Does the pathogenesis of SARS-CoV-2 virus decrease at high-altitude?

Abstract

In the present study we analyze the epidemiological data of COVID-19 of Tibet and high-altitude regions of Bolivia and Ecuador, and compare to lowland data, to test the hypothesis that high-altitude inhabitants (+2,500 m above sea-level) are less susceptible to develop severe adverse effects in acute SARS-CoV-2 virus infection. Analysis of available epidemiological data suggest that physiological acclimatization/adaptation that counterbalance the hypoxic environment in high-altitude may protect from severe impact of acute SARS-CoV-2 virus infection. Potential underlying mechanisms such as: (i) a compromised half-live of the virus caused by the high-altitude environment, and (ii) a hypoxia mediated down regulation of angiotensin-converting enzyme 2 (ACE2), which is the main binding target of SARS-CoV-2 virus in the pulmonary epithelium are discussed.

Keywords: COVID-19; Hypoxia; Lung remodeling; UV.

Fig. 1

A) Geographic and altitudinal distribution of COVID-19 pandemic in China. The blue dots represent COVID-19 positive cases. Geographic coordinates were retrieved from the real-time database elaborated by Xu et al. on March 30th (Xu et al., 2020). Altitude data were extracted from the digital elevation model of BIOCLIM. B) Geographic altitudinal distribution of COVID-19 pandemic in Bolivia. The blue dots represent COVID-19 positive cases. Geographic coordinates were included following the method used by Xu et al. on March 30th (Xu et al., 2020). Altitude data were extracted from the digital elevation model of BIOCLIM. This data is available at https://docs.google.com/spreadsheets/d/1sSK9-n0uoxzcRRQgQe2EYhDXb2zPea86gj1TjJnC9eo/edit?usp=sharing. In order to maintain this article up to date, the daily updated version of this graphic will be available in the following link until the end of the pandemic: https://altitudeclinic.com/blog/2020/04/covid-2-bolivia/.

Fig. 2

Altitudinal distribution of COVID-19 pandemic in the World. The altitude for positive cases of COVID-19 was calculated using de digital elevation model of BIOCLIM and the geographic data from the real-time database elaborated by Xu et al. on March 31st (Xu et al., 2020).