[Opinion] COVID‑19 pandemic: Monitoring space‑time data and learning from global experience

Statistics based opinion

COVID-19 pandemic is a ‘bad dream’ reality for the planet. Global daily news dealing with the threat of such viral infection recalls from our memory scenes from movies with similar stressful scenarios. Longitudinal information was extracted from the case in Italy and from that in South Korea during COVID-19 pandemic, by analyzing online global data. Johns Hopkins e-monitoring platform (1) periodically updated the latest information of confirmed cases and deaths globally among other data. At the time of the first observation (1), 126,660 total cases were globally confirmed, 4,641 total deaths were registered and 68,305 were totally recovered. One month later (2), 1,783,941 total cases were confirmed, 109,312 total deaths were registered and 405,972 were totally recovered. Five months later (3), 20,306,856 total cases were reported, 741,723 total deaths were registered and 12,602,544 were totally recovered.

Observing numbers and thinking that, beyond the arithmetics, people suffer, a couple of points appear to be demanding in their content analysis. The case in Italy and the case in South Korea are extremely different in their geographical, environmental, social, cultural and racial characteristics, with 12,462 confirmed cases and 7,869 respectively, on 12th March 2020(1). On that date, Italy and South Korea were listed among COVID-19 most threatened countries. One month later, Italy recorded 152,271 confirmed cases and South Korea 10,512 cases (2). At five months Italy registered 251,237 confirmed cases and South Korea 14,714 cases (3). Epidemic burden was different for the two countries and the gap evolved by further opening. During our first e-data observation (1), by extracting the rates of total deaths per total confirmed cases at a specific time period (4), we noted that Italy reported a case fatality ratio (CFR) of 6.6% (827/12,462) and South Korea presented a CFR of 0.8% (66/7,869). Global total rate was calculated at 3.6%. One month later, Italy reported a CFR of 12.8% (19,468/152,271) and South Korea a rate of 2.0% (214/10,512). Global total rate was calculated at 6.1% (2). Five months later, Italy reported a CFR of 14.0% (35,215/251,237) and South Korea presented a CFR of 2.0% (305/14,714). Global total rate was calculated at 3.6% (3). All figures from Italy and South Korea diverge in a consistent manner from total global rates. Of course, these are non-adjusted per age, sex or other feature rates and attention is brought to readers to avoid misunderstandings, especially when data from different countries or regions are compared (5). At the time of publication absolute numbers will definitely differ. However, CFRs in the two countries are likely to evolve without surprising changes.

As evidence becomes more palpable (6,7), some explanations were given on the poor situation, reporting that the control of infectious wave was totally lost early on, and that population is aged and thus vulnerable (8), since deaths are more common among elderly or frail. On the the contrary, extensive diagnostic testing performed in South Korea was seen as a really protective measure (9). With great respect to the Italian people, we are extremely cautious not to deal with other explanations of this phenomenon observed across the two countries. Noxious or protective systemic factors can occur and play a synergistic role towards a more positive or negative scenario (6,10). We cannot exclude other causes that are related to administration model and local health system parameters by creating a different reaction to emergency (11), citizens' compliance, public health surveillance tactics and readiness (5,12,13), health system adaptation (14), articulation of services from primary care to intensive care flow handling (11), level of health sector readiness to absorb an exponential ‘pressure’ and, finally, system capacity to ‘resist’ in terms of time and effort endurance. A safe conclusion is that both scenarios, ‘bad’ or ‘good’, are simultaneously likely to occur at moment ‘zero’ and arithmetical or geometrical death rate figures are related to the scenario that prevails. It appears that ‘epi-epidemic’ parameters (15) can strongly influence population health during COVID-19 pandemic, and the good or bad scenario seems to endure in terms of CFRs over time.

Acknowledgements

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No funding was received.

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Authors' contributions

EKS, GS, DAS and CL each contributed substantially to this report. All authors read and approved the final manuscript.

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Patient consent for publication

Not applicable.

Competing interests

DAS is the Editor-in-Chief for the journal, but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision, for this article. The other authors declare that they have no competing interests.

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