COVID-19 and Cancer: Acting on past lessons and learning new ones

eLife has published a special issue containing articles that examine how cancer prevention, control, care and survivorship were impacted by the COVID-19 pandemic.
  1. Eduardo L Franco  Is a corresponding author
  2. Diane M Harper  Is a corresponding author
  1. eLife, United Kingdom

We have seen much new science emerge since January 2020, when the World Health Organization (WHO) declared COVID-19 to be a public health emergency of international concern. Indeed, according to PubMed, researchers have published more than 420,000 articles on COVID-19, SARS-CoV-2 and related topics to date. Moreover, a number of efficacious and safe vaccines and anti-virals were developed in a relatively short period of time. Researchers from many different fields – including virology, epidemiology, molecular biology, vaccinology, and infectious disease modelling – were involved in these efforts.

For those who worked on the global HIV/AIDS epidemic, which began in 1981, the COVID-19 pandemic brought a sense of déjà vu. Back in the early 1980s, with the support of funding agencies, entire academic teams in a wide range of fields reoriented their research programs in an effort to control the effects of the HIV/AIDS epidemic via multiple areas, including epidemiology, HIV pathogenesis, vaccine development, diagnostics and therapy. Four decades later, HIV infection is no longer a death sentence, but there is still a need for research into new treatments and approaches for prevention and disease management, and to ensure that existing treatments are made available to vulnerable populations in low- and middle-income countries. The HIV/AIDS epidemic also resulted in a great deal of new science (almost 500,000 articles), albeit spread out over a longer time frame than the articles published on COVID-19 to date.

There are other parallels. Much like the HIV/AIDS epidemic required new science, new social practices, and new disease-management skills, so did the COVID pandemic. The COVID-19 lockdowns resulted in the suspension of cancer-prevention activities (such as tobacco control and vaccinations for hepatitis B and human papillomavirus) and prevented people in many countries from being screened for cancer. Treatments for patients with newly diagnosed cancers were also delayed, and existing patients – who were already at increased risk of death from the combined comorbidity of their cancer and COVID – had their oncology surgeries postponed. At the same time, like all other patients, cancer patients had to share their physicians with large numbers of COVID-19 patients: the pandemic also led to high levels of stress and burnout among medical staff, which has resulted in many leaving the profession. Understanding the impact of the pandemic on the entire trajectory of cancer – prevention, screening, diagnosis, therapy, survivorship, and end-of-life care – will help us plan interventions and prioritize care to mitigate or prevent the increases in cancer burden that may happen in the medium and long term.

There are also parallels in how the public and politicians responded to HIV/AIDS and COVID-19. Much like we learned to fight the pervasive bigotry that marginalized gay communities in the 1980s, we must learn how to fight the misinformation and disinformation that have hindered efforts to prevent the spread of COVID-19 in many countries. One stark difference between HIV/AIDS and COVID-19 is that we still do not have an effective vaccine against HIV.

The articles included in this special issue cover many different aspects of the impact of the COVID-19 pandemic on cancer across the globe, including both high- and low-income regions and countries. Many of the articles report the results of empirical research studies that captured the extent of the disruptions in care (such as disruptions in screening and vaccination activities, and delays in diagnoses and care). There are also articles about therapeutic interventions for the care of cancer patients affected by COVID-19, and articles about insightful modelling studies that provided projections of the impact of the pandemic on cancer prevention, control, and care pathways.

One of the lessons learned during the pandemic was that cancer control programmes could be made more resilient by taking advantage of recent technological advances: examples of this include the wider use of patient-centred screening for a number of cancers. The pandemic also confirmed the usefulness of videoconferencing for many different activities, including telemedicine, university teaching and virtual clinical appointments.

We thank all the reviewing editors, guest editors and reviewers who were involved in the peer review of the articles in this special issue (their names are on the home page for the special issue and/or in the individual articles), and we hope that it will serve as a valuable source of scientific evidence and information for those working in public health and elsewhere to develop plans to respond to future epidemics and pandemics. We also hope that this collection of articles will be a valuable historical account of what was often an improvised – yet innovative – response to a major public health threat.

