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Quality Data Needed to Fight COVID19

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As many countries and international organisations grapple with the challenges of the Corona Virus COVID19, one thing becomes crystal clear: we need quality data. As countries collect data, and World Health Organisation and others try to make sense of it, they face the challenges associated with inconsistent and incomplete data. Basic parameters needed to estimate the impact of COVID19 (such as its fatality rate and Basic Reproduction Number) are extremely hard to determine when every country has different criteria for patient testing, different analytic methods and different reports. It is a small wonder that parameters reported by different countries vary widely.

One country that invested a lot in data integration and communication is Taiwan (see Further Reading below). Taiwan, which was predicted to be the second most infected country due to its proximity to China and the frequent travel to COVID-19 hotspots in China, has been able to control the infection effectively. It is now only the 10th most infected country. Another way to look it at is that about 90% of Corona Virus infections in Taiwan have been prevented.

Further reading: Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing

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