Covid19 Service Delivery Tracker by MC Sonipat

Real-time Assistance THrough Enabling Emergency Relief (RATHEE) Monitoring System RATHEE Monitoring System for COVID-19

  1. Author : Shambhu Rathee, HCS
  2. Designation: Joint Commissioner, MC Sonipat
  3. Email : shambhoorathee@gmail.com

Introduction:

Amidst the COVID-19 crisis, it is very challenging to track, monitor, manage and deliver relief and assistance to those in need, in a timely manner due to limited human resource engagement and movement. Many who need our help and support do not own or know how to operate smartphones to enable us to pin-point their exact location and deliver the services and supplies in an efficient and effective manner. Another challenge faced by the administration is to avoid duplication and repetition of relief efforts being made to those in need. Along with optimizing the resources and service delivery, there is a need for multiple stakeholders such as local bodies, district administration, civil society organizations, volunteers etc to work in tandem and unison. Identifying some of the below mentioned challenges, I have developed an integrated tech system, to address these concerns and help the administration deliver services efficiently, making it convenient and easy for everyone involved to contribute their best by saving time and resources through RATHEE Monitoring System for COVID-19.

Key Challenges:

  1. Overlapping areas of operation for multiple stakeholders
  2. Limitation on engaging more persons in service delivery due to the very nature of the COVID-19 disease.
  3. Duplicacy and even multiplicity in service and relief material delivery
  4. Absence of accurate location of the citizens
  5. Absence of assessment of needs of citizens during lockdown
  6. Multiple formats of reports to higher authorities and proper record keeping of inventory and utilization of funds
  7. Real-time monitoring and tracking of requests and challenges
  8. Scalability of the approach
  9. Defining specific roles to the stakeholders so that multiple entities can work independently
  10. Optimized utilization of resources
  11. Maintaining transparency in service delivery
  12. Confidence and capacity building of manpower
  13. Lack of awareness on COVID-19
  14. Integrity of the data, requests and challenges
  15. Digital illiteracy among population

Strategy Adopted

Firstly, base data to assess the problem was collected through a door-to-door survey during the beginning of the crisis. As the disease is communicable and can spread from one area to another, the lockdown has been enforced on the areas and localities that are hotspots or focus areas. The nature of the problem is such that we cannot allocate resources uniformly, we have to allocate the resources on a need-basis. We followed the below mentioned strategy:

  1. Collect the base data
  2. Analyse the spatial distribution of various needs, requests and challenges
  3. Identify the hot spots of various needs, requests and challenges
  4. Depute teams and resources for each hotspot and define their roles, responsibilities and areas of operations
  5. Assess future requirements by tracking the functioning of the teams
  6. Setup control room to receive requests, grievances, needs etc
  7. Depute mobile teams for supplementing the dedicating teams
  8. Assign requests to teams for verification and followed by assigning service-delivery tasks to the designated teams in the area.
  9. Track movement and functionality of teams.

Solutions Developed

To solve the problems and challenges list above, few mobile apps were developed to implement

  1. Survey App -- for doing the door to door survey of households and to link their mobile number with a location
  2. Connect Needy App -- for registering requests, needs, complaints, grievances related to essential services
  3. Reverse Tracing App -- for reporting suspected cases and identifying the potential suspects
  4. Generation of Interactive Maps -- for analysing the spatial patterns of the problems and to identify the hotspots
  5. Relief Delivery App -- for delivering the relief and service delivery to the needy

Some Key Features that Make a Difference

  1. Identification of hotspots of any size, deputing teams for these hotspots and thus defining mutually exclusive areas of operation.
  2. Disabling the user for a period once relief delivery has been ensured for that period.
  3. Recommendation on future requirements in the upcoming days so as to be prepared well in advance.

Scalability:

The RATHEE Monitoring System is ready-to-use, scalable and replicable platform requiring limited resources and maintenance.

In [1]:
from covid19Tracker import plot_need
In [2]:
from covid19Tracker import plot_choropleth
In [3]:
plot_need("basic-need", "DRY RATION")
Out[3]:

Street-View Map of weekly DRY RATION requirements reported by households in MC Sonipat during door to door survey

This map is useful for identification of hotspots of weekly DRY RATION requirements. One hotspot of any size can be alloted to a particular team, thus specifying his role and operation area.

Zooming in and out produces hotspots of different sizes.

Markers of Blue color represent household surveyed, which reported the requirements of weekly DRY RATION to be supplied.

Clicking on marker, the details of Name, Mobile Number, Colony Name, Total Members in the family may be found out.

There is color coding for hotspots in the ranges -

  1. 1 - Blue
  2. 2 - 10 - Green
  3. 10 - 100 - Yellow
  4. Above 100 - Dark Orange
In [4]:
plot_choropleth("basic-need", "DRY RATION")
Out[4]:

Ward Map of weekly DRY RATION Requirements found in MC Sonipat during door to door survey

This map represents the ward wise requirements of weekly DRY RATION the area and may be used to involve the persons having political ambitions or reponsibilties to provide support.

