Predicting vaccination levels without accurate or timely vaccination data (Penn State)
Researchers at Penn State and the World Health Organization develop method to predict measles vaccination levels using routinely collected clinical data on suspected measles cases
UNIVERSITY PARK, Pa. — Knowing how many people are vaccinated against an existing or re-emerging threat is a key factor guiding public health decisions, but such information is often sparse or non-existent in many regions, according to researchers at Penn State. Now, in collaboration with a team at the World Health Organization, the researchers have developed a new method to estimate and predict regional measles vaccination coverage levels even when accurate or timely survey data on vaccination is not available. The method uses data that is routinely collected when potential measles cases present at clinics to model vaccination coverage and can be used to guide public health interventions to slow or prevent measles outbreaks.
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