STROME-ID (Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases)

What it is

— STROME-ID (Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases) is a 42-item reporting checklist, published as an extension of the STROBE statement by Field, Cohen, Struelens et al. (Lancet Infectious Diseases, 2014). It does not replace STROBE; it adds items specific to studies that use molecular data — pathogen genotyping, whole-genome or amplicon sequencing, phylogenetic/phylodynamic inference — to make claims about transmission chains, strain identity, clonality, or antimicrobial-resistance mechanisms. Its purpose is to make the molecular layer of an infectious-disease epidemiology study transparent and reproducible: which isolates were sampled and how representatively, which typing/sequencing platform and bioinformatics pipeline (with versions) produced the genotypes, how genetic distance was thresholded into "linkage," and how phylogenetic and sampling uncertainty was propagated into the epidemiological conclusions. It is hosted and maintained as a STROBE extension within the EQUATOR Network.

When to use

— Apply STROME-ID when reporting an observational study (cohort, case-control, cross-sectional, surveillance, or outbreak investigation) in which molecular characterization of a pathogen is part of the inference — for example, reconstructing a transmission network from sequenced isolates, attributing cases to a clone or lineage, estimating the genetic relatedness that defines an outbreak, or linking a resistance genotype to a clinical outcome. It is a journal-stage reporting checklist (peer-reviewed manuscript) and is relevant to public-health/agency surveillance reports (e.g., ECDC/ENCePP-adjacent molecular surveillance, outbreak post-mortems). Decision rule for choosing the right STROBE family member: use plain STROBE for an observational ID study with no molecular component; use STROME-ID the moment genotyping/sequencing data drive a substantive claim; use RECORD-PE / HARPER / ENCePP instead when the study is a routinely-collected-data pharmacoepidemiology study (drug safety/effectiveness in claims or EHR), even if the outcome is an infection — those guidelines, not STROME-ID, govern that design. (Note the easily-confused sibling STROBE-ME, a separate molecular-epidemiology extension oriented toward non-communicable/biomarker exposures; STROME-ID is the infectious-disease-specific one.)

What it requires

— On top of every STROBE item, STROME-ID enforces reporting domains that are the failure points of molecular ID studies: (1) Sampling and representativeness of isolates — what fraction of incident cases were genotyped, how isolates were selected, and the risk that the sampled isolates are not representative of the transmission process (the molecular analogue of selection bias). (2) Laboratory and bioinformatics transparency — the typing/sequencing method, platform, coverage/depth, quality-control thresholds, reference genome, variant-calling and assembly pipeline, and software versions — so the genotypes are reproducible. (3) Definition of genetic linkage — the explicit distance metric and threshold (e.g., SNP cutoff) used to call two isolates "linked," and its justification, because that threshold creates the transmission network the study then analyzes. (4) Phylogenetic and temporal inference — the model, assumptions, and uncertainty (posterior support, bootstrap, dating intervals) carried through to the epidemiological conclusion. (5) Case/exposure ascertainment and time — consistent with STROBE, how cases were defined and how time/follow-up was handled, which in transmission studies interacts with sampling completeness. Several of these items are causal-claim safeguards: a SNP threshold and a phylogeny do not by themselves prove who infected whom, and STROME-ID forces the authors to state the uncertainty rather than assert linkage.

When NOT to use — limitations and common misapplications

— STROME-ID is a reporting checklist, not a risk-of-bias instrument and not a quality score; a fully STROME-ID-compliant paper can still report a biased or non-causal analysis — completing the checklist documents the molecular methods, it does not validate the transmission inference. Concrete failure modes: (1) Wrong guideline for the design — using STROME-ID for an ID study with no molecular data (use plain STROBE), or for a drug-safety/effectiveness study in claims/EHR where an infection is merely the outcome (use RECORD-PE/HARPER/ENCePP). (2) Confusing the siblings — using STROME-ID where STROBE-ME (the general molecular-epidemiology/biomarker extension) is the right tool, or vice versa. (3) Checklist-as-theater on the molecular items — stating that isolates were "sequenced and analyzed" without reporting depth, QC thresholds, the SNP/linkage cutoff, the pipeline, or version numbers is non-compliance dressed as compliance; the whole point of the extension is that those details are the analysis. (4) Treating the SNP threshold as ground truth — reporting a single distance cutoff as if it deterministically defines transmission, without sensitivity to the threshold or to incomplete sampling, defeats the inference the checklist exists to discipline. (5) Mistaking the checklist for an appraisal of the included evidence — STROME-ID governs one primary study's report, not a synthesis (use PRISMA/AMSTAR families) and not a formal bias appraisal (use a non-randomized RoB tool).

How it maps to this catalog

— This catalog is pharmacoepidemiology- and HEOR-heavy, so the molecular core of STROME-ID — phylogenetic/phylodynamic inference, sequencing QC and bioinformatics pipeline versioning, SNP-distance transmission-linkage thresholds, and pathogen-isolate sampling representativeness — has no direct concept implementation here, and a reviewer should be told that plainly rather than be pointed at wrong-domain pharmacoepi concepts. What does map are the generic, cross-domain reporting disciplines STROME-ID inherits from STROBE and adapts: - Observational design scaffolding the checklist reports against: cohort-prospective, cohort-retrospective, and case-control. - Case/outcome definition and validation (the epidemiological-ascertainment items): algorithm-validation, outcome-algorithm-construction-rwe, diagnosis-phenotype-algorithm-1ip-2op-time-window-rwe, and (for record-based ID case-finding) ehr-phenotyping-algorithms-rwe. - Data-fitness and source-representativeness (the isolate-sampling/representativeness analogue): fit-for-purpose-data-assessment-rwe and disease-registry (surveillance/registry substrates for ID studies). - Attrition/completeness and signal-finding context: attrition-and-loss-to-follow-up-rwe and signal-detection (outbreak/surveillance case ascertainment). Use these concepts to satisfy the generic reporting items; satisfy the molecular items (sequencing QC, linkage thresholds, phylogenetic uncertainty, isolate sampling) directly from the STROME-ID statement and the bioinformatics literature, since this catalog does not yet implement them.

Applied note (surveillance / registry / record-based ID RWE)

When an infectious-disease study is built on routinely collected records (a surveillance registry, EHR-based case-finding, or linked laboratory data), report the case-ascertainment algorithm and its validity (PPV/sensitivity) under the catalog's algorithm-validation and phenotype concepts, document how completely cases were captured and what was lost (attrition/observable-time), and separately — outside this catalog — report the isolate sampling fraction, sequencing depth/QC, the genetic-distance threshold defining linkage, and the phylogenetic uncertainty, exactly as STROME-ID requires. Conflating "we identified cases from records" with "we sequenced a representative sample of those cases" is the central misapplication the extension was written to prevent.