2 Introduction and overview

The purpose of this project was to develop and propose guidance for (1) MMWR authors, (2) reviewers of MMWR reports before they reach MMWR scientific editors, and (3) MMWR scientific editors.We reviewed 56 full reports published between January 2019 and May 2022, to identify specific practices regarding presentations of data, analytic methods, analytic results, tables and graphics, and interpretation of results. We also reviewed guidance from journals, the American Statistical Association (ASA), the International Committee of Medical Journal Editors (ICMJE), and related sources.

This report is largely qualitative but informal. We sought a rich variety of topics and treatments published over a 41-month period before and during the Covid-19 pandemic. About half have a high Altmetric attention score relative to other reports published around the same time; scientific credibility is especially important in active social discourse. The other included reports had prompted methodological consultation by editorial staff or authors during review and production, so that these reports presented particular interest regarding correctness of methods and clarity in expression.

2.1 Principles

The MMWR’s weekly reports are CDC’s “primary vehicle for scientific publication of timely, reliable, authoritative, accurate, objective, and useful public health information and recommendations.” (MMWR Publications 2025) Many MMWR reports, especially full reports, apply statistical and other data-analytic methods to describe, keep up with, and intervene on evolving issues in public health practice. This report assessed how reports present and interpret data and data analysis.

ICMJE (@icmje_2025) urges authors to “[d]escribe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to judge its appropriateness for the study and to verify the reported results.” For this assessment, we adapted general principles regarding style, accuracy, and significance from existing norms for presenting and reviewing statistics in peer-reviewed articles.

Style: Many elements of MMWR’s editorial style support the series’ authority and consistency, such as article structures and format, the use of third-person voice, certain typographical conventions, and the application of scientific norms. Beyond authority and consistency, reports should strive for both precision and clarity, and they should avoid ambiguity. Since MMWR limits full reports to 1,400 words, authors must take special care to focus on important details and concise exposition. The principles of information design can guide editorial choices regarding tables and figures.

Accuracy: MMWR’s authority is also rooted in its scientific integrity, reliability, and credibility, which in turn depend on accuracy and transparency. The principle of accuracy calls for data, methods, results, and interpretations to be technically correct and defensible. Data should be suited to the public health purpose of the report. Methods for managing and analyzing data should be suited to the purpose and the data. Results should be suited to the purpose, data, and methods. And interpretations should match the purpose, data, methods, and results.

Significance: MMWR seeks to publish timely and useful public health information and recommendations to save lives and protect people from health threats. As data-related practices, norms, and methods evolve—such as guidance from ICMJE and the ASA and practices in data visualization—the MMWR’s house style should adapt in line with those external forces, much as it has with changes in digital technologies for communication and engagement. This report’s recommendations were intended to guide those adaptations.

By examining a set of MMWR reports that motivate methodological consultations, high public engagement, or both, this report intended first to check how well published reports achieve clarity, demonstrate accuracy, and explain the real-world significance across a variety of topics. On consulting with outside norms for presenting and reviewing statistics in peer-reviewed articles, we looked for ways to improve how MMWR full reports present and interpret data and data analysis with ever greater clarity through style, integrity through accuracy, and impact through significance.

In this assessment we applied the following guiding principles:

  • Focus on clarity, precision, and accuracy in presenting data, analysis, results, and interpretation
  • Balance important details with concise presentation formats
  • Consult current practices for presenting data-oriented elements, including inferences, in narrative text, tables, and figures
  • Recommend changes geared toward style, accuracy, and significance, mindful of MMWR’s purpose, orientation, and house style

2.2 Scope of selected publications

To delineate the scope of reports for review, we used 2 data sources—MMWR online and Altmetric score data—to narrow the scope to no more than 60 articles. For this review, we limited consideration to volumes and issues published between 2016 (volume 65) and May 2022 (volume 71, issue 21), immediately before this project began. From volume 65, issue 1, through volume 71, issue 21, MMWR published 2,711 reports, including weekly reports, recommendations and reports, surveillance summaries, and supplements. Among 2,548 weekly reports, report categories include 1,437 full reports and 1,111 reports in other categories, including announcements, cover boxes, errata, grand rounds, notes from the field, notices to readers, outbreak reports, quick stats, retraction, and Vital Signs.

To focus on data and analyses while including substantive pre-Covid coverage, we further limited consideration to 845 full reports published between January 2019 and May 2022. We grouped contiguous issues, ranging in size from 16 to 28 full reports, from which we selected about 1 report per grouping. We considered 2 additional criteria: (1) reports that received higher Altmetric attention scores (Altmetric Glossary 2020) than other reports published within the same few weeks, and (2) reports on which an author, a clearance official, or an MMWR editor sought technical consultation during review or production. Taking these criteria together, we purposefully selected 56 full reports for review.

