Nikita Nekliudov

I turn diverse real-world data into impactful, policy-relevant insights and Lancet-level publications.

Postdoctoral researcher at IHME/UW · MD · Oxford MSc
Available for pharma consulting engagements

0 countries modeled

0M+ claims observations

0+ publications

~0 citations

What I Do

Turning fragmented healthcare data into defensible, decision-ready evidence

Bayesian and time-series modeling (ST-GPR, MR-BRT, cascading splines)
Survey, claims, EHR, and administrative data integration
Stratified population-level estimates with full uncertainty quantification
Systematic reviews and protocol development

Synthesizing multilingual, nonstandard data into actionable evidence for decision-makers

70M+ claims observations harmonized

Policy-relevant synthesis for in-country health investment decisions
Incidence and prevalence estimation across 275 GBD causes
ICD-10-coded analytical databases, EHR integration, cause-specific correction factors

Intercultural collaboration across 4 working languages

Collaboration with Santé Publique France, Gulf CDC, Colombian clinical networks, Polish Ministry of Health
Coordinated the COMFA Consortium with 70+ experts across 30+ countries

I trained as a physician and have spent the years since building population-scale models at one of the world's leading global health institutes. My work brings clinical understanding together with rigorous data analysis, and I care about producing evidence that is reproducible, honest about its limitations, and genuinely useful to the people making decisions.

Selected Work

The Lancet

Inpatient hospital admission rates for 204 countries and territories, 1990–2023

Ready for submission · First Author

A systematic analysis for the Global Burden of Disease Study — producing stratified estimates with full uncertainty intervals across 34 years and every major world region.

Clinical Infectious Diseases

Stop COVID Cohort: Observational Study of 3,480 Patients (Sechenov University Hospital Network)

2021 · Co-first Author · ~2,000 total citations

Directed a 50-person team building a 5,000-patient ICD-10-coded analytical database during COVID — contributing individual-level effectiveness data to ISARIC and two international consortia.

The Lancet

Global age-sex-specific all-cause mortality and life expectancy, 1950–2023

2025 · Contributing Collaborator (GBD 2023 Demographics Collaborators)

Part of the flagship Global Burden of Disease demographic estimation effort — producing all-cause mortality and life expectancy estimates spanning 73 years and the full global population.

Experience & Education

Institute for Health Metrics and Evaluation (IHME), University of Washington

Postdoctoral Scholar, Clinical Informatics

Built global inpatient utilization models across 204 countries, 1990–2023, integrating 3,000+ country-years of heterogeneous health data.
Delivered population-level prevalence and incidence estimates from 70M+ claims observations for 275 GBD causes across 60+ countries.
Collaborated with Santé Publique France, Gulf CDC, Polish Ministry of Health, and Colombian clinical networks.

I.M. Sechenov First Moscow State Medical University

Project Coordinator, StopCOVID Longitudinal Cohort Study

Directed a 50-person team building a 5,000-patient prospective EHR-linked database.
Contributed individual-level real-world data to ISARIC and two international consortia; managed two British Embassy research grants.

COMFA Consortium (Core Outcome Measures for Food Allergy)

Project Coordinator & Virtual Networking Support Manager

Led international consensus protocol and two systematic reviews across 70+ global experts; co-authored published core outcome set (Allergy, 2024).

Education

Erasmus University Rotterdam

PhD, Public Health (Candidate — publication-based)

University of Oxford

MSc, Global Health Science & Epidemiology

I.M. Sechenov First Moscow State Medical University

Doctor of Medicine (MD)

Philipps-University Marburg

Visiting Student, School of Medicine

Available for consulting engagements

Real-World Evidence Study Design & Analysis

Observational study design, claims/EHR/survey data analysis, benefit-risk frameworks, regulatory-grade population estimates. Relevant for pharma and biotech medical affairs and HEOR teams.

Global Health Modeling & Evidence Synthesis

Systematic reviews, meta-analyses, Delphi consensus processes, core outcome set development, and population-level modeling for policy-facing organizations and health agencies.

Analytical Infrastructure & Reproducible Workflows

Building or auditing R/Python analytical pipelines, implementing reproducible workflows (Git-based), and translating large-scale data into publication-ready or regulatory-ready outputs.

I work with pharma, biotech, and health-policy clients on a project basis, on problems that need someone who can hold both the clinical reasoning and the statistical rigor in the same conversation. I am direct about what I can deliver and transparent about the strengths and limitations of any approach, and my focus is on producing evidence that is reproducible and actually used.