A 3D print of a spike protein of SARS-CoV-2, the virus that causes COVID-19, in front of a 3D print of a SARS-CoV-2 virus particle. The spike protein (foreground) enables the virus to enter and infect human cells. Caption and photo: niaid/Flickr, CC BY 2.0.
The WHO announced in a press conference that the world might have to come to terms with the coronavirus disease as the situation looks like it may not settle down soon. Since the outbreak of COVID-19, researchers across the globe are trying to find the potential factors explaining the infections and deaths attributed to novel coronavirus in multifarious forms of researches. They have left no stone unturned to remedy this issue, but are we any closer to an antidote?
While BCG vaccination, hydroxychloroquine and a handful of other drugs are undergoing clinical trials, empirical evidence has attested to the relationships between COVID-19 deaths, non-communicable diseases morbidities, and age.
In addition, the pandemic has caught even developed nations and their better healthcare systems short, despite their economic and infrastructural advantages. While high-income countries have successfully vanquished many infectious diseases, the novel coronavirus has proved challenging to quell.
An analysis of 112 countries, each with more than 1,000 confirmed COVID-19 cases as of May 31, reveals a strong association of selected infectious as well as non-communicable diseases with underlying COVID-19 deaths.
Note: These results indicate that developing nations might have a certain resilience against the novel coronavirus. However, this hypothesis needs to be checked by clinical trials. For example one confounding factor could be that low-income countries also have poorer death registration systems, causing fewer COVID-19 deaths to be recorded than the actual figure.
The current prevalence of selected infectious diseases – tuberculosis, malaria and HIV-AIDS – indicates a strong negative association with COVID-19 deaths around the world, implying that countries with a higher prevalence of these diseases are reporting fewer deaths due to the coronavirus itself.
Countries seem to be clustered based on their incomes in a plot of the prevalence of infectious diseases versus COVID-19 mortality. The first group, closer to the vertical axis, is mostly high-income countries. The middle and low-income countries show up as the curve moves from left to right.
It’s clear that countries with higher incomes have a lower prevalence of infectious ailments but have also been reporting more deaths due to the coronavirus. This scenario gets flipped in the case of the low-income countries, which have reported fewer deaths due to COVID-19.
This pattern is inverted for chronic morbidities: a few morbidities – chronic respiratory diseases, cardiovascular diseases, cancer and diabetes – have a positive correlation with COVID-19 deaths.
Countries with maximal COVID-19 deaths lie mostly towards the top-right corner.
Countries like Singapore, Saudi Arabia, Maldives, Gabon and Djibouti have a substantial number of confirmed cases but relatively fewer deaths. The situation in Slovenia, Finland, Greece, Croatia and the Czech Republic is the reverse: the number of deaths relative to the confirmed cases is much higher.
The former set of countries has a higher prevalence of infectious diseases while the latter, of chronic morbidities.
These results indicate that countries with a higher prevalence of infectious diseases have fewer COVID-19 deaths. And countries with more non-communicable diseases have higher deaths.
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An advanced analysis might show that all countries exhibit similar associations vis-à-vis infectious and chronic diseases irrespective of the delay between a novel coronavirus outbreak.
Interestingly, among non-communicable morbidities, chronic respiratory diseases are strongly associated with higher COVID-19 mortality. And among select infectious diseases, tuberculosis has a relatively stronger association with the reduced likelihood of deaths.
Note: This article was updated on June 7, 2020, at 6:10 pm to emphasise the correlational nature of the data.
Gursimran Singh Rana is a research graduate (MPhil in Biostatistics and Demography), and Nand Lal Mishra, Alka Chauhan, and Bishwajeet Besra are research graduates (MPhil in Population Studies) – all from the International Institute for Population Sciences, Mumbai.