By hovering over the wards, one can see the ward details and total number of households in that ward requiring DRY RATION.

In [5]:
plot_need("basic-need", "COOKED FOOD")
Out[5]:

Street-View Map of daily COOKED FOOD requirements reported by households in MC Sonipat during door to door survey

This map is useful for identification of hotspots of daily COOKED FOOD requirements. One hotspot of any size can be alloted to a particular team, thus specifying his role and operation area.

Zooming in and out produces hotspots of different sizes.

Markers of Blue color represent household surveyed, which reported the requirements of daily cooked food to be supplied.

Clicking on marker, the details of Name, Mobile Number, Colony Name, Total Members in the family may be found out.

There is color coding for hotspots in the ranges -

  1. 1 - Blue
  2. 2 - 10 - Green
  3. 10 - 100 - Yellow
  4. Above 100 - Dark Orange
In [7]:
plot_choropleth("basic-need", "COOKED FOOD")
Out[7]:

Ward Map of daily COOKED FOOD Requirements found in MC Sonipat during door to door survey

This map represents the ward wise requirements of daily COOKED FOOD the area and may be used to involve the persons having political ambitions or reponsibilties to provide support.

By hovering over the wards, one can see the ward details and total number of households in that ward requiring COOKED FOOD

In [8]:
plot_need("basic-need", "MEDICINE")
Out[8]:

Street-View Map of MEDICINE requirements reported by households in MC Sonipat during door to door survey

This map is useful for identification of hotspots of MEDICINE requirements. One hotspot of any size can be alloted to a particular team, thus specifying his role and operation area.

Zooming in and out produces hotspots of different sizes.

Markers of Blue color represent household surveyed, which reported the requirements of MEDICINE to be supplied.

Clicking on marker, the details of Name, Mobile Number, Colony Name, Total Members in the family may be found out.

There is color coding for hotspots in the ranges -

  1. 1 - Blue
  2. 2 - 10 - Green
  3. 10 - 100 - Yellow
  4. Above 100 - Dark Orange
In [10]:
plot_choropleth("basic-need", "MEDICINE")
Out[10]:

Ward Map of MEDICINE Requirements found in MC Sonipat during door to door survey

This map represents the ward wise requirements of MEDICINE the area and may be used to involve the persons having political ambitions or reponsibilties to provide support.

By hovering over the wards, one can see the ward details and total number of households in that ward requiring MEDICINE

In [11]:
plot_need("special-need", "OLD PERSON")
Out[11]:

Street-View Map of OLDAGE CARE requirements reported by households in MC Sonipat during door to door survey

This map is useful for identification of hotspots of OLDAGE CARE requirements. One hotspot of any size can be alloted to a particular team, thus specifying his role and operation area.

Zooming in and out produces hotspots of different sizes.

Markers of Blue color represent household surveyed, which reported the requirements of OLDAGE CARE.

Clicking on marker, the details of Name, Mobile Number, Colony Name, Total Members in the family may be found out.

There is color coding for hotspots in the ranges -

  1. 1 - Blue
  2. 2 - 10 - Green
  3. 10 - 100 - Yellow
  4. Above 100 - Dark Orange
In [14]:
plot_choropleth("special-need", "OLD PERSON")
Out[14]:

Ward Map of OLDAGE CARE Requirements found in MC Sonipat during door to door survey

This map represents the ward wise requirements of OLDAGE CARE the area and may be used to involve the persons having political ambitions or reponsibilties to provide support. By hovering over the wards, one can see the ward details and total number of households in that ward requiring OLDAGE CARE

In [15]:
plot_need("special-need", "PHYSICALLY DISABLED")
Out[15]:

Street-View Map of DISABLED CARE requirements reported by households in MC Sonipat during door to door survey

This map is useful for identification of hotspots of DISABLED CARE requirements. One hotspot of any size can be alloted to a particular team, thus specifying his role and operation area.

Zooming in and out produces hotspots of different sizes.

Markers of Blue color represent household surveyed, which reported the requirements of DISABLED CARE.

Clicking on marker, the details of Name, Mobile Number, Colony Name, Total Members in the family may be found out.

There is color coding for hotspots in the ranges -

  1. 1 - Blue
  2. 2 - 10 - Green
  3. 10 - 100 - Yellow
  4. Above 100 - Dark Orange
  5. Above 100 - Dark Orange
In [16]:
plot_choropleth("special-need", "PHYSICALLY DISABLED")
Out[16]:

Ward Map of DISABLED CARE Requirements found in MC Sonipat during door to door survey

This map represents the ward wise requirements of OLDAGE CARE the area and may be used to involve the persons having political ambitions or reponsibilties to provide support. By hovering over the wards, one can see the ward details and total number of households in that ward requiring DISABLED CARE

In [ ]: