a month ago, and they are definitely better placed to handle public health. ICMR reported in mid-May that just 1% of non-metro was infected (Serological sample study). So, there's a lot of spread yet to happen, and a lot of work yet to be done.
• Lockdown no more: It was tried as a fool-proof solution, and failed. Prevention and containment is the only way out. That will include demarcation of boundary, testing, treatment, tracing and quarantine. 
• Measure it: All this needs measurement of the disease at the scale wherever it unfolds. Older colour-coded zone label (by Centre in April) was district-level. It gave little benefit, but was collective punishment. Even returning migrants could change the district's colour, so no one was happy. And that could lead to lockdowns.
• Design the metrics well: From here on, at the ward and community level, metrics need to be designed well.
• Types of metrics:

1. Any classification must include socio-economic and demographic data (density of area, number of people living in one room homes, people using community toilets). This identification of vulnerable areas is useful. Decongestion via out-migration may be done.
2. PCR Corona Test can be taken by those who fill the SRF (Specimen Referral Form) of ICMR. Various patient details are taken like international travel, acute symptoms and patient movement/stay details, symptomatic or asymptomatic, etc. Data show that symptomatic cases with no known contact are a large fraction of the infected.
3. Rich data can inform us about the progression of the disease. For example - "acute symptoms in patients from outside containment zone" will mean there's community transmission happening. Similarly, symptomatic and asymptomatic close cases of an earlier case will show total infectivity. Using such data interpretation, we can get a better control over procedures being used.
4. Migrants included in SRF: It's good that this was done, as it will give an indication of risk from migrants to community at large when seen coupled with quarantine data. The NMIS (National Migrant Info System) set up in NDMA is welcome as that tells the fraction of migrants that has reached home safely.
5. Preparedness of villages and towns: One metric to help in this is the number of beds, doctors and ambulances per 1000 (and comparison with active cases in that region). Local shortage of medical care leads to adverse mortality. Example: In Maharashtra, 200 cases per day will start biting. Data is being given to a central portal already, and we may also add PDS and drinking water data to it.
6. Prevention: People are still not serious about masks, distancing and open ventilation. Install cameras and count people with masks, across locations. Ensure social distancing by forced measures (plastic sheets between driver and passengers in a bus).
7. Mitigation: To minimise disease spread, we need social understanding and local solutions. To re-start normal life, first design proper metrics and then provide all relevant data. Fear will reduce. But central bureaucracy is not doing all this.
8. Atmanirbharta: Genuine atmanirbharta will only come via publicness and decentralisation of science and governance. Otherwise we are headed for a society of angry people trying to make old arrangements work somehow. If we cannot recreate joy, life will be lost. And for that, we need data.

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