Internship in Biostatistics (Master I students only)

Schistosomiasis is a parasitic disease caused by blood flukes of the genus Schistosoma with an acute phase followed by a chronic phase due to repeated exposure to the parasite if untreated. The main species causing human infections are Schistosoma mansoni and Schistosoma haematobium In Africa mainly and S. japonicum and S. Mekongki in Asia. Approximately 779 million people are at risk of acquiring the infection. In 2021, an estimated 136 million school-aged children and 115 million adults worldwide needed preventive chemotherapy (PC) in 51 countries. 

The main hurdle to the WHO strategy to eliminate Schistosomiasis is based on the prevalence of the disease are the diagnostic tests used to detect the presence of the parasite, which are inaccurate in terms of sensitivity especially when it comes to low prevalence. For S. mansoni, the conventional reference standard diagnostic test is duplicate Kato-Katz thick smears (KK) and the main parasitological method for detecting infection with S. haematobium is urine filtration and microscopy. These methods have been available for decades and are widely implemented because of their simplicity and low cost, but lack sensitivity. 

Meta analysis of available data on diagnostic tools accuracy is a means to evaluate current knowledge and to define research needs in this topic. Aggregated data from articles are usually pooled and analysed with random effects methods but these are less accurate when it comes to jointly evaluate 2 criteria such as sensitivity and specificity. In that case bayesian models may be used.

Objectives

The objectives of the current work are to perform litterature seach on the diagnostic tools to detect the 4 species of parasites responsible for Schistosomiaisis and carry out a meta analysis for one species that will compare the sensitivity (Se) and specificity (Sp) by using meta analysis methods.

The steps to carry out the research are:

• Litterature search on scientific articles on diagnostic tools for schistosomiasis
• Selection of articles
• Extraction of data from articles
• Analysis of data with review manager (Cochrane collaboration)
• Analysis of data with Bayesian models

Training and research environment

Within the Department of Medical Information at the Centre of Competences for Methodology and Statistics, the candidate will work in collaboration with biostatisticians and methodologists. The LIH documentalist will provide training and support to enable the intern to define a search methodology of the literature ion the subject.

Students have the opportunity to work in an interdisciplinary & international scientific environment, benefitting from diverse exchanges with other students and scientists in and across the department, and allowing further training in a variety of health-related domains, fostering the acquisition of horizontal skills around presentation & communication skills, scientific English, statistical data evaluation.

Required Profile

• Current master student in statistics, mathematics, applied mathematics or data science
• Good knowledge and hands-on experience of SAS or R
• Prior experience with data analysis of medical data
• Good writing skills in English
• Good organizational skills
• High motivation and discipline to work in a multi-disciplinary team.

Main activities

• Litterature search on diagnostic tools for shistosomiasis
• Use of Revman to update data on the systematic review
• Extraction of data to further use with Network mea-analysis

Scientific contact: 

Dr Michel Vaillant
Centre of Competences for Methodology and Statistics
Department of Medical Informatics
Email: michel.vaillant@lih.lu

Gender Equality

The LIH is an equal opportunities employer. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. The LIH is attentive to gender representation among its leadership staff and aims to eliminate obstacles to the recruitment and promotion of female leaders and their career development.