the-lancet-public-health

The Lancet Public Health (the-lancet-public-health)

Journal positioning

The Lancet Public Health is a Lancet specialty journal for population and public-health

research — population-level interventions, health policy and systems, epidemiology and

disease burden, and global-health and health-equity research with population-level

relevance. It favors **rigorous studies whose unit of interest and consequence is the

population, not the individual patient**: large-scale epidemiology, policy and natural

experiments, modelling with clear public-health decision value, and interventions

addressing inequalities or the social determinants of health. The defining misfit is an

individual-level clinical study (a drug or device effect in patients) with no

population, policy, or equity dimension — that belongs in a clinical journal. This skill

is a fit / venue-selection / re-framing aid; it is not clinical or regulatory advice

and does not replace the journal's current instructions for authors. Before submitting,

re-check the live The Lancet Public Health author instructions.

When to trigger

• The author names The Lancet Public Health for a population-health, epidemiology, or

policy study and wants a fit/framing check.

• A study must be re-framed around a population-level intervention, burden, or policy

question with equity relevance.

• The author is choosing between The Lancet Public Health, a clinical specialty journal,

and general medicine.

• The author needs the journal's reporting-guideline, registration, and desk-reject

expectations for population/policy evidence.

Scope & topic fit

• Population-level interventions and policy/natural experiments (taxation, regulation,

screening programmes, vaccination, public-health service delivery).

• Epidemiology, disease-burden, surveillance, and risk-factor studies at population

scale, including global and comparative analyses.

• Health-systems, health-services, and health-economics research with population-level

decision relevance.

• Health-equity, social-determinants, and inequalities research with population-level

framing and policy implication.

• Modelling and forecasting studies (transmission, burden, intervention impact) with

transparent assumptions and public-health decision value.

• Systematic reviews and meta-analyses answering a focused population-health or policy

question.

Method & evidence bar

• Studies must have a clear population-level question and an appropriate population

denominator; individual-level clinical endpoints alone do not establish public-health

relevance.

• The applicable reporting guideline and completed checklist are expected: STROBE for

observational studies, CONSORT (incl. cluster-CONSORT) for trials, PRISMA for reviews,

GATHER for global-health estimates, and modelling-reporting standards where relevant.

• Trials and pre-specified evaluations require prospective registration; protocols and

analysis plans are expected, with cluster/stepped-wedge design detail where used.

• Observational and natural-experiment claims must address confounding, secular trends,

ecological bias, and missing data; causal language must match the design.

• Modelling studies must state assumptions, perform sensitivity/uncertainty analysis,

and report data sources transparently; code/data sharing strengthens the submission.

• Effect estimates need uncertainty intervals and, where relevant, equity-stratified or

absolute population-impact measures.

Structure & house style

• Lancet specialty format with a structured summary and a Research in context /

evidence-before-this-study panel; re-check current article types and limits on the

live guide.

• The introduction frames the population-health or policy gap; the discussion states the

policy or public-health consequence and limitations plainly.

• A STROBE/CONSORT/PRISMA flow diagram and (for estimates) GATHER reporting are expected

where applicable; tables/figures follow Lancet statistical-reporting standards.

• The role of the funding source statement and a data-sharing statement are expected;

appendices carry protocol/model specification, full methods, and additional analyses.

Official-submission checklist

• Before giving submission-ready advice, read ../../resources/source-basis.md and

../../resources/official-source-map.md; start from the ICMJE/EQUATOR and Lancet

anchors, then cite the current The Lancet Public Health page you checked.

• Search the live site for "The Lancet Public Health information for authors" and follow

the current version.

• Re-check article types, structured-summary and Research in context format, and

word/reference/figure limits.

• Confirm registration where applicable, the reporting checklist

(STROBE/CONSORT/PRISMA/GATHER), protocol/model specification, role-of-funding-source,

and data/code-sharing statement.

• Re-check IRB/ethics and consent or data-governance approvals, ICMJE authorship and

conflict-of-interest disclosure, funding, and AI-use disclosure.

• If the live official instructions conflict with this skill, the official instructions

win.

Pre-submission self-check

• [ ] The study has a genuine population-level question, denominator, and policy/equity consequence.
• [ ] The correct reporting checklist (STROBE/CONSORT/PRISMA/GATHER) is completed and attached.
• [ ] Trials/evaluations are registered where applicable; protocol or model specification is provided.
• [ ] Confounding, secular trends, ecological bias, and missing data are addressed; causal language matches the design.
• [ ] Modelling assumptions, uncertainty, and data sources are transparent; code/data sharing is planned.
• [ ] Ethics/data-governance approvals, ICMJE disclosures, role-of-funding-source, and a data-sharing statement are prepared.

Common desk-reject triggers

• Individual-level clinical studies with no population, policy, or equity dimension.
• Small or local descriptive surveys with no generalizable population-health implication.
• Modelling with opaque assumptions, no sensitivity analysis, or undocumented data sources.
• Ecological analyses with overstated individual-level causal claims.
• Missing reporting checklist, registration (where applicable), or data-governance approvals.
• Narrow scope without international or policy relevance, better suited to a regional or clinical venue.

Re-routing decision

• Individual-level clinical trial or patient-outcome focus → the relevant clinical specialty journal or general medicine (jama / NEJM / The Lancet in the natural-science bundle).
• Population mental-health and psychiatric epidemiology dominant → the-lancet-psychiatry.
• Diabetes/obesity population research with a clinical-metabolic core → the-lancet-diabetes-and-endocrinology.
• Respiratory population/clinical research with a respiratory endpoint → the-lancet-respiratory-medicine.
• Cancer epidemiology with a clinical-oncology endpoint → annals-of-oncology / jama-oncology.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] The Lancet Public Health
[Specialty tags] <2–3 closest population-health/policy/epidemiology topics>
[Study design / reporting guideline] <observational-STROBE / cluster-RCT-CONSORT / review-PRISMA / estimates-GATHER / modelling>
[Method/evidence] <population-level question, denominator, confounding/assumptions — does it clear the policy-relevance bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / registration / checklist / role-of-funding / ethics-data-governance / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>