2.3 Scope of auxiliary sources

We reviewed existing guidelines for statistical presentation in, and review of, scientific literature. Although the MMWR is not peer-reviewed, it is supported by a tiered sequence of reviews, including CDC clearance, ad hoc subject-matter review, and editorial review by MMWR staff. We considered lessons and advice on peer review processes to the extent that they might apply or be adapted to MMWR.

ICMJE (ICMJE recommendations (2025)) states that authors should “[d]escribe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to judge its appropriateness for the study and to verify the reported results.” (Bailar and Mosteller 1988) offered guidelines for statistical reporting in articles for medical journals, comprising 15 numbered statements focusing on manuscript preparation. Many medical journals cite or have adapted Bailar and Mosteller’s recommendations. Several, but not all, of their guidelines would apply to MMWR reports. Other authors have also adapted or expanded on guidelines for authors; see, for example, (Lang and Altman 2016).

Altman (Altman (1998)) advises statistical reviewers for medical journals: “The main reason for the plethora of statistical errors is that the majority of statistical analyses are performed by people with an inadequate understanding of statistical methods. They are then peer reviewed by people who are generally no more knowledgeable. … The main areas for the statistical reviewer to consider are design, methods of analysis, presentation of results, and interpretation.”

2.4 Report identifiers

Each full report is identified by its digital object identifier (DOI) suffix consisting of an 8-10–character string of the form “mmXXYY[YY]wZ[Z]”, where “mm” signifies a weekly report, XX is the 2-digit volume, YY[YY] is the 2-digit or 4-digit issue number, w is either “e” (for early release) or “a” (for reports published on-cycle), and Z[Z] is a 1-digit or 2-digit number indicating approximate pagination order and ensuring that each identifier is unique. This format goes back to volume 47, with regular use from volume 48, issue number 17 to the present. The full DOI is of the form 10.15585/mmwr.mmXXYY[YY]wZ[Z].

2.5 Observations and recommendations

The epidemiological literature contains varied advice on how to report descriptive or causal analyses, including Strengthening the Reporting of Observational Studies in Epidemiology (STROBE; (Vandenbroucke et al. 2007)) and (Lesko et al. 2022). This assessment applied broader components focusing on the uses and interpretation of data, organized in 4 main sections:

  1. Section 4: What data are used in the report? What design choices and constraints influence how well those data might address the public health question of interest?
  2. Section 5: What do the data show? What analytic methods did authors use, and how did they present the results of those methods, in narrative, tabular, or graphical form?
  3. Section 6: What do the data signify? How did the authors place data, methods, and results into the context of public health, including discussion and any recommendations?
  4. Section 7: What additional practices could help MMWR modernize uses of data in reports?

Each section contains a more refined set of topics, along with principles, observations, and recommendations.

  • Principles: Each topic addresses a principle or principles, citing sources where possible.
  • Observations: Each topic lists specific observations from assessed reports (citing each report) or a general summary of issues seen in multiple reports.
  • Recommendations: By comparing observed practices with motivating principles, each topic lists a recommendation or recommendations, which might be general or might be more narrowly directed to authors, reviewers, or editors.

References

Altman DG. 1998-12-15. Statistical reviewing for medical journals. Statist. Med. 17(23):2661–2674. https://doi.org/10.1002/(SICI)1097-0258(19981215)17:23<2661::AID-SIM33>3.0.CO;2-B
Altmetric Glossary. 2020-09-15. Altmetric. https://help.altmetric.com/support/solutions/articles/6000232842-altmetric-glossary
Bailar JC, Mosteller F. 1988-02-01. Guidelines for statistical reporting in articles for medical journals: Amplifications and explanations. Ann Intern Med. 108(2):266–273. https://doi.org/10.7326/0003-4819-108-2-266
ICMJE recommendations. 2025-04. https://icmje.org/recommendations/
Lang T, Altman D. 2016-09-01. Statistical analyses and methods in the published literature: The SAMPL guidelines. Medical Writing. 25(3):31–36. https://journal.emwa.org/statistics/statistical-analyses-and-methods-in-the-published-literature-the-sampl-guidelines/
Lesko CR, Fox MP, Edwards JK. 2022-11. A framework for descriptive epidemiology. American Journal of Epidemiology. 191(12):2063–2070. https://doi.org/10.1093/aje/kwac115
MMWR Publications. 2025-03-11. https://www.cdc.gov/mmwr/publications/index.html
Vandenbroucke JP, Von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger M. 2007-11. Strengthening the reporting of observational studies in epidemiology (STROBE): Explanation and elaboration. Epidemiology. 18(6):805–835. https://doi.org/10.1097/EDE.0b013e3181577511