The Data Management and Biostatistics Core will build the physical infrastructure, software solutions and human resources for a centralized, web-based fully GCP-compliant data management system and a program-wide data warehouse and provide support for the analyses of complex longitudinal data systems. The Core will serve the data storage and analytic needs of the 3 Research Projects conducted in all malaria endemic sites ofthe ICEMR and interact directly with the Molecular Diagnostics Core that will create an archive of biological samples and perform diagnostic tests related to malaria infections of humans and mosquitoes.
The Specific Aims are to: 1: Set up a robust and comprehensive, centralized, web-based fully GCP-compliant data management system for ICEMR program 2;Create a collaborative environment between Papua New Guinea and participating sites in Solomon Islands and other ICEMR institutions and countries for the design, development, testing, and implementation of the data management system 3: Establish a centralized data repository that provides secure access to researchers and collaborators 4: Develop adequate data analysis tools for the analyses of complex longitudinal datasets (with multiple endpoints) 5: Analyze data and prepare results in a timely manner for interim analyses, publications, and presentations 6;Ensure regulatory compliance of data collection management 7: Provide training and development opportunities to Papua New Guinea and Solomon Islands in the areas of epidemiology, biostatistics, and database architecture The core will be directed by Prof. John Aponte from CRESIB, where he has organized similar data systems for large scale malaria epidemiology studies and clinical trials in Sub-Saharan Africa, and supported by Dr. Ivo Mueller, leader ofthe Epidemiology Project, and Thomas Adiguma, senior data manager at PNGIMR. Infrastructure and capacity building will be accomplished by the provision of training and resources in the fields of epidemiology, biostatistics, and dataset architecture.

Public Health Relevance

Sophisticated relational database management, compliance with Good Clinical Practice and advanced biostatistical analysis are all essential to the conduct of ethical research related to the control and elimination of malaria. The Data Management and Biostatistics Core will serve this essential function forthe ICEMR.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI089686-04
Application #
8494545
Study Section
Special Emphasis Panel (ZAI1-AWA-M)
Project Start
2013-07-01
Project End
2017-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
4
Fiscal Year
2013
Total Cost
$49,857
Indirect Cost
$8,179
Name
Case Western Reserve University
Department
Type
DUNS #
077758407
City
Cleveland
State
OH
Country
United States
Zip Code
44106
Lerch, Anita; Koepfli, Cristian; Hofmann, Natalie E et al. (2017) Development of amplicon deep sequencing markers and data analysis pipeline for genotyping multi-clonal malaria infections. BMC Genomics 18:864
Messerli, Camilla; Hofmann, Natalie E; Beck, Hans-Peter et al. (2017) Critical Evaluation of Molecular Monitoring in Malaria Drug Efficacy Trials and Pitfalls of Length-Polymorphic Markers. Antimicrob Agents Chemother 61:
Fran├ža, Camila T; Li Wai Suen, Connie S N; Carmagnac, Amandine et al. (2017) IgG antibodies to synthetic GPI are biomarkers of immune-status to both Plasmodium falciparum and Plasmodium vivax malaria in young children. Malar J 16:386
Schofield, Louis; Ioannidis, Lisa J; Karl, Stephan et al. (2017) Synergistic effect of IL-12 and IL-18 induces TIM3 regulation of ?? T cell function and decreases the risk of clinical malaria in children living in Papua New Guinea. BMC Med 15:114
Hofmann, Natalie E; Karl, Stephan; Wampfler, Rahel et al. (2017) The complex relationship of exposure to new Plasmodium infections and incidence of clinical malaria in Papua New Guinea. Elife 6:
Jain, Aarti; Taghavian, Omid; Vallejo, Derek et al. (2016) Evaluation of quantum dot immunofluorescence and a digital CMOS imaging system as an alternative to conventional organic fluorescence dyes and laser scanning for quantifying protein microarrays. Proteomics 16:1271-9
Hupalo, Daniel N; Luo, Zunping; Melnikov, Alexandre et al. (2016) Population genomics studies identify signatures of global dispersal and drug resistance in Plasmodium vivax. Nat Genet 48:953-8
Koepfli, Cristian; Nguitragool, Wang; Hofmann, Natalie E et al. (2016) Sensitive and accurate quantification of human malaria parasites using droplet digital PCR (ddPCR). Sci Rep 6:39183
Guo, Suqin; He, Lishan; Tisch, Daniel J et al. (2016) Pilot testing of dipsticks as point-of-care assays for rapid diagnosis of poor-quality artemisinin drugs in endemic settings. Trop Med Health 44:15
de Assis, Rafael Ramiro; Ludolf, Fernanda; Nakajima, Rie et al. (2016) A next-generation proteome array for Schistosoma mansoni. Int J Parasitol 46:411-5

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