Wild Connect

The emerging zoonotic diseases are a growing public health care threat. Explosive outbreaks of zoonotic diseases have become increasingly common in the past two decades because of increased human-animal interactions. Zoonotic infections are a major concern to global health security owing to their ability to rapidly spread and turn into epidemics or pandemics. Early detection of the symptoms of the disease and geolocating the original could play a remarkable role in curtailing the spread of the infection and therefore making a significant impact in combating the proliferation of zoonoses. Wild Connect, a gis-based offline-first data-collection and analysis platform which aids in the early detection and tracking of infections in remote locations and keeping the medical centres updated. Staff at control centres can analyse and detect any spreads from occurring.

It is estimated that about 60% of emerging infectious diseases that are reported globally are zoonoses. Rural communities living in and around the wildlife reserves are the most vulnerable as they are highly prone to the risk of zoonotic diseases. The lack of preliminary information from these remote rural locations makes it very difficult to contain the spread of the infection. Building an early warning system will be advantageous in preventing the escalation of the infection cases and help the health care workers to be better prepared to tackle the zoonotic outbreaks. Keeping a regular medical record of symptoms shown by every patient interacting with the ASHA workers or primary health centres in these areas and using machine learning can help detect patterns emerging of any existing or new disease spreading.

Zoonotic infection outbreaks mostly occur in remote areas which makes it impossible to provide urgent public health services to these hard-to-reach populations. One of the reasons for the delay is that there is a dearth of sufficient data from the remote villages. Wild Connect is a GIS based, offline-first data collections and analysis platform. It has 3 components a) Data Collection which is done through Mobile/Web Apps. b) Admin portal to manage the components and ensure data usage c) Analysis which builds GIS based dashboards to identify the symptoms and their spread in a geography. Analyses of the data using ML models will help detect outbreaks.

There is an estimated population of 50-100 million living in and around wildlife protected areas in India. Wild Connect is built in the interest to serve the remote dwellers in and around the wildlife reserves as these rural communities are much vulnerable to the exposure of zoonotic infections. The Centre for Wildlife Studies has deployed this application in the Western Ghats of India which includes the state of Karnataka, Goa, Tamil Nadu, Maharashtra and Kerala. It could be employed in the rural locations around the wildlife areas across India and could be scaled globally to combat zoonotic outbreaks.

Data collection and analysis of symptoms from the remote locations around the wildlife reserves will assist as an early warning predictive system for the disease outbreak and thereby strengthening zoonotic disease surveillance. Early detection of zoonoses will curb the rampant effect of the infection. It will also assist the medical and ASHA workers to be prepared to diagnose and tackle contagious diseases more efficiently. At the Centre for Wildlife Studies, the Wild Connect Application is deployed to collect information regarding the primary healthcare centres which will help us to support and equip last-mile primary healthcare providers with the essential medical supplies required.

Presently, the Wild Connect Platform being used by our staff in these remote areas to collect data on primary healthcare centres and covid related equipment requirement and from the headquarters, we are fulfilling that need. We have tested the platform on the field conditions and piloted it for a specific use case.

The same model will then be deployed in primary healthcare centres to record the medical data and then the data will be analysed by the team of researchers at the headquarters who will work on building the early detection models.

The Centre for Wildlife Studies is an internationally recognized centre of excellence in the arenas of wildlife research, conservation, policy, and education. CWS practices science-based conservation which includes understanding conflict, zoonotic, resource extraction, tourism, alternative livelihoods, and wildlife diseases. CWS is recognised as a Scientific and Industrial Research Organisation, and Centre for Excellence by the Government of India.

The uniqueness of Wild Connect lies in its capability of working in remote areas with low or zero connectivity with periodic updates possibilities. Also, the team will be analyzing the data and eventually build the models for the early detection and warning system. The Primary Healthcare centres, ASHA workers can use this platform and provide almost real-time data for analysis. The models once built and tested can be deployed without much efforts. 

The network of primary healthcare centres we built over last few months while helping them with covid relief efforts also puts us in a unique situation to convince and train the ASHA workers and health workers in these remotest areas in and around wildlife protected areas for the use of the platform.

The platform will use Machine Learning and the models will be built under the guidance of Dr. BINDU RAGHAVAN who have worked on Immunology & Infectious Diseases and Dr. Krithi Karanth who  has worked extensively on wildlife conservation and is known around the world for her contributions. Sumit Arora will be leading the development and deployment of the project across who has experience in working with the governments on technological solutions for Swachh Bharat Mission and worked on deployments of the same across the country.

The population in India that is living close to wildlife protected areas is estimated to be 50-100 Million. All of these people are being served by Primary Healthcare Centres and ASHA workers in those areas. The solution is going to serve all the community members by keeping their medical records and doing analysis of any future outbreaks.

