Lauren Maxwell, PhD, MPH
Junior Group Leader
Lauren Maxwell is an epidemiologist, data scientist, and qualitative researcher with 20 years of experience developing and managing global health research. Her interest is in bringing together teams, disciplines, methods, and geographies to address complex challenges in global health with a focus on maximizing the utility of data and samples and on maternal and child health. She leads the HIGH research group FAIR and ethical data and sample reuse. Her team works on addressing barriers to implementing the FAIR (findable, accessible, interoperable, reusable) principles for data resources, including adopting standards for capturing and exchanging health research and system data, best practice in data governance, and on ELSI barriers to data and sample reuse. She is an active member of the RDA and CODATA communities and leads the biostatistics module for HIGH MSc students.
Education
2017 PhD, Epidemiology, McGill University School of Medicine
2010 Graduate Certificate, Field Epidemiology, Gillings Global School of Public Health, University of North Carolina, Chapel Hill
2010 MPH, Gillings Global School of Public Health, University of North Carolina, Chapel Hill
2000 BA, University of Michigan, Ann Arbor
Contributions
Projects & Grants
- European Clinical Research Alliance on Infectious Diseases (ECRAID) Base, 2022-2026, Horizon Europe Funding, https://www.ecraid.eu/;
- ECRAID Plan 2021-2022, Horizon 2020 Funding;
- Reconciliation of cohort data for emerging infectious diseases (ReCoDID), 2019-2023, Horizon 2020 and CIHR Institute of Genetics funding, https://recodid.eu/;
- ZIKV IPD-MA, Wellcome Trust and WHO Health Emergencies Funding, https://www.who.int/publications/m/item/the-zika-virus-individual-participant-data-consortium-individual-participant-data-meta-analysis-initiative;
- Evaluation of data sharing platforms and repositories in COVID-19 response, 2021-2023, WHO TDR Funding
Other scientific projects and initiatives
- Templates to support the design and conduct of individual participant data meta-analyses (https://www.ipdma.co.uk/templates)
- FAIR Data for European COVID-19 Response Fall 2021 Workshop Series: https://figshare.com/collections/FAIR_Data_for_European_COVID-19_Response_Fall_2021_Workshop_Series/5740430
- FAIR and ethical data sharing for COVID-19: https://coronavirus.tghn.org/research-resources/data-sharing-covid-19/
- Research Data Alliance (RDA): https://www.rd-alliance.org/
- Toolkit for the design & conduct of IPD-MAs: https://www.ipdma.co.uk/templates
I am working in two research streams. One is violence against women and children, another is FAIR and ethical biomedical data reuse.
FAIR and ethical data and sample reuse Research Group
Publications
Data and sample reuse in pandemic response
- Zika Virus Individual Participant Data Consortium. The Zika Virus Individual Participant Data Consortium: A Global Initiative to Estimate the Effects of Exposure to Zika Virus during Pregnancy on Adverse Fetal, Infant, and Child Health Outcomes. Trop. Med. Infect. Dis. 2020. 5, no. 4: 152. Corresponding Author. https://doi.org/10.3390/tropicalmed5040152
- Carabali M, Maxwell L, Levis B The ZIKV IPD-MA Consortium, et al. Heterogeneity of Zika virus exposure and outcome ascertainment across cohorts of pregnant women, their infants and their children: a metadata surveyBMJ Open 2022;12:e064362. doi: 10.1136/bmjopen-2022-064362
- Wilder-Smith A, Wei Y, Barreto de Araujo TV, VanKerkhove M, Turchi Martelli CM, Turchi Martelli, MD, Teixeira M, Tami A, Souza J, Sousa P, Soriano-Arandes A, Soria-Segarra C, Sanchez-Clemente N, Rosenberger KD, Reveiz L, Prata-Barbosa A, Pomar L, Pelá Rosado LE, Perez F, Passos SD, Nogueira M, Noel TP, Moura da Silva A, Moreira MA, Morales I, Miranda Montoya MC, Miranda-Filho DB, Maxwell L, et. al. Understanding the relation between Zika virus infection during pregnancy and adverse fetal, infant, and child outcomes: A systematic review and individual participant data meta-analysis of Zika virus-related cohorts of pregnant women and their infants and children (IPD-MA Protocol). BMJ Open. 2019. 9, e026092. Corresponding Author. http://dx.doi.org/10.1136/bmjopen-2018-026092
ELSI barriers to data and sample reuse
- Maxwell L, Chamorro JB, Leegstra LM, Laguna HS, Miranda Montoya MC (2023) "How about me giving blood for the COVID vaccine and not being able to get vaccinated?" A cognitive interview study on understanding of and agreement with broad consent for future use of data and samples in Colombia and Nicaragua. PLOS Global Public Health 3(5): e0001253. https://doi.org/10.1371/journal.pgph.0001253
- Miranda Montoya MC, Bravo Chamorro J, Leegstra LM, Duque Ortiz D, Maxwell L (2022) A blank check or a global public good? A qualitative study of how ethics review committee members in Colombia weigh the risks and benefits of broad consent for data and sample sharing during a pandemic. PLOS Global Public Health 2(6): e0000364. https://doi.org/10.1371/journal.pgph.0000364
- Enguita‐Fernàndez C, Marban-Castro E, Mander O, Maxwell L, Correa Matta G. "The COVID‐19 epidemic through a gender lens: what if a gender approach had been applied to inform public health measures to fight the COVID‐19 pandemic?." Social Anthropology (2020). 10.1111/1469-8676.12803
Methodological innovations in data reuse
- de Jong V M T, Rousset R Z, Antonio-Villa N E, Buenen A G, Van Calster B, Bello-Chavolla O Y…Maxwell L…, et al. Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis BMJ 2022; 378 :e069881 doi:10.1136/bmj-2021-069881
- Campbell H, de Jong VMT, Maxwell L, Jaenisch T, Debray TPA, Gustafson P. Measurement error in meta-analysis (MEMA)—A Bayesian framework for continuous outcome data subject to non-differential measurement error. Res Syn Meth. 2021; 1- 20. doi.org/10.1002/jrsm.1515