Fondation Pierre Fabre

MoSQuIT helps in streamlining Malaria Surveillance for initiation of timely action, through use of mobile technology.

Main beneficiary country:
India

About the sponsor

Centre for Development of Advanced Computing, Pune

Centre for Development of Advanced Computing (C-DAC) is a R&D organization of the Ministry of Electronics and Information Technology (MeitY) for carrying out R&D in IT and Electronics, Language Computing, Health Informatics, etc.

Sector: Organizational: Communities, public authorities, NGOs, associations, foundations, etc.

Country of origin: India

The organisation has:

11
Full-Time Equivalents
8
Employees
30
Volunteers
2
Service providers

Initiative overview

Healthcare themes targeted

  • Malaria/paludism

Stage of development:

  • Pilot project/testing/trials

Area where initiative is utilised

  • National (in one country only)

Initiative start date

  • 09/01/2014

Initiative end date

  • 05/31/2018

Financing

Financing method

  • Public (grant/subsidies, call for proposals/call for tender, etc.)

Economic model(s)

  • Public health funding

About the initiative

C-DAC, in collaboration with the Indian Council of Medical Research, has developed a digital platform, Mobile-based Surveillance Quest using IT (MoSQuIT), to address some of the challenges malaria poses to the Indian health system, especially in remote rural areas. MoSQuIT automates and streamlines the otherwise manual malaria surveillance process that Accredited Social Health Activists (ASHAs) perform in rural India. It uses the guidelines and policies that underpin the national surveillance programme for malaria and fills in execution gaps through technology. The Malaria Disease Surveillance using Mobile platform (MoSQuIT) is designed for facilitating the steps of Surveillance namely: data-collection using the ubiquitous mobile phone platform, data transfer to centralized system, followed by collation and analytics.

MoSQuIT was designed to integrate within the existing surveillance framework as set up by the National Vector Borne Disease Control Program (NVBDCP) in India. It uses the guidelines and policies that underpin the national surveillance programme for malaria and fills in execution gaps through technology.

MoSQuIT has the following main objectives:

• Real-time snapshot of malaria incidence in a community;

• Detection of changes in malaria incidence distribution to initiate appropriate health system response;

• Transparency and accountability across value-chain;

• Measuring the effectiveness of anti-malaria interventions and real-time assessment of health system needs (e.g. stocks of medical supplies).

To realise these objectives, the system's functionality services the needs of multiple stakeholders involved with the surveillance process at various levels of the health system.

• ASHA workers in villages: MoSQuIT allows ASHA workers to collect patient data through a mobile phone application and upload this information onto a central server immediately, rather than rely on the manual processing of paper forms. The platform also provides: training videos (e.g. how to use Rapid Diagnostic Tests), audio clips (precaution during epidemic), and health games (encouraging health prevention). MoSQuIT also delivers lab results onf each patient, providing ASHA's with quick feedback on malaria status in the community.

• Malaria Lab: Through MoSQuIT, lab results can be uploaded straight onto the central server, making results visible to ASHA workers in the community, and facilitating timely action.

• Medical Officer & Public Health Governance/Research Staff Automated analysis on the server transforms individual patient entries into a real-time snapshot of the levels of malaria in a community. This information allows medical officers to identify, prevent or manage malaria epidemics quickly. Alongside this, the system analyses a wide range of malaria indicators, highlighting significant trends, e.g. geographical distribution of incidence, healthcare performance etc.

A pilot study conducted across 50 villages for 18 months has demonstrated the ability of the platform to: (1) improve information travel, removing the barriers of paper-based records; (2) coordinate a response between stakeholders (e.g. ASHA workers, lab technicians etc.); (3) detect epidemic outbreaks; and (4) monitor drug stock levels, making supply targeted and entirely demand-driven.

MoSQuIT has added value to the public health system in the following ways:

• Improving information travel: paper-based records take a long time to travel between the various stakeholders involved with the surveillance system, the digital system reduces a lot of this time and provides instant visibility.

• Coordinated response: the efficacy of the NVBDCP malaria surveillance protocol relies on successful communication between various stakeholders, such as ASHA workers, lab technicians, medical officer etc.; MoSQuIT streamlines this process by providing visibility over the contribution each stakeholder is having towards the surveillance process.

• Detecting epidemic outbreaks: analytics on the system compare current levels of malaria incidence to historical data to identify outbreaks and trigger health system response.

• Strengthen supply chain: MoSQuIT allows for monitoring of stock levels, allowing supply to be targeted and entirely demand-driven

MoSQuIT has thus helped in improve the efficiency of information proliferation at different levels, and initiation of timely action by Public Health system The deployments have demonstrated the ability of the platform to:

(1) improve information travel, removing the barriers of paper-based records;

(2) coordinate a response between stakeholders (e.g. ASHA workers, lab technicians etc.);

(3) detect epidemic outbreaks;

(4) monitor drug stock levels, making supply targeted and entirely demand-driven.

The complete Workflow of malaria surveillance using the MoSQuIT software is as follows:

• Data collection on Mobile phone: This provides user interface on the Mobile phone for collection of Demographic data, Fever related information (Duration of fever, RDT result), Laboratory slide collection status and result, Treatment given to patient

• Data transfer from Mobile phone to Server machine: This helps in transferring the data collected to centralized system, using three modes (General Packet Radio Service (GPRS), Short Message Service (SMS), or Manual mode). Depending on availability of cellular network in the rural area where data collection is being done, the mode of data transfer can be selected. If network is strong and continuously available then GPRS can be selected, while if the network is intermittently available then SMS mode can be selected, and if network is not available data can be transferred using manual mode. This flexibility is particularly important in rural areas where the mobile towers may be sparsely located

• Data collation and analysis on Server machine: The data transferred through the mobile phones on the field is instantly available at a centralized location. This is collated and available for analytics as part of the MoSQuIT software The following parameters can improve as a result of deployment of MoQuIT:

• Data collection

• Data Transfer

• Diagnosis/Result

• Stock Availability

• Data verification by Medical officer per 100 records

• Surveillance report/ Epidemiological indices report generation

• Data Collation

• Data availability and granularity for Analysis

Field report of the initiative

Fields of application:

Health professional training - Information, education and communication for behaviour change (IEC) - Patient monitoring and medical data

Target audience

  • Healthcare professionals and structures (hospitals, healthcare centres/clinics, health networks)
  • Entire population
  • Sick people
  • Pregnant women
  • Children - adolescents (ages 6-18)
  • Young children (0-5 years)
  • Health Worker, Lab Technician, Medical Officer

Initiative objectives

  • Decreased morbidity
  • Improve the efficiency of the public health by facilitating coordination among the stakeholders like ASHA worker, Lab technician, Medical officer etc

Key figures

100000 Number of beneficiaries since launch

30 Number of users per Day

Materials used

  • Cellular (mobile) phone
  • Smartphone
  • Tablet
  • Computer

Technologies used

  • Mobile telecommunications (without data connection)
  • Internet
  • Geolocation
  • Mobile app (Android, iOS, Windows Phone, HTML5, etc.)

Offline use

Yes

Open Source

No

Open Data

No

Independent evaluation

No

Partners

Dr Saurav Patgiri, RMRC, Dibrugarh , Assam

Health: Healthcare professionals and structures

Partners

Collaborators

startupBrics