Strong negative covariation between toxoplasmosis and CoVID-19 at a global scale: a spurious indirect effect?

Abstract

Coronaviruses may exert severely negative effects on the mortality and morbidity of birds and mammals including humans and domestic animals. Most recently CoVID-19 has infected over 2,360,000 humans and killed more than 165,000. Susceptibility to this disease appears to differ markedly across different societies but the factors underlying this variability are not known. Given that toxoplasmosis exerts both direct and immune-mediated antiviral effects, we hypothesize a negative covariation between toxoplasmosis and measures of the Covid-19 pandemic across countries. We obtained aged-adjusted toxoplasmosis prevalence of pregnant women from the literature. Since the differences in the CoVID-19 morbidity and mortality may depend on the different timing of the epidemics in each country, we applied a standard measure, i.e. the date of first documented CoVID-19 in each country as a proxy of susceptibility, with a statistical control for population size effects. Using these two indices, we show a highly significant negative co-variation between the two pandemics across 86 countries. Then, considering that the wealth of nations often co-varies with the prevalence of diseases, we introduced Gross Domestic Product per capita into our model. The prevalence of toxoplasmosis co-varies negatively, while the date of first CoVID-19 cases co-varies positively with GDP across countries. Further, to control for the strong spatial autocorrelation among countries, we carried out a Spatial Structure Analyses of the relationships between the date of first COVID-19, prevalence of toxoplasmosis, and GDP. Results of this analysis did not confirm a direct causal relationship between toxoplasmosis and susceptibility to the CoVID-19 pandemics. As far as an analysis of observational data let us to suggest, it appears that the interaction between CoVID-19 and toxoplasmosis is mediated by GDP and spatial effects. This prompts the question whether the formerly known covariation between BCG vaccination and CoVID-19 might have also emerged as a spurious indirect effect.

A new, simple method of describing the COVID-19 trajectory and dynamics in any country based on Johnson Cumulative Distribution Function fitting.

“…Other obtained results showed that, excluding countries where peak of infections occurred very early and its duration was short, the higher GDP per capita, the earlier peak occurs and the first epidemic wave is shorter. This result, in turn, is similar to another very recent paper, which reported that the date of first CoVID-19 cases co-varies positively with GDP across countries, most probably due to their more intensive participation of the global tourism and traffic industries (Jankowiak et al 2020). The other example showed that the higher population density the lower the percentage of population infected during first wave of infections.…”