Collation of Global Health Data: A Response to COVID-19 Pandemic

Photo: towardsdatascience.com
By Jitamanyu Sahoo & Syed Mujtaba Hussain
Coronavirus (COVID-19) is expanding rapidly and has been detected in more than 190 countries globally. The absence of precise epidemiological and clinical data at the onset of the outbreak has upset the public health decision-making by several countries. At the time when health system runs on data, from disease modelers to government, from people quarantined to practicing physical distancing, all need potential data to increase the efficiency of the healthcare.
Fragmented data as we are currently witnessing in the battle against COVID-19 creates risk for individual patients and risk for care. Fragmentation also creates a risk for data privacy as disorganized and disorderly data is shared across various health actors. At the institutional level, the data fragmentation only provides a partial picture on which the health outcomes depend. Whether collecting and collating health data across jurisdictions will provide us real time epidemiological information to combat this global health crisis is yet to be seen.
In this critical period we need to first place reliance on the benefits of the collation of global health data and acknowledge the challenges it possesses before us, specifically the fragmentation problem. Second, the challenge is to guide the health data to immediate health intervention and situational awareness.
Global Health Data Today
A blizzard of health data at an increasing rate is generated by the health systems in the midst of COVID-19 pandemic across 190 countries. The proliferation of data from traditional record keeping and use of sophisticated technology attempts to give us a broader picture of the current crisis. But the varied healthcare systems across different jurisdictions have held us back from reaching a common meeting ground of data sharing. Drawing lessons from the Spanish Flu, severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), Ebola, and lethal influenza like avian and swine flu which have taken millions of lives, we cannot let COVID-19 to haunt us from our past.
Another feature which the health data offers is a substantial promise to improve the healthcare. A recent study published in Lancet (February 2020) on by Xu & Kremer on COVID-19 says, “Consistent recording of epidemiological information is important to understand transmissibility, risk of geographic spread, routes of transmission, and risk factors for infection, and to provide the baseline for epidemiological modelling that can inform planning of response and containment efforts to reduce the burden of disease.” This is essential as it will translate into multiplicity of analyses providing a consensus for intervention in the current health crisis.
Fighting Pandemics with Data Analytics
Historical approaches versus data analytics: which one will prevail? Historical approaches are slow and reliable as they go through the hospital reports, whereas data analytics such as data mining give us a more accurate picture of when and where the next pandemic is going to emerge or how to avoid one which is unfolding before us. Both the approaches do add value in any given outbreak in charting out progression for combating infectious diseases.
But novel datasets subjected to data-analytics do have enormous edge to overcome the challenges in pandemics including the current COVID-19. A case in point is BlueDot, an infectious disease data analytics firm, which has successfully predicted Zika to the US by contextualizing ecological data, world itineraries, global population data, environmental and other factors.
What do we know so far? The COVID-19 has provided us with datasets of travel history, onset dates as well as confirmation dates, symptoms and a global map to chart on. Though the current data available is updated, a lot of data are outdated as the pandemic unfolds rapidly. It must be remembered no single sector, no single country, no single doctor and no single individual can solve the current global health crisis. To make sense of the raw data, a unified behemoth effort is required by the health agencies and data firms to transmit and translate the practices on the use of data across the globe.
Resilience in Global Health Data
The inaccessibility of health data, the perennial question of privacy and the fear of medical error are all questions of vital importance when addressing global health crisis. The search for balance and need to have access to data for valuable life-saving inputs, identifying persons at risk and applying appropriate medical measures are where global health data can step in. Since the data on COVID-19 leans heavily on information found online as well as on the information released by the public health officials of each countries, it is difficult to draw analysis to address the crisis on unverified data.
For the sake of resilience in Global Health Data the World Health Organization has designed a SOLIDARITY trial which is a robust data sharing study to suppress and control the current pandemic as well as to provide data for the most effective treatment for our fight against COVID-19. However, till date only ten countries have joined the trial. SOLIDARITY will pool resources from across the countries and will provide verified and vetted information to battle COVID-19. We urge all the countries that are fighting the current global health battle to share information and be part of this global health data movement.
The unpredictability of globalised pandemics needs health data to draw counter measures. The countries today need to avail the choice of global collectivism and cohesiveness which will lead to bridging the gap of information vacuum in global health data. This will lead to predict progression which will help prevent the current and future pandemics of the 21st century.
Bio:
Jitamanyu Sahoo & Syed Mujtaba Hussain are Research Scholars working in Comparative Heath Law, Human Security & Constitutional Law.
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