Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic

Abstract

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

Molnupiravir Use Among Patients with COVID-19 in Real-World Settings: A Systematic Literature Review

“…COVID-19 continues to be a major source of morbidity and mortality: in November 2023, the World Health Organization (WHO) reported > 9400 new cases and > 120 deaths attributable to COVID-19 per week [ 1 ]. Due to decreases in testing, monitoring, and surveillance activities over time [ 2 , 3 ], and especially since the WHO declared in May 2023 that the global health emergency had ended [ 4 ], both cases and deaths are likely under-reported; wastewater surveillance data suggest that clinical detection underestimates global cases 2- to 19-fold [ 5 ] and global excess mortality data suggest that the true COVID-19 mortality rate may be up to 2.7-fold higher than stated in official figures [ 6 ].…”

Temporal trends in test-seeking behaviour during the COVID-19 pandemic

“…The case-based surveillance data generated by mass testing were often used by epidemiologists to understand, monitor, and predict epidemic activity [1] including the potential exceedance of hospital capacity [2]. However, such analyses are fraught with challenges since the relationship between the time-series of cases and the underlying infection dynamics is difficult to characterise [3]. The COVID-19 cases recorded by mass testing programs represent only a fraction of individuals infected with SARS-CoV-2 [4] which depends on how many people seek and access testing.…”