A strategy to come out of lockdown 4.0
To pre-empt further spread of the virus and utilise resources effectively, states should map Residential Area types of all Covid-19 cases as well. Here’s why.Updated: May 23, 2020 15:09 IST
As India slowly opens up in lockdown 4.0, our cities — home to some of the highest densities in the world and with limited public health infrastructure — must prepare to battle an expected spike of Covid-19 cases. As on May 20, 2020, almost 65% of all confirmed cases were concentrated in just 10 cities. The worst five affected — Mumbai, Delhi, Ahmedabad, Chennai and Pune — account for over 50% of the country’s cases.
Now that India has crossed 100,000 cases, substantial data is available to analyse and project future trends to prepare nuanced urban strategies. In the above-mentioned five cities, publicly available data shows us that approximately 56,000 cases are spread across around 1,600 containment zones. We can thus determine the interrelationship between the spread of the virus and specific urban contexts: identifying the types of areas where the impact of the virus has been greatest can help us pre-empt future spread by ensuring monitoring, screening and containment of similar areas elsewhere. This paradigm shift in approach can help cities get ahead of the curve, and municipalities to effectively use their resources in a targeted manner for maximum benefit.
Cities have adopted varying parameters for demarcating containment zones, ranging from an individual plot, a small residential cluster to an entire ward. However, it is important to look at the coronavirus spread through a common granular lens. Urban India typically has seven types of residential areas (RA) based on parameters such as population density, dwelling and household size, building type (apartment, individual house, tenements etc.), street widths, levels of amenity etc. These are categorized as types, with type 1 being slums or temporary hutments; type 2 being unplanned colonies, rehabilitation colonies, urban villages, small-sized plotted housing (< 125 sqm), old city and other traditional cores; type 3 being government housing/low-rise group housing; type 4 being cooperative group housing schemes, integrated townships; type 5 being medium-sized plotted housing (125– 300 sqm); type 6 being large-sized plotted housing (> 300 sqm); and type 7 being villages on the city periphery. As data is tagged to the residence of the Covid-19 case, it would benefit cities to include the residential area type of these cases in their analytics.
Once economic activity resumes, typology of non-residential areas (NRA) such as small and medium scale industries, commercial uses, retail, etc. that begin to demonstrate greater incidences of cases, should also be analysed.
Our analysis of the location of the almost 1,600 containment zones in Mumbai, Delhi, Ahmedabad, Chennai and Pune reveals that over 65% lie within RA type 2 (RA 02), i.e. areas such as unplanned colonies, chawls, and housing on plots less than 125 sqm. As one would expect, these areas are characterised by high densities. However, it is essential to acknowledge that the quality of the built environment and the resultant poor living conditions is significant: three to five storey high building typologies with small habitable spaces for large families, narrow lanes that double as the primary open space and shared bathing and toilet facilities lead to heightened physical contact and make RA 02 unsuitable for home isolation and home quarantine. Furthermore, enforcing restrictions on movement in these areas is difficult due to multiple entry and exit points. Almost 20% of the containment zones fall in RA 05 (medium sized-plotted housing), while 10 % fall in RA 03 (low-rise group housing) in these cities. Slums or temporary hutments, villages on the periphery and larger scale plotted housing are less than 5% of the containment zones.
Since comprehensive data on addresses of positive Covid-19 cases is not available publicly, we were unable to correlate the intensity of spread with the residential area type. However, with the information available, a definite pattern emerged: zones of the city, usually unplanned, with extremely high densities, are significantly more vulnerable. These areas accommodate a substantial percentage of a city’s overall population and are home to a majority of its lower income workforce.
Can pre-emptive monitoring and containment measures and social benefit schemes be rolled out in all such areas, even those unaffected by the virus? Could health booths manned primarily by volunteers under the supervision of a small medical team be set up locally to conduct biweekly door-to-door visits and provide much needed health updates? Infrastructure such as this would help in early detection, timely isolation and quarantine, and prevent these areas from transitioning into higher levels of transmission. Similarly, targeted schemes for social and financial assistance including supply of essential provisions and minimum monthly sustenance allowances could be guaranteed for such areas, especially if they lie in a containment zone. These areas should also be prioritised when pre-emptive testing for asymptomatic cases is undertaken.
It is crucial that economic growth drivers such as these cities no longer merely respond to the pandemic. Data analytics, linking positive cases to specific RA and NRA types will enable municipalities to identify priority areas, roll out pre-emptive monitoring and containment measures, allocate limited resources in a targeted way and adopt a quick-footed response to the Covid-19 pandemic. At the same time, cities must start the process of aligning development priorities and budgetary allocations towards the rehabilitation of these unplanned areas to enhance living conditions of city residents.
Mriganka Saxena and Puneet Khanna, architects and urban designers and founding partners of Delhi-based practice, Habitat Tectonics Architecture and Urbanism