October 20, 2022 – In November 2021, researchers at Botswana’s Sikhulile Moyo lab discovered an unexpected result while testing samples for COVID-19: a sequence of the coronavirus genome that contained dozens of potentially dangerous new mutations. Researchers quickly alerted the rest of the world to the mutated virus, which eventually became known as the highly transmissible variant of Omicron.
With the early warning, public health officials stepped up vaccination programs and reimplemented social distancing measures. “Governments were able to respond in days, not months, and that was very important in trying to slow transmission,” Moyo said at an Oct. 17 event at the Harvard TH Chan School of Public Health. He is Laboratory Director of the Botswana Harvard AIDS Institute Partnership and a Research Associate in the Department of Immunology and Infectious Diseases at Harvard Chan School.
Technologies such as genomic sequencing have proven invaluable in responding to the COVID-19 pandemic and will be important in preventing future infectious disease outbreaks, according to the panel of experts who spoke at the event. Other crucial tools have included checking levels of viral material in sewage, tracking population movements through cellphone data and combining disparate data sources, they said.
However, they cautioned, the effectiveness of the tools depends on building trust between academic researchers, public health officials and the general public.
Alexandria Boehm, a professor of civil and environmental engineering at Stanford University, spoke about her efforts to detect viral genetic material in California wastewater. In November 2020, she began looking for traces of the coronavirus in sewage. His measurements helped predict the number of COVID-19 cases in the region. Since then, the method has become widely used in the United States as an early warning system for potential power surges.
“Wastewater represents this amazing resource that seems to work well for studying all kinds of infectious diseases,” Boehm said. His team is now applying sewage detection to emerging epidemics, including influenza and monkeypox.
“We had built this relationship of trust with public health [officials] so even though we weren’t sure exactly what we were going to find or how it would relate to the case data, they were still open and interested in seeing those results,” Boehm said.
Satchit Balsari, assistant professor of global health and population at Harvard Chan School, spoke about his work helping to develop a COVID response tool based on cellphone location data. Early in the pandemic, when treatments and vaccines were not yet available, public health officials needed to know whether non-pharmaceutical interventions such as lockdowns and travel restrictions were effective. Balsari and a global network of researchers gathered anonymized, aggregated location information from cell towers and social media apps, using it to analyze the impact of people’s movements on COVID case counts. -19. The results have successfully helped local, state and national agencies adjust policies for specific locations across the country, he said.
Researchers are now using cellphone location data to identify other displacement patterns, such as forced displacement caused by California wildfires, Balsari noted. But using the information to improve policy remains difficult, he added, particularly because people fear the government is failing to protect the privacy of their data.
“This lack of trust… prevents the partnership we need to generate and act on the data we have. Citizens are understandably reluctant to engage with the state or part with their data,” he said, adding that transparency is needed on how data is collected and shared.
In order to get the most out of several promising tools that could help prevent future infectious disease outbreaks, it will be crucial to combine different data sources, according to Marc Lipsitch, professor of epidemiology, director of the Center for Communicable Disease Dynamics at Harvard. Chan School and scientific director of the newly created Center for Forecasting and Outbreak Analytics at the Centers for Disease Control and Prevention.
“Our new center is designed…to pull data from multiple sources and produce short-term forecasts, long-term scenario projections, and answers to analytical questions, such as: How should we formulate testing policy? How to formulate an isolation policy? Is there an advantage to closing or closing the borders? said Lipsitch.
For example, when the Omicron coronavirus variant was first detected, no one knew if it would cause serious infections. Lipsitch was part of a team that quickly collected genomic and clinical data. Within weeks, researchers were able to estimate that the Omicron variant was causing less severe cases than the previously dominant Delta variant, giving public health officials an idea of what to expect.
Going forward, combining data sources to predict COVID-19 trends will continue to be important, especially as many cases are detected using home testing and not officially reported. Lipsitch said. His team also monitors trends in other infectious disease outbreaks, including monkeypox. The job depends on having early detection systems in place before a public health threat emerges. “Maintaining momentum and interest and not falling into the classic cycle of panic and then neglect of public health funding is something we need to be aware of,” he said.
– Jessica Lou