Epidemiology professor Marc Lipsitch talks about Covid-19 surveillance strategies | New
Harvard epidemiology professor Marc Lipsitch discussed lessons from the Covid-19 pandemic regarding disease surveillance strategies at a Harvard School of Public Health seminar on Wednesday.
Lipsitch, who has led the Center for Forecasting and Outbreak Analytics at the Centers for Disease Control and Prevention since last year, reflected on the strategies different countries are using to track the spread of Covid-19.
Lipsitch said most countries, with the exception of Luxembourg and the UK, relied on case notification as the “basic unit of surveillance” during the pandemic.
However, he noted that the number of reported cases is an “unreliable measure of disease activity” because people may not be prompted to take a Covid test or report a positive result.
“It’s a very strange type of quantity to report, because it’s not an epidemiological quantity such as incidence, prevalence, or duration,” he said. “But it’s a complex function of those quantities.”
Lipsitch instead hailed the surveillance strategies used in Luxembourg and the UK
He said Luxembourg randomly takes a “substantial fraction” of its “small population” each week to measure the spread of the virus. This strategy has enabled Luxembourg to monitor the effectiveness of its countermeasures against Covid-19.
The UK used two surveillance methods at the start of the pandemic, according to Lipsitch. One was repeated at different times during the pandemic, while the other tracked households over time.
Lipsitch said the methods used in Luxembourg and the UK are based on the belief that the “best way” to track infection in a country is to measure the spread in a random sample.
Lipsitch also stressed the importance of data completeness. For example, Lipsitch said the United States lacks data examining the race and ethnicity of people infected with SARS-CoV-2.
Still, there are ways to “extract” additional detail from the “admittedly imperfect data that’s collected in a place that doesn’t have random sampling,” according to Lipsitch.
Lipsitch said studies over the past year show that taking data from hospital populations can be a cheaper alternative to random sampling of the general population.
Lipsitch pointed out that seemingly constant factors — such as genetic sequence, disease severity and contagiousness — can change over time as the virus mutates and the population develops resistance.
“What Covid has taught us is that actually it’s all surveillance issues,” he said. “All are changing through the pandemic.”