title: Structuring targeted surveillance for monitoring disease emergence by mapping observational data onto ecological process.
abstract: An efficient surveillance system is a crucial factor in identifying, monitoring and tackling outbreaks of infectious diseases. Scarcity of data and limited amounts of economic resources require a targeted effort from public health authorities. In this paper, we propose a mathematical method to identify areas where surveillance is critical and low reporting rates might leave epidemics undetected. Our approach combines the use of reference-based susceptible-exposed-infectious models and observed reporting data; We propose two different specifications, for constant and time-varying surveillance, respectively. Our case study is centred around the spread of the raccoon rabies epidemic in the state of New York, using data collected between 1990 and 2007. Both methods offer a feasible solution to analyse and identify areas of intervention.
authors.affiliation: Center for Disease Ecology, Rollins School of Public Health, Emory University, Atlanta, GA, USA. lgerardo@bcamath.org
authors.forename: Luca
authors.initials: L
authors.lastname: Gerardo-Giorda
authors.forename: Gavino
authors.initials: G
authors.lastname: Puggioni
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Rudd
authors.forename: Lance A
authors.initials: LA
authors.lastname: Waller
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Real
mesh_terms: D000818:Animals; D004784:Environmental Monitoring / Q000379:methods*; D062665:Epidemiological Monitoring; D009518:New York / Q000453:epidemiology; D011818:Rabies / Q000453:epidemiology* / Q000662:veterinary*; D011821:Raccoons; D012189:Retrospective Studies
keywords: data assimilation; modelling; public health; raccoon rabies; risk monitoring