Updated: May 29, 2021 9:13:23 am
We are not at war; we are in a pandemic and in data we trust. The COVID-19 pandemic has highlighted globally how important data is to governments in decision-making. The power of such data was seen early on in the evidence-based response and decision-making in countries like South Korea. Modern response to pandemics has focused on exploiting all the available data to inform policy action in real time. It is quite obvious that epidemiological data is of paramount significance for targeting and implementing control measures for public health in a timely manner. We have never had a coherent statistical picture of public health in India, nor of the provision of health services. There has never been a bigger moral imperative or need in India for data transparency and data sharing than today.
The need for timely data sharing lies in its utility through analysis and its power resides in its interpretation. The current pandemic is a prime example. It has revealed the need for continuous and repeated tracking of case numbers, fatalities and recoveries. The epidemiological concept of flattening the curve and its predictions are results of data analysis and modelling. The first wave showed us how certain underlying illnesses, comorbidities, could impact the outcome of the disease. Understanding testing adequacy or lack thereof allows us to measure our preparedness, prognostic versus diagnostic ability, and shape our responses to identify, manage, and care for new cases. Epidemic outbreak data like case data, medical and treatment data can be used to understand disease pathogenesis and severity. Genome sequencing surveillance helps identify and track viral genome sequence variants in real time and the evolution of the virus. Data is most valuable when you compare it to a control. Hence, background data defining underlying characteristics of the resident population including demographics, movement data, health infrastructure, water supply system and hygiene infrastructure are critical.
Enabling access to data in a timely manner is critical for experts to analyse and provide evidence-based knowledge to guide decision making. The concept of open access to various data enables models to improve forecast and study the spread of the disease. When genome surveillance data is correlated with the magnitude of cases and their outcomes, that is, fatalities or recovery, then we can understand the transmissibility or infectivity of the virus. Geographical mapping of prevalence of mutants allows us to understand viral spread and explain recoveries or deaths in a specific area. The roll out of vaccinations can shape viral evolution and drug-treatment strategies. Surveillance through studying genome sequencing of the virus, coupled to other epidemiological data allows us to identify these connections. Outbreak analytics starting with disease surveillance systems, followed by risk assessment, management and response, results in evidence-based actionable information. The integration and analysis of multiple heterogeneous datatypes eventually would yield a holistic picture and help guide policy decisions for control and management of public health.
Part of the challenge in evidence-based decision-making pertains to the standardisation of data collection, curation, annotation and the seamless integration of data analytics pipelines for outbreak analytics. Thus, ensuring data availability and quality under operational constraints is critical. The use of data standards instils consistency, reduces errors and enables transparency. Embedded in the idea of data sharing lies the concept of data security and confidentiality.
Public outlook in recent history of large-scale attempts at data sharing through social media has been marred by concerns of privacy and security. This calls for a systemic infrastructure with built-in safeguards to ensure data encryption while preserving anonymity and ensuring privacy. In the light of the pandemic, as our dependence on data-based decisions becomes more and more critical, an urgent charter for standardised digital health data in India is required.
Rational and scientific methods necessitate data without which neither can we have information, nor knowledge or wisdom. Data sharing, and transparency and timely dissemination of data are critical to overcome the pandemic.
This column first appeared in the print edition on May 29, 2021, under the title ‘In Data, Let Us Trust’. The writer is senior principal scientist in the Biological Engineering Unit of the Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune
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