Editorial Notes

[Editorial Notes] Measuring the COVID-19 epidemic

The COVID-19 cases are very close to the 3 lakhs mark in India. Well-designed metrics at the ward and community scale will help guide the people and the administration and allow the states to compare practices and learn from each other.
By IASToppers
June 13, 2020

Contents

  • Introduction
  • Containing the spread
  • Factors for Area classification
  • Specimen Referral Form
  • Fighting the stigma
  • Metrics to measure the epidemic
  • Conclusion

Measuring the COVID-19 epidemic

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Introduction:

With the COVID-19 cases surging near 3 lakhs, the states are finally given more freedom in managing the epidemic. They are better prepared and placed to deliver on public health and welfare. According to the recent Indian Council of Medical Research serological sample study conducted in mid-May, barely 1 % of non-metropolitan India was infected. Thus, as the infection spreads and eventually stabilises, there is a lot of heavy lifting that the states must do.

Containing the spread:

  • As India has begun the countdown for unlockdown, the message of prevention and the device called containment zones are the only ways left to manage the epidemic.
  • This includes allied activities like demarcation of the boundary, testing, treatment, tracing and quarantine.
  • This will require measuring the disease and its management at the scale where the disease unfolds.
  • The older colour-coded zone label, introduced by the Centre on April 14, was at the district scale, which has shown little measurable benefits.
  • One consequence of it was that districts were unhappy with the return of migrants simply because that could change their colour.
  • The second problem was that the red-ness of a region was equated with the need for lockdowns, since that was the only visible instrument.
  • Well-designed metrics at the ward and community scale will help guide the people and the administration and allow the states to compare practices and learn from each other.

Factors for Area classification:

  • Any area classification must include key socio-economic and demographic determinants.
  • They may include the density of the area, number of people in dwellings with one room or less, or the fraction of people using community toilets.
  • As much of the infection is spreading within dense clusters, such metrics would indicate vulnerable areas and the limits to reduction in contact rate through policing.
  • This would require decongestion measures such as out-migration and serve as a guide to the future of the locality or ward.

Specimen Referral Form:

  • An important document is the Specimen Referral Form (SRF) designed by the ICMR which must be filled to undertake the PCR Corona Test.
  • These are: (1) international travel, (2) acute symptoms and patient from inside containment zone, (3) acute symptoms but patient outside containment zone, (4) symptomatic close contact of an earlier case, (5) asymptomatic close contact of an earlier case, (6) frontline worker, and the newly added (7) migrant.
  • Given this rich structure and daily test results, many useful indicators may be designed, even at the ward or hospital level.
  • For example: (2) and (3) can tell us how effective our containment zones are. The overall infectivity is estimated by (4) and (5). Relative proportions of (3), (4) and (5) tell us about contact tracing.
  • This and other fields in the SRF such as age, location and symptoms, would give us substantial insights into the dynamics and severity of the disease and the efficacy of our procedures.

Fighting the stigma:

  • The recent inclusion of migrants in the SRF is indeed welcome.
  • This coupled with other quarantine data in the SRF, gives us the risk from migrants to the community at large.
  • The setting up of a National Migrant Information System (NMIS) on the NDMA database is a welcome step.
  • This can tell the fraction of migrants who have safely reached home and the state-wise status of those who haven’t and the reasons for the same.
  • In any case, the number of infected migrants, if suitably quarantined, must be subtracted from the total number of positive cases for that area/district, for they did not arise there and they are outside the infective load in the area.
  • This will help reduce the stigma on migrants and instead put more focus on quarantine arrangements for them.

Metrics to measure the epidemic:

1. Preparedness:

  • One metric to measure preparedness is the number of beds, doctors and ambulances per 1,000.
  • This may then be compared with the active cases in the region.
  • The adverse mortality in some areas is directly correlated with the local shortage of medical care.
  • For most districts in Maharashtra, shortages would start biting at about 200 cases per day.

2. Public amenities:

  • An important addition would be village-level data on the running of the local quarantine, the functioning of the PDS and availability of drinking water.

3. Prevalence of Masks:

  • A simple statistical metric is to measure the prevalence of masks in an area.
  • This can be done by installing cameras in suitable locations and counting people with masks.
  • Social distance measures are also amenable to indicators.

4. Local solutions:

  • Mitigation and adaptation require social comprehension and local solutions.
  • For example, public transports can have a sheet installed between the driver and the passengers, or innovative ways of ticket vending.
  • These need scientific studies by regional institutions and partnerships with civil society.
  • Creating and supporting good metrics and providing data is an important step in that direction.
  • This will not only save lives; it will reduce fear and help re-start normal life.

Conclusion:

The epidemic has underlined that decentralisation of science and governance is the only way to create knowledge and the professional ability to solve our own problems. Ultimately, we must learn to live with the virus, but with more awareness and preparedness, its impact can be minimized. To overcome the fear, stigma associated with the disease and sustain both life and happiness requires constant engagement and adaptation.

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