UNIVERSITY PARK, Pa. — In the most detailed study to date of epidemic spread, an international team of researchers has modeled measles dynamics based on over 40 years of data collected in England and Wales. The models — which span the prevaccination period, introduction of measles vaccination, and local elimination by vaccination in the 1990s — reveal that, before the introduction of a vaccine, measles could persist in both large population centers and by spread among sets of smaller towns. The study also provides critical data on the importance of spatial modeling for the long-term control of global epidemics and could help inform the long-term public health response to the current COVID-19 pandemic.
A paper describing the study appears April 27 in the journal Nature Ecology & Evolution.
“During the last 20 years there have been tremendous inroads towards eradicating measles — one of the major killers of children globally — as annual deaths have been driven down from more than a million to less than 200,000,” said Ottar N. Bjørnstad, distinguished professor of entomology and biology at Penn State and one of the leaders of the research team. “However, previous efforts to eradicate smallpox and polio highlight the complexity of moving from local control to global eradication. Our study provides critical data on how long-term control efforts will need both general and detailed spatial models to finally stop this deadly disease.”
Prior to the introduction of a vaccine, the number of measles cases in England and Wales would undergo, periodic — often biennial — epidemics. This pattern, driven by herd immunity, is common among a number of diseases and in other locales. The researchers sought to locate the reservoirs where the virus persists in the dips between epidemics, which are the sources for reintroduction of the virus into the general populace in the next major epidemic. This persistence question is central to understanding the dynamics of measles and other viral diseases and for coordinating public health interventions.