We are not at war; we are in a pandemic and in data that we trust. The COVID-19 pandemic has highlighted globally how important data is to governments in decision-making. The power of this data was seen early on in evidence-based response and decision-making in countries like South Korea. The modern response to pandemics has focused on harnessing all available data to inform policy action in real time. It is quite evident that epidemiological data is of paramount importance for the targeting and implementation of public health control measures in a timely manner. We have never had a consistent statistical picture of public health in India, nor of the provision of health services. There has never been a greater moral imperative or need in India for transparency and data sharing than today.

The need for timely data sharing lies in its usefulness through analysis and its power lies in its interpretation. The current pandemic is a prime example. It revealed the need for continuous and repeated monitoring of the number of cases, deaths and recoveries. The epidemiological concept of flattening the curve and its predictions are the results of data analysis and modeling. The first wave showed us how certain underlying diseases, co-morbidities, can impact disease outcomes. Understanding the adequacy or lack of testing allows us to measure our preparedness, our prognostic ability versus our diagnostic ability, and shape our responses to identify, manage, and cure new cases. Data on disease outbreaks such as case data, medical and treatment data can be used to understand the pathogenesis and severity of the disease. Monitoring genome sequencing allows real-time viral genome sequence variants to be identified and tracked and virus evolution. Data is more valuable when you compare it to a control. Therefore, basic data defining the underlying characteristics of the resident population, including demographics, movement data, health infrastructure, water supply system, and hygiene infrastructure are essential.

Allowing timely access to data is essential for experts to analyze and provide factual knowledge to guide decision making. The concept of open access to various data allows models to improve predictions and study the spread of disease. When genome surveillance data is correlated with the magnitude of cases and their outcome, i.e. death or recovery, then we can understand the transmissibility or infectivity of the virus. Geographic mapping of mutant prevalence allows us to understand viral spread and explain recoveries or deaths in a specific area. The deployment of vaccinations can shape viral evolution and drug treatment strategies. Monitoring by studying the sequencing of the genome of the virus, coupled with other epidemiological data, allows us to identify these connections. Analysis of outbreaks, starting with disease surveillance systems, followed by risk assessment, management and response, results in actionable evidence-based information. The integration and analysis of several types of heterogeneous data would eventually provide a holistic picture and help guide policy decisions for the control and management of public health.

Part of the challenge in evidence-based decision making is standardizing data collection, curation, annotation, and seamless integration of data analysis pipelines for epidemic analysis. Thus, it is essential to guarantee the availability and quality of data under operational constraints. The use of data standards instills consistency, reduces errors and enables transparency. The concept of data security and privacy is rooted in the idea of ​​data sharing.

The public perspective in the recent history of large-scale attempts to share data through social media has been marred by concerns about privacy and security. This requires a systemic infrastructure with built-in safeguards to ensure data encryption while maintaining anonymity and ensuring confidentiality. In light of the pandemic, as our reliance on data-driven decisions becomes increasingly critical, an urgent charter for standardized digital health data in India is needed.

Rational and scientific methods require data without which we also cannot have information, knowledge, or wisdom. Data sharing, transparency and timely dissemination of data are essential to overcome the pandemic.

The author is Senior Scientist at the Biological Engineering Unit of the Division of Chemical Engineering and Process Development, CSIR-National Chemistry Laboratory, Pune