Harvard Public Health Experts Develop Tool for Real-Time Monitoring of Infectious Diseases

Recently, scientists at the Harvard T.H. Chan School of Public Health developed a way to monitor epidemics by calculating real-time estimates of the epidemic’s growth rate. The method evaluates the viral load of a disease, which pertains to the rate of increase or decrease of infection cases in relation to the quantity of viruses found in an individual’s body.

The research and development study was led by Michael Mina, an assistant professor of epidemiology at the T.H. Chan School of Public Health in Harvard. Professor Mina also works as a core constituent of the Center for Communicable Disease Dynamics. According to the epidemiology professor, this latest method can give a new metric that policy makers, epidemiologists, and health officials can use to obtain real-time updates about an epidemic. Especially since scientists link knowledge of how the virus grows in a person’s body to the rate by which the virus spreads.

This new method will be extremely helpful in determining the effectiveness of basic interventions like social distancing and wearing of protective masks. The new tool can also help identify which geographical areas need more attention. That way, public health officials can immediately distribute extra medical resources in order to arrest the increase of infection cases.

Current Monitoring Methods are Reactive Responses to Epidemic Outbreaks

Monitoring epidemics today currently involves following hospitalization rates, testing of positivity rates, and mortality rates. This current method has limitations because data collection can be affected by poor reporting systems. More often than not, poor systems provide inaccurate and misleading information, which can greatly impact the delivery of public health responses.

As it was in the case of the COVID-19 pandemic, those who tested positive already had higher viral loads that have already spread widely before they were tested.

When cases of the virus increase, those who are positive will be infected and have higher viral loads by the time they are tested, which is why outbreaks fluctuate exponentially. Testing could take place when the virus has already reached its peak amount in the body, and tends to lessen gradually after the infection.

This new mathematical tool created by the researchers at Harvard Chan school can track pandemic hotspots better than the current method. In their study, their findings show that the method can help estimate the decay or growth rate of the outbreak in a particular population in a specific location.