Four decades after the start of the HIV/AIDS epidemic, HIV infection and AIDS are still with us. It is likely that SARS-CoV-2 and COVID-19 – and their successors – will also be with us for years to come, and that they will continue to inspire research that can be translated to provide new medicines, diagnostics and treatments. As the articles in this special issue confirm, it is essential that this research also includes work on managing cancer risk during any future public health emergency.

Article and author information

Author details

  1. Eduardo L Franco

    Eduardo L Franco is a Senior Editor at eLife

    For correspondence
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4409-8084
  2. Diane M Harper

    Diane M Harper is a Deputy Editor at eLife

    For correspondence
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7648-883X

Publication history

  1. Version of Record published: September 6, 2023 (version 1)


© 2023, Franco and Harper

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.


  • 304
  • 47
  • 0

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Eduardo L Franco
  2. Diane M Harper
COVID-19 and Cancer: Acting on past lessons and learning new ones
eLife 12:e91607.

Further reading

    1. Epidemiology and Global Health
    Caroline Krag, Maria Saur Svane ... Tinne Laurberg
    Research Article


    Comorbidity with type 2 diabetes (T2D) results in worsening of cancer-specific and overall prognosis in colorectal cancer (CRC) patients. The treatment of CRC per se may be diabetogenic. We assessed the impact of different types of surgical cancer resections and oncological treatment on risk of T2D development in CRC patients.


    We developed a population-based cohort study including all Danish CRC patients, who had undergone CRC surgery between 2001 and 2018. Using nationwide register data, we identified and followed patients from date of surgery and until new onset of T2D, death, or end of follow-up.


    In total, 46,373 CRC patients were included and divided into six groups according to type of surgical resection: 10,566 Right-No-Chemo (23%), 4645 Right-Chemo (10%), 10,151 Left-No-Chemo (22%), 5257 Left-Chemo (11%), 9618 Rectal-No-Chemo (21%), and 6136 Rectal-Chemo (13%). During 245,466 person-years of follow-up, 2556 patients developed T2D. The incidence rate (IR) of T2D was highest in the Left-Chemo group 11.3 (95% CI: 10.4–12.2) per 1000 person-years and lowest in the Rectal-No-Chemo group 9.6 (95% CI: 8.8–10.4). Between-group unadjusted hazard ratio (HR) of developing T2D was similar and non-significant. In the adjusted analysis, Rectal-No-Chemo was associated with lower T2D risk (HR 0.86 [95% CI 0.75–0.98]) compared to Right-No-Chemo.

    For all six groups, an increased level of body mass index (BMI) resulted in a nearly twofold increased risk of developing T2D.


    This study suggests that postoperative T2D screening should be prioritised in CRC survivors with overweight/obesity regardless of type of CRC treatment applied.


    The Novo Nordisk Foundation (NNF17SA0031406); TrygFonden (101390; 20045; 125132).

    1. Epidemiology and Global Health
    Xiaoxin Yu, Roger S Zoh ... David B Allison
    Review Article

    We discuss 12 misperceptions, misstatements, or mistakes concerning the use of covariates in observational or nonrandomized research. Additionally, we offer advice to help investigators, editors, reviewers, and readers make more informed decisions about conducting and interpreting research where the influence of covariates may be at issue. We primarily address misperceptions in the context of statistical management of the covariates through various forms of modeling, although we also emphasize design and model or variable selection. Other approaches to addressing the effects of covariates, including matching, have logical extensions from what we discuss here but are not dwelled upon heavily. The misperceptions, misstatements, or mistakes we discuss include accurate representation of covariates, effects of measurement error, overreliance on covariate categorization, underestimation of power loss when controlling for covariates, misinterpretation of significance in statistical models, and misconceptions about confounding variables, selecting on a collider, and p value interpretations in covariate-inclusive analyses. This condensed overview serves to correct common errors and improve research quality in general and in nutrition research specifically.