Health vulnerability analysis from the OpenCity Datajam

April 27, 2023 Vaidya R

On April 1st, 2023, the city of Bangalore was host to a “datajam” conducted by at the Indian Institute of Management Bangalore to analyse the data of Bengaluru constituencies. in the context of the upcoming Assembly elections. The event was largely attended by educated and urban civic minded people; many were part of civil society agencies. People of varied backgrounds like historians, academics, urban designers, GIS experts, software developers, and public health and policy enthusiasts attended.

Public Health is one of the more important services provided by a government to its people. Since the Covid-19 pandemic, emphasis has been on investment in public health and health vulnerabilities. Our team decided to analyse the data publicly available and focus on the public health systems of the city.

Problem Statement

Rank the health vulnerability of Bengaluru’s constituencies in terms of access to public health care facilities. 

Data Sources: 

Much of this data was provided by in advance of the event.

Analytical Framework

In the process of deciding which variables to use to analyse the data, the initial direction was to use WHO guidelines, where the vulnerability of a population was categorised by:

  • Social Determinants
    • Population density
    • Designated slums
    • Economic development in the form of income
  • Health Infrastructure Environment
    • Access to public healthcare in the form of Namma Clinics, PHCs, referral hospitals. 
    • Access to daycare, child care and early health intervention in the form of Anganwadis. 
  • Other Infrastructure
    • Sewage Treatment Plants and open drains
    • Green cover
    • Street networks
Source: Dahlgren and Whitehead, 1991

However, as we analysed the data available as well as the WHO guidelines, it became apparent that the analysis would have been constrained by the data available, the quality of the data and the time available for the analysis. For these reasons, a more basic analytical rating framework was defined. This framework included:

  • Social Determinants: Population density and gender ratio based on the voter rolls of the different constituencies.
  • Health infrastructure: 
  • Number of primary healthcare centres – Namma Clinics, UPHCs and Anganwadis. 
  • Number of secondary and tertiary healthcare centres in the form of BBMP referral hospitals and maternity hospitals

The most important and visible forms of government investment in health were considered accessible public health centres and Anganwadis. The numbers of health care centres and their reach was considered for each constituency. The reach was measured using the population served by each health centre (Population/Number of health centres). Overlapping of access to health centres and Namma Clinics in the constituency was considered so as to analyse if they ended up serving the same population.

The final Total Rating weightage was:

  • 25% for Social Determinants + 75% for Health Infrastructure
  • For health infrastructure, 90% weightage is allocated to primary health care centres (Namma Clinics, PHCs and Anganwadis) and 10% to BBMP referral hospitals and BBMP maternity hospitals.


The Government of India’s recommendations indicate that one rural Primary Health Centre (PHC) should serve a population of 30,000, and one Urban PHC for 50,000 residents. At the national level, this number is 35,667. In Bengaluru, based on the total number of UPHCs and Namma Clinics available, the population served per PHC is 35,000. This seems to suggest that in terms of the number of PHCs at least, the city is doing well. This figure, however, does not cover the number of migrants using the infrastructure too; and in Bangalore, the number of migrants is significant. It does not consider the spread of PHCs and skew in distribution across wards and constituencies.

Note: The biggest issue beyond just numbers is the quality of health services. These are dependent on the availability of staff and their capacity, medicines, equipment, diagnostic facilities. Quality is also determined by the distribution and access of these facilities within the area, the efforts in preventive/promotive healthcare and community participation, in addition to the process challenges, for e.g., insistence of Aadhar or Thayi cards.

It also needs to be mentioned that it is not clear if Namma Clinics are to be considered equivalent or supplementary to PHCs. However, during the launch the Health Minister had mentioned a population of 15,000 to 20,000 being served by each Namma Clinic. For the purposes of this analysis, for health vulnerabilities, we consider access to a Namma Clinic as equivalent to access to a PHC.

Bengaluru has 1,434 Anganwadis in the BBMP area, or one for an approximately 6,000 population. The recommended ratio is one Anganwadi for 1000 people. The discrepancy is at least 4500 people being underserved in the city (again, not considering migrants to the city). 

Based on the raw analysis, there is a definite need for PHCs, Namma Clinics and more Anganwadis to be established in the city.

At the constituency level

In terms of number of health centres, Govindaraj Nagar constituency ranks best with 5 Namma Clinics, but oddly has only one PHC. A similar pattern with more Namma Clinics and less PHCs was observed in Chamrajapet, Malleswaram and Bommanahalli constituencies.

In terms of numbers of both PHCs and Namma Clinics, Padmanabhanagar, BTM Layout and C.V. Raman Nagar ranked high in terms of the number of health centres.

The following 8 constituencies ranked the highest:

  1. Bommanahalli
  2. Gandhi Nagar
  3. Yeshwantpur
  4. Vijaynagar
  5. Sarvagnanagar
  6. Jayanagar
  7. Bangalore South
  8. K.R. Pura

In terms of health centre coverage 11 constituencies fall within acoverage of 30,000 per health care centre. Of this, Chickpet ranks best with each PHC serving a population of 17,755. 

In contrast, those that scored most poorly in health centre coverage were:

  1. Pulakeshinagar
  2. Rajajinagar
  3. Byatarayanapura
  4. C.V. Raman Nagar
  5. B.T.M Layout
Bengaluru Constituencies in terms of total number of health centres – PHCs + Namma Clinics


Health vulnerability and care is one of the most important issues that the government needs to address. This was highlighted by the paucity of care in the Covid-19 pandemic. The provision of healthcare services (through Primary Health Centres) as well as medical treatment (through Namma Clinics) is critical in the city of Bengaluru and the gaps need to be addressed by the government. There is a dearth of PHCs and Namma Clinics in the City and the lack of access, especially in areas such as Pulakeshinagar, Rajajinagar and BTM layout. Additionally, with a discrepancy of 5000 citizens being underserved in the city per PHC, many more PHCs are needed.

The 1978 AlmaAta Declaration identified primary health care as the key to the attainment of the goal of “Health for All”. The components of Primary Health Care includes: Nutrition, Water and Sanitation, Education, Prevention of endemic diseases, Mother and Child Health, Immunization, Treatment of minor ailments and injuries and Access to Essential Medicines.

Health vulnerabilities are more than just the number of PHC’s and Namma Clinics and Anganwadis. As stated above, it incorporates many variables such as population density, income, gender, disabilities, physical infrastructure etc. Using the data available to analyse the gap in numbers and coverage of PHCs and Anganwadis is just a start. But this exercise shows that if elected representatives and government wish to make a positive change, they can easily access existing data to understand the current situation and remedy the lapses.


The views expressed by the authors are in their personal capacity and do not reflect the views of their employers.

Shreya Pillai. Shreya is an urban planner based in Bangalore. 

Prerak Shah. Prerak is a social development sector professional working in public health, livelihoods and education domains for the last 3 years to leverage technology and data for effective decision-making and real-time analytics.

Nitish Kumar

Riddhi Lakhiani

Rahul Muraleedharan