SOCIETY FOR HEALTH ALLIED RESEARCH & EDUCATION INDIA (SHARE INDIA)

Disease Surveillance

Building Systems Capacity on Outbreaks, Laboratory Surveillance Training Emergency Response and


Infection Prevention Control and Anti-Microbial Resistance (BOLSTER)

Disease Surveillance

The disease surveillance training and health system emergency response component under project Building systems capacity on Outbreaks, Laboratory Surveillance Training Emergency response and Infection Prevention Control and Anti-Microbial Resistance(BOLSTER) supported by the Centers for Disease Control and Prevention (CDC) is working towards improving health systems and strengthening disease detection, diagnostics and mortality surveillance along with epidemiological and public health workforce capacity development. The technical assistance envisaged in the project will help in achieving timely generation of disease burden data, trends and associated risk factors through a robust dovetailed surveillance system which is based on real time data reporting and will enable the system to efficiently manage disease outbreaks and build capacity for public health system resilience over time.

The NITI Aayog’s “Vision 2035 for Public Health Surveillance in India” envisages that surveillance in India will need to graduate from traditional data entry systems based on vertical program implementation to real-time data capture from existing health records which are integrated. The project is based on a three-stage process (3 years duration) of health intervention model suggested in selected states of India:

1. To conduct baseline assessment of existing health systems (4-6 months)

2. Capacity building to enhance systems capacity of monitoring and response to common pathogens and emerging outbreaks (1-2 years)

3. Outcome Evaluation and documentation of success and lessons learnt (4-6 months)

Our Reach

  1. 1. Chhattisgarh
  2. 2. Rajasthan
  3. 3. Orissa
  4. 4. Delhi
  5. 5. Uttarakhand
  6. 6. Maharashtra
  7. 7. Andhra Pradesh

Deliverables

  • Baseline assessment of existing health systems and capacity building of public health and laboratory work force
  • Strengthening of MIS-C surveillance
  • Mortality reporting and training of physicians for cause of death
  • Real time and integrated health systems and early outbreak detection and response
  • One health surveillance training

Objectives

  • To improve health systems and strengthen disease detection, diagnostics and mortality surveillance, along with epidemiological and public health workforce capacity building.
  • To establish an enhanced real time data reporting system for timely generation of disease burden data, trends and associated risk factors through a robust dovetailed surveillance system.

1. Activities

The activities envisaged under the Surveillance project are in congruence with the public health surveillance goals stated in NITI AAYOG’s-Vision 2035 document. The focus is on strengthening the public health surveillance for improving outbreak preparedness for communicable diseases and also emerging epidemics of non-communicable diseases. While guiding prevention and health promotion strategies, these activities would help build the capacity of public health personnel and improve outbreak response so that the states in India are able to undertake evidence-based decisions and thereby limit the morbidity, disability or death due to outbreak prone diseases.

Baseline assessment of infectious disease surveillance systems including disease monitoring programs in selected states. The outbreak preparedness of these States for epidemic-prone diseases and gaps in existing health systems and District Public Health Laboratory (DPHL) diagnostic capacity will be assessed.

Capacity building of laboratory and public health work force by:

  • Identifying and conducting ToTs, focusing on trainings/procurements on diagnostics and reporting of priority pathogens
  • Expanding diagnostic capacity to also include other diseases prioritized for elimination or other state specific priorities
  • Using algorithmic detection, real time dashboards and AI tools for outbreak detection

Use of surveillance data for evidence-based decision making: The timely generation of disease burden data, trends and associated risk factors based on real-time data will enable the system to efficiently manage disease outbreaks and build capacity for public health system resilience over time. This will empower decision makers to lead and manage more effectively by utilizing information in a timely manner.

Evaluate Interventions and document achievements: This activity will facilitate the flow of information and support the continuity, quality and safety of data.

Assessment of existing mortality surveillance systems and provide training for all cause-mortality reporting in the selected states: Identification of gaps in the mortality reporting at different levels of the reporting units in the health system and need based interventions will be undertaken to minimize the human/technical reporting errors. Support will be provided to increase reporting of cause of death for all registered deaths in selected states. Training of physicians will be conducted in correct certification of cause of death for all-cause mortality.

Provide training for MIS-C reporting: MIS-C is considered a serious complication of COVID-19 and warrants the need for systematic collection of information to monitor characteristics of the disease and informs public health response.

Provide training for one health disease surveillance: To scale up Anti-Microbial Resistance, Zoonosis (One health) activity and data reporting.

 
Trainings1
Trainings2
 

2. Accomplishments

  • The project team supported by the Centers for Disease Control and Prevention, India surveillance team visited Haridwar, Uttarakhand in April 2021 to extend support to the Uttarakhand State Health Department for its Kumbh Mela Surveillance activities, at the request of the Director, National Centre for Disease Control (NCDC), New Delhi.

The Kumbh Mela response activities included:

  • TIntegration of data received by the Health Emergency Operation Centre (HEOC) established at Haridwar, Uttarakhand for Kumbh Mela disease reporting on Integrated Health Information Platform (IHIP) portal. The various data sources integrated included IHIP data, data from ambulance services, call centre data and media alerts/rumours received by the HEOC.
  • TCreation of a decision support system (DSS) tool for the HEOC team for automated generation of daily reports for Kumbh Mela surveillance. The DSS tool was designed to auto-generate graphical visualizations of the IHIP portal data. These graphs were then used by the HEOC team for the daily reports submitted to policy makers for day-to-day decision-making regarding allocation of resources such as health workers at mass gathering sites and services such an ambulance and setting up testing sites.
  • TGeographic Information System (GIS) mapping of all health facilities reporting on IHIP portal for Kumbh Mela disease surveillance.
  • TThe call related data from the call centre established for the HEOC was analysed by the team to provide the HEOC team information on the type of calls received at their call centre which was established for the Kumbh Mela.
Kumbh-Mela1
Kumbh-Mela2