Updated: June 13, 2020 9:36:43 am
It was four weeks ago that the states were finally given more freedom in managing the epidemic. They are, of course, better placed to deliver on public health and welfare. They are also generally more accountable. According to the recent ICMR serological sample study conducted in mid-May, barely 1 per cent 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.
Since the brahmastra of lockdown is now exhausted, the message of prevention and the device called containment zones are the only ways left to manage the epidemic. This includes allied activities: The demarcation of the boundary, testing, treatment, tracing and quarantine. Hidden inside this box of practices are the answers to questions such as: Why is Karnataka doing better than Maharashtra in terms of mortality?
But this will mean 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. That quickly became a collective punishment with little measurable benefits. One consequence 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.
That said, well designed metrics at the ward and community scale will help the science develop. They can guide the people and the administration and allow the states to compare practices and learn from each other. Let us see what can be achieved within the current framework.
Firstly, any area classification must include key socio-economic and demographic determinants, for example, the density of the area, number of people in dwellings with one room or less, or the fraction of people using community toilets. As we know, 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. Here, decongestion measures such as out-migration may be required. This will also serve as a guide to the future of the locality or ward.
An important document is the Specimen Referral Form (SRF) designed by the ICMR which must be filled to undertake the PCR Corona Test. In that, the possible patient backgrounds for recommending the test, are recorded. 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. A recent research article by ICMR has presented some of this data in an aggregated format. In that, symptomatic cases with no known contact are already a large fraction of those infected.
Given this rich structure and daily test results, many useful indicators may be designed, even at the ward or hospital level. For example, the fraction of cases which arise from (3) are essentially the unexplained cases and an important proxy for community transmission. This may well be over 20 per cent. Moreover, (2) and (3) 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. This data should be made available immediately.
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. Also welcome is the setting up of a National Migrant Information System (NMIS) on the NDMA database. Hopefully, we may now know 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.
Ensuring that our villages and towns are prepared to meet the disease is an important objective. 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. In fact, 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. Much of this data at the district level is already being submitted by the states to the central data portal covid19.nhp.gov.in. 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.
Coming to prevention, the importance of masks, distance and open ventilation is still not appreciated. 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. For example, the fraction of buses which have installed a sheet between the driver and the passengers, or recording innovative ways of ticket vending. Popularity of such colour-coding may be effective in social mobilisation.
Mitigation and adaptation require social comprehension and local solutions. 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. And yet, the central bureaucracy and elite scientific institutions have not followed this route.
The epidemic has underlined that publicness and decentralisation of science and governance is the only way to atma-nirbharta, of creating knowledge and the professional ability to solve our own problems. Without this, the post-corona Indian society would be an unhappy attempt at making the old arrangement work in a degraded reality of fearful and angry people.
Ultimately, we must learn to live with the virus, but we must also find joy. Only through constant engagement and adaptation will we overcome fear and forge a new society that will sustain both life and happiness.
This article first appeared in the print edition on June 13 under the title “Measuring the epidemic”. The writer is with Centre for Technology Alternatives for Rural Areas, IIT Bombay. He is currently on deputation to IIT Goa.
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