Capturing individual‐level parameters of influenza A virus dynamics in wild ducks using multistate models. Issue 4 (9th June 2016)

• Record Type: Journal Article
• Authors: Avril, Alexis; Grosbois, Vladimir; Latorre‐Margalef, Neus; Gaidet, Nicolas; Tolf, Conny; Olsen, Björn; Waldenström, Jonas
• Editors: Bauer, Silke
• Is Part Of: Journal of applied ecology. Volume 53:Issue 4(2016:Aug.)
• Page Start: 1289
• Page End: 1297
• Publication Date: 2016-06-09
• Subjects: avian influenza -- epidemiology -- host–pathogen dynamics -- individual‐based monitoring -- influenza A virus -- multistate capture–recapture -- outbreaks -- SIR model -- waterfowl -- zoonosis; Agriculture -- Periodicals; Biology, Economic -- Periodicals; Agricultural ecology -- Periodicals; Applied ecology -- Periodicals; 577
• DOI: 10.1111/1365-2664.12699
• Languages: English
• ISSNs: 0021-8901

Abstract

Summary: Disease prevalence in wildlife is governed by epidemiological parameters (infection and recovery rates) and response to infection, both of which vary within and among individual hosts. Studies quantifying these individual‐scale parameters and documenting their source of variation in wild hosts are fundamental for predicting disease dynamics. Such studies do not exist for the influenza A virus (IAV), despite its strong impact on the global economy and public health. Using capture–recaptures of 3500 individual mallards Anas platyrhynchos during seven migration seasons at a stopover site in southern Sweden, we provide the first empirical description of the individual‐based mechanisms of IAV dynamics in a wild reservoir host. For most years, prevalence and risk of IAV infection peaked at a single time during the autumn migration season, but the timing, shape and intensity of the infection curve showed strong annual heterogeneity. In contrast, the seasonal pattern of recovery rate only varied in intensity across years. Adults and juveniles displayed similar seasonal patterns of infection and recovery each year. However, compared to adults, juveniles experienced twice the risk of becoming infected, whereas recovery rates were similar across age categories. Finally, we did not find evidence that infection influenced the timing of emigration. Synthesis and applications . Our study provides robust empirical estimates of epidemiological parameters for predicting influenza A virus (IAV) dynamics. However, the strong annual variation in infection curves makes forecasting difficult. Prevalence data can provide reliable surveillance indicators as long as they catch the variation in infection risk. However, individual‐based monitoring of infection is required to verify this assumption in areas where surveillance occurs. In this context, monitoring of captive sentinel birds kept in close contact with wild birds is useful. The fact that infection does not impact the timing of migration underpins the potential for mallards to spread viruses rapidly over large geographical scales. Hence, we strongly encourage IAV surveillance with a multistate capture–recapture approach along the entire migratory flyway of mallards.