Infectious disease surveillance is fundamental to public health systems. (1) However, Canada's COVID-19 pandemic response relied on clinical and outbreak management (COM) platforms; i.e., public health institutions tracking case counts across a range of reasons for testing (e.g., symptoms) or screening (e.g., exposure, routine screening for health care workers). (2) Although important for clinical care and providing broad COVID-19 population health metrics and trends, these COM platforms were not designed for infectious disease surveillance and have important limitations. (2)
We propose a tiered surveillance approach that encompasses waste-water testing, representative population-based testing (including data on potential transmission mechanisms; e.g., social determinants of health) and genomics to efficiently monitor disease trends, and rapidly detect resurgences and emergence of novel variants or strains. This information is crucial to inform the development of tailored and effective public health programs. The proposed system could, and ultimately should, be expanded beyond COVID-19 to support pan-respiratory pathogen surveillance.
Why does relying strictly on COM platforms limit a public health response?
The objectives of COM testing platforms are to support clinical care (e.g., patient diagnosis, determining appropriate treatment) and public health case and contact tracing (e.g., testing exposed individuals to determine isolation needs). (3) Although these platforms are not intended for surveillance purposes, many jurisdictions have used them as ad hoc surveillance systems during the COVID-19 pandemic. (2) However, the utility of these data are limited by biases due to changing case definitions and testing criteria over time and across jurisdictions, a lack of standardization to account for differences in the populations being tested, and inadequate capture of mild or asymptomatic infections. (2,4)
Long-term reliance on COM platforms creates challenges for public health response as a result of undercounting of cases, selection biases from health care-seeking behaviours, lagging epidemiological indicators and unmanageable case volumes. (5) For instance, clinical platforms typically conduct diagnostic testing among symptomatic individuals and are therefore likely to miss individuals who do not seek testing owing to asymptomatic or mild illness, leading to an underestimation of community disease burden. (6) Prevailing inequities in health care for marginalized and lower-income communities--such as lower access to and utilization of health care services--contribute to underestimating disease burden in these populations. (7,8) Further, data on hospital admissions capture only severe cases, and because patients may present later in their course of illness, they are a lagging indicator of community transmission. (9) Together, these limitations compromise effective and equitable policy-making.
What information do different surveillance systems provide to support public health decision-making?
Surveillance systems offering opportunities to move beyond COM platforms include waste-water, syndromic, sentinel and population-based surveillance.
Waste-water surveillance is a relatively low-cost, innovative method in which routine testing of waste-water samples provides early signals of changes in pathogen trends at the population level. (10,11) Genomic sequencing of waste-water samples can be conducted to enable early detection of novel viral variants or strains. (11) Because waste-water surveillance does not rely on health system interaction, it is not biased by health care-seeking behaviour. However, although these data can be...