Measuring the Prevalence of Toxoplasmosis and Its Socio-economic Consequences

An estimated 2 billion humans worldwide are affected by the protozoan Toxoplasma gondii. The resulting Toxoplasmosis is considered one of the most important but most neglected parasitic infections. Toxoplasmosis has been linked to behavioral alterations in humans. While rarely resulting in an acute pathology, latent infections have been associated with non-clinical outcomes such as car accidents, impulsiveness, and suicides through the pathology's influence on personality and risk-taking behaviors.

Given the economic and social impact of these consequences, it is important to have reliable estimates of Toxoplasmosis prevalence. However, current methods involve costly, time-expensive medical tests, which are not always available, especially in developing countries. Therefore, simpler, inexpensive, and easily-scalable diagnostic methods would be highly valuable. For this reason, both the CDC and the WHO consider it a priority to improve diagnostic testing of Toxoplasmosis. This includes obtaining reliable and easily-implementable estimates at the population level, which is essential to gauge the magnitude of the problem and to inform and design health policy aimed at reducing the number of infections in the population.

Therefore, the investigators aim to determine the frequency of latent Toxoplasmosis infections in the general population in a simple, quick, and inexpensive way.

The key idea of simplifying the diagnosis of this infection is that Toxoplasmosis induces specific behavioral and physiological changes. It alters the levels of neurotransmitters such as dopamine and causes a delay in muscle response time. In particular, people with RhD-negative blood type become slower when afflicted by Toxoplasmosis, while the RhD-positive sub-population does not experience a change in response times. This relation is important because, while the distribution of blood types can be determined in an inexpensive way and is already commonly known at the aggregate level (RhD-negative are 15% in Caucasians, 8% in Africans, and 1% in Asians), the actual prevalence of the Toxoplasmosis infection is underinvestigated, and the respective tests are costly and not easily deployable in large numbers (especially in developing countries). The investigators aim to leverage on the differential effects of Toxoplasmosis on response times across blood types to estimate its latent diffusion.

Response times (RT) are known to be log-normally distributed [22]. This is crucial because mixtures of log-normally distributed variables are identifiable through standard statistical methods as e.g. finite mixture models [23]. The distribution of RTs in the population is a mixture of two different types, afflicted vs. non-afflicted, and the first group should show a systematic delay in RTs compared to the latter group. A finite mixture model can then be applied to a sample of RhD-negative individuals to estimate the characteristics of the two distributions and hence quantify both the magnitude of the delay in response times as well as the size of the afflicted group.

The investigators already obtained data showing that the proposed method is able to capture interesting and economically-relevant individual characteristics between those who are imputed to be afflicted by this parasite compared to those who do not. This first investigation also passed some preliminary validation. For example, those estimated to be afflicted by Toxoplasmosis are also those who are more likely to have a cat, which is the main vector of contagion for this parasite.

In this study the investigators propose a systematic validation of the proposed method. In particular, the investigators aim to compare it agrees with a standard medical test for Toxoplasmosis infection, e.g., compare it to the presence of Toxoplasma gondii IgG Antibodies. The latter medical test requires a blood sample.