作者
Shruti Murthy,Christian S. Marchello,Marieke Emonts,Suzanne Faigan,Jason R. Andrews,Marina Antillón,George E. Armah,Adwoa Bentsi-Enchill,Megan Birkhold,Robert F. Breiman,Megan E. Carey,Helen Dale,Christiane Dolecek,Amanda J. Driscoll,Denise O. Garrett,M. Lowe Gordon,Lee M. Hampton,Kathryn E. Holt,Justin Im,Leslie P Jamka
摘要
Prevalence and incidence are fundamental metrics with numerous applications in epidemiology. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline lacks specific items for reporting studies of disease prevalence or incidence. To address this gap, the STROBE Enhanced Prevalence and Incidence Criteria (STROBE EPIC) extension was developed in accordance with established methods for reporting guideline development. The authors generated an initial list of reporting items, conducted a modified Delphi process, and convened a face-to-face consensus meeting to confirm the need for a STROBE extension and to generate an early version of the checklist. They conducted 2 further Delphi surveys, first extending from typhoid and other invasive salmonelloses to all infectious diseases, and then to noncommunicable diseases and injuries. Finally, experts piloted the checklist on relevant manuscripts to critically assess if it was clear, concise, complete, and free of errors. An executive group curated the checklist after every survey round. The STROBE EPIC checklist comprises 47 items in the domains of title (1 item), abstract (2 items), introduction (1 item), methods (25 items), results (6 items), discussion (7 items), and other information (5 items). STROBE EPIC items address reporting of study design, adjustment factors for underreporting and underdiagnosis, denominator population estimation, case ascertainment methods, factors producing artefactual changes to observed disease prevalence or incidence, limitations of incomplete surveillance coverage, generalizability of short-duration studies, and data availability. The authors anticipate that the STROBE EPIC extension will be used by researchers, authors, modelers, burden-of-disease researchers, peer reviewers, and journal editors to optimize the presentation of epidemiologic evidence to support diverse health policy decisions.