Consulting in Biostatistics, Epidemiology, and Global Public Health
Modern Scientist Global (MSG) brings together a diverse team of modern scientists to provide research and advanced analytics consulting services focused on global public health. Our team has expertise in biostatistics, epidemiology, social sciences, qualitative methods, advanced quantitative analytics, econometrics, health economics, Bayesian estimation and machine learning. We offer support in all aspects of the research process including developing a research question, determining appropriate methodological approaches, sample size estimation, study design, data management and cleaning, data analysis, research dissemination products and impact opportunities.
MSG specializes in producing innovative multidisciplinary solutions to research problems using diverse mixed methodologies. We believe public health issues are complex and multi-faceted in nature, and our solutions take into account this interconnectedness.
Data Analysis: Statistical Modelling
Modern Scientist Global uses a variety of leading frequentist and Bayesian statistical methodologies to address your research question(s) thoroughly and accurately. Our specialization includes:
- Causal modelling of epidemiological data using multi-level modelling
- Multivariable hierarchical/multilevel model building incorporating the social determinants of health at distal, intermediate and proximal levels
- Times series/longitudinal models
- Survival analysis
- Assessing data missingness & imputation methods (e.g. multiple imputation)
- Individual patient data (IPD) meta-analyses using fixed and random-effect models
- Bayesian geospatial modeling
- Models for count data (e.g. Poisson/negative binomial/0-inflated)
- Sample size calculations for unique designs, and several non-parametric approaches
We use a wide range of statistical software including expertise in Stata, SAS, SPSS, R and Python.
Data Analysis: Machine Learning
Modern Scientist Global uses innovative machine learning techniques to analyze data in novel ways. We are able to develop and implement large scale algorithms, model & analyze data, and visualise findings using Python, Scala, SAS and SQL. Using machine learning as well as statistical algorithms applied to public health issues, including:
- Neural Networks
- Gradient Boosted Trees
- Random Forest
- Clustering
- Generalized Linear Models
- Simulation models
- Gaussian Mixture Models
Our team are technical experts in: linear/logistic regression, SVM, ensemble trees, random forests, clustering, gradient boosted tree. We are able to build end-to-end machine learning platforms using Python and big data technologies.
Data Analysis: Qualitative Research
We work with clients to formulate research questions and a data collection plan, including developing qualitative tools, such as semi-structured and unstructured interview guides, focused group discussion questionnaires, key informant interviews, etc. We use a variety of qualitative analysis methods, with expertise in:
- Ethnographic
- Narrative
- Phenomenological
- Grounded theory
- Case study research
Econometrics: Health Economics
Modern Scientist Global uses statistics for economics and advanced econometric modelling including time series analysis for prediction and forecasting, and panel data analysis. We conduct health economic evaluations, for example burden of disease and cost-effectiveness analysis to best answer the research topic at hand. We are able to identify and adapt existing economic models, as well as create de novo models depending on what the research question calls for.
Education/Training
Our fellowship programme engages graduate students and recent graduates from diverse disciplines including public health sciences, nutrition, economics, medicine, and data analytics. Modern Scientist Global fellows are mentored by senior scientists and assisted in the design and execution of their own custom research projects. We provide assistance with formulating a research topic, obtaining data, developing a data analysis plan, interpretation of results, and disseminating findings. The fellowship programme provides a professional development opportunity for new scientists to hone their research skills with the support of experienced scientists.
We accept fellows on a rolling basis. Current graduate students or recent graduates interested in participating in MSG’s fellowship programme are encouraged to reach out to: info@modernscientistglobal.com
Public Health Media Messaging
We use a variety of media tools to disseminate public health messages including social media (YouTube, Twitter, Instagram, etc.), video, audio, and mixed media.
Modern Scientist Global uses a diverse set of tools to spread public health information to reach audiences beyond traditional means of disseminating scientific knowledge (such as peer-reviewed published literature, reports, and conference presentations). Social media platforms (i.e. YouTube, Instagram and Twitter) are used to provide clear, brief and easily understood public health information that is accessible to many people. Follow us for updates!