Measuring the Prevalence of Toxoplasmosis and Its Socio-economic Consequences (EconToxo)

May 16, 2023 updated by: Carlos Alós-Ferrer, University of Zurich
The investigators propose a fast and inexpensive procedure to determine the prevalence of the Toxoplasmosis infection (Toxoplasma Gondii) in the general population, using response times in a cognitive task instead of costly medical tests. Therefore, the investigators aim to measure the prevalence of Toxoplasmosis and its socio-economic consequences in the general population.

Study Overview

Status

Not yet recruiting

Conditions

Detailed Description

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.

Study Type

Observational

Enrollment (Anticipated)

120

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Non-Probability Sample

Study Population

Participants will be recruited among the student population of the University of Zürich according to the established procedures of the SNS Laboratory.

Description

Inclusion Criteria:

  • Ability and willingness to participate in the study.
  • Declaration of consent.
  • Having RhD-Negative blood. This is because only RhD-negative blood type become slower when afflicted by Toxoplasmosis. Hence, the proposed analysis can only be performed on RhD-Negative people.
  • Good English language skills (at least C1, to ensure understanding of all instructions and the declaration of consent).

Exclusion Criteria:

  • Inability to give the declaration of consent.
  • Any neurological disorders
  • Reduced general health / chronic diseases (e.g. autoimmune disease, severe cardiovascular diseases, insulin-dependent diabetes, severe depression); chronic pain disorders

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Toxoplasmosis positive
Healthy students with RhD-Negative blood with Toxoplasma gondii IgG Antibodies
Testing for the presence of Toxoplasma gondii IgG Antibodies in participants blood.
Toxoplasmosis negative
Healthy students with RhD-Negative blood without Toxoplasma gondii IgG Antibodies
Testing for the presence of Toxoplasma gondii IgG Antibodies in participants blood.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Presence of Toxoplasma gondii IgG Antibodies
Time Frame: 6 months
Presence of Toxoplasma gondii IgG Antibodies
6 months
Classified as afflicted by Toxoplasma gondii using response times
Time Frame: 6 months
Classification based on a reaction-time task of whether the participant is considered as afflicted by Toxoplasma gondii.
6 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Field of study
Time Frame: 6 months
Which major the participant studied.
6 months
Accidents
Time Frame: 6 months
Number of accidents (work related or traffic accidents) the participant experienced.
6 months
Owning Pets
Time Frame: 6 months
Which pets the participant owns or owned.
6 months
Income
Time Frame: 6 months
The yearly income (in Swiss Francs).
6 months
Alcohol consumption
Time Frame: 6 months
Average units of alcohol consumed in a week.
6 months
Big 5 personality trait
Time Frame: 6 months
Score in the Big 5 personality trait scale from Gosling et al. (2013). It is a 10-items scale subdivided in 5 traits (2 items for each trait): Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness to Experiences. Each item is evaluated using a 7-points Likert scale with the following labels "Disagree Moderately", "Disagree a little", "Neither agree not disagree", "Agree a little", "Agree moderately", "Agree strongly". For each trait one of the two items is reversely scored. For each of the 5 traits the score of the two items is added, hence it can go from 2 to 14. Higher scores on each of the scales correspond higher closeness to that personality trait, e.g., more agreeable.
6 months
Sensation Seeking scale
Time Frame: 6 months
Score in the Sensation Seeking scale (Cook et al., 2015). This scale consists of 10 binary choices where participants are asked to choose which option best describes their likes or the way they feel. One of the two options is associated with a higher Sensation Seeking score. Items 2, 3, 5, 6, and 8 are reversely scored. The answers from the single items are added to obtain the total score, which can go from 0 to 10. Higher scores indicate more sensation seeking.
6 months
Cognitive Reflection Test
Time Frame: 6 months
Score in the Cognitive Reflection Test from Toplak, West, and Stanovich (2014). In this 7-item scale each item asks for the answer to a mathematical or logical problem in an open-entry format or as multiple-choice question. The score for this scale is the sum of the correct answer to the 7 items, hence it goes from 0 to 7. Higher scores indicate higher cognitive reflections.
6 months
Risk aversion
Time Frame: 6 months
Measure of risk aversion (number from 1 to 10, Falk et al., 2018). A single question asking the participants' attitude toward risk. 1 means "not willing to take risks" and 10 means "very willing to take risks". Higher values mean more risk tolerance.
6 months
Time preference
Time Frame: 6 months
Measure of time preference (number from 1 to 10, Falk et al., 2018). A single question asking the participants' patience. 1 means "not willing to give up something today" and 10 means "very willing to give up something today". Higher values mean more patience.
6 months
Self-control
Time Frame: 6 months
Score in the self-control scale from Tangney, Boone, and Baumeister (2018). It is a 13-item scale evaluated using a 5-point Likert scale with two labels at the extreme of the scale 1="Not at all" and 5="Very much". Items 2/5, 7, 9/11 are reversely scored. The score is obtained by adding the score of the single items. Higher values indicate more self control.
6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

June 26, 2023

Primary Completion (Anticipated)

July 30, 2023

Study Completion (Anticipated)

July 30, 2023

Study Registration Dates

First Submitted

April 26, 2023

First Submitted That Met QC Criteria

May 5, 2023

First Posted (Actual)

May 16, 2023

Study Record Updates

Last Update Posted (Actual)

May 18, 2023

Last Update Submitted That Met QC Criteria

May 16, 2023

Last Verified

May 1, 2023

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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