Presently, we worked with around 8000 Primary Healthcare workers working with 200 Primary Healthcare Centres. Next year we plan to scale the data collection from around 1000 primary healthcare centres which will serve more than 1 Million Community Members. Further, this can be rolled out in all the parks in India serving all 50-100 Million population as direct beneficiaries and eventually all of India as In-direct beneficiary by safeguarding them from any outbreaks crossing the boundaries of those villages.

The solution aims to serve about 80 million rural communities of India living in and around the wildlife reserves. The Centre for Wildlife has been working tirelessly to mitigate the human-wildlife conflict for 37 year across India. We have established strong relationships with these rural communities which will enable us to implement the solution. Our dedicated field staff all in and around the wildlife corridor will be involved in collecting the critical data necessary for the solution.

1. Technology development and Deployment Lead: 1

2. Immunity and Infectious Diseases Specialist: 1

3. Wildlife Conservation Specialist: 1

4. Research Fellows: 2

5. Field Staff for Training: 20

6. Technical Staff: 8

1. Sumit Arora: comes with 15 years of experience in building large scale technology systems. In the past Sumit has developed and deployed community-driven technology systems under the world-known Clean India Mission which is being used by 20 Million citizens across more than 3000 cities.

2. Dr. Krithi Karanth: Is world known for her contributions to Wildlife Conservation and research. Her research in India and Asia spans 23 years and encompasses many issues in human dimensions of wildlife conservation. Her more than 40 awards and recognitions include Wild Innovator, Eisenhower Fellow, and the Rolex Award for Enterprise. 

3. Dr. Bindu Raghavan: has worked extensively on Immunity and Infections Diseases. Has also worked on Medical Geography and Spatial Epidemiology of Tropical Diseases which makes her a good fit to guide the machine learning model creation for early detection.

The Centre for Wildlife Studies is a 37-year-old internationally recognized centre-of-excellence in the arenas of wildlife research, conservation, policy, and education and established in 1984 by Padmashri Dr. Ullas Karanth. In 2020, we launched the Wild Surakshe (Surakshe means Safety), a public health and safety program. The program provides knowledge to empower the communities living close to wildlife reserves to cope with zoonotic diseases such as Covid-19 and human-wildlife conflict. Our team has conducted 150 workshops and trained more than 4,000 people. These initiatives are implemented in collaboration with a network of dedicated local partners who engage with government officials, opinion makers and social leaders in several places across India. 

All three members of the leadership team have worked extensively with communities in areas of conservation, healthcare and technology. Over the years their work shows that they work very close with communities in building solutions which are right for them. In all the programs the participation from citizens is encouraged which is irrespective of gender. In the public safety program we worked extensively with the ASHA workers and women in the rural areas as we believe they can bring about the real difference.

Solve is a space where innovative and scalable ideas get the right guidance, mentorship, opportunities for partnerships and funding to scale the solutions. We are deeply impressed by the ideas which have got support over the years and would love to be part of the same.

We wish to achieve the following by being part of solve

1. Build partnerships with governments of various countries where our solution can be deployed. 

2. Build partnerships with organizations willing to work with us and help us in the early warning detection systems through the use of Machine Learning.

3. Get support from governments and organizations in terms of funds as to finish building this platform.

At the current stage, the platform can be deployed for data collection and manual analysis. We would like to seek support on building the next phase of the technology from experts. 

We would also like to seek support on building a business model which could be for-profit in nature. 

1. MIT. We would like to work with the machine learning experts at MIT who can help us build the model. 

2. Large Scale Tech Organizations: Help us evaluate our technology and help us make it more scalable through volunteer support from their employees if possible. 

The early warning system for outbreaks of Zoonotic diseases will be able to safeguard millions of lives by helping curb the disease immediately before its outbreak. Starting with developing countries where the devastating effects of pandemics are much larger than developed countries, that makes this platform even important.

The platform will use Machine Learning heavily for the same and thus we feel we qualify for the prize. This prize will help us hire the right talent and perfect the machine learning models to achieve the goal of building robust early warning systems. 

Presently the platform is helping us collect data on various primary healthcare centres in the Western Ghats region of India in the states of Karnataka and Goa. With the data collected about the shortage of essential supplies such as Oximeters, IR Thermometers, PPE Kits, Sanitizers, BP Monitors at these primary healthcare centres during the second wave of COVID19 in India, we are able to replenish the same. The platform has been tested on the ground and has also helped us establish the primary use case of technology working for an emergency cause. 

We believe the platform can serve these communities living in close proximity to wildlife reserves and more in a customized manner. The solution qualifies for the Global Fund Prize.