COVID-19 Research: Challenges to Interpret Numbers and Propose Solutions

Abstract

The response of the scientific community to the COVID-19 pandemic has been unprecedented in size, speed and discovery output. Within months of virus emergence, the SARS-CoV-2 genomics, replication, evolution and dissemination dynamics as well as natural history, infection risk and prognostic factors and biology of the disease have been gradually deciphered. More than 250 articles on COVID-19 published in Frontiers in Public Health have contributed to these insights. We discuss here some of the key research themes and challenges that have been addressed. We provide our perspective on current research issues with surveillance data quality and limitations of epidemiological methods. We warn against the potential misuse or misleading interpretation of public data of variable quality and the use of inadequate study designs for the evaluation of effect of non-pharmaceutical interventions. We conclude by interrogating possible public health strategies for pandemic control as well as discuss the ethical responsibilities and democratic accountability of researchers in their role as experts and policy advisors.

The Waiver of Patent Protections for COVID-19 Vaccines During the Ongoing Pandemic and the Conspiracy Theories: Lights and Shadows of an Issue on the Ground

“…This is a fundamental point since the first period of vaccination against COVID-19 in the West has publicly highlighted the possibility of some rare adverse effects that had not been reported in earlier stages of clinical research (phase 1, 2 and 3), in particular vaccine-induced thrombocytopenia/thrombosis associated with the use of viral vector vaccines (32)(33)(34)(35)(36). Unfortunately, national health surveillance procedures may not be standardized and their improvement depends on local laboratory and clinical capabilities (37).…”

Real-time mortality statistics during the COVID-19 pandemic: A proposal based on Spanish data, January–March, 2021

“…In this way, using quadratic and cubic regressions helps mitigate the negative bias observed in real-time estimates due to death reporting lags. Other recent studies ( 30 , 31 ) consider this delay as one of the main obstacles to the correct interpretation of COVID-19 data. Sarnaglia et al ( 32 ) or Guglielmi et al ( 33 ), for example, suggest other methodologies to reduce the problems generated by reporting lags in counting the number of infectious cases.…”

Editorial: Insights in coronavirus disease (COVID-19) - surveillance, prevention and treatment

“…Thus, it is not surprising that epidemiological studies continue to feature strongly in the published scientific literature as understanding of the changing dynamics of COVID-19 remains a public health priority. To this end, the greater emphasis on public perceptions, attitudes and behaviors is a welcome development, further strengthening public health responses and gradually involving an active participation of “citizen scientists” as advocated previously ( 6 ).…”