| 1. |
- Avril, Alexis, et al.
(författare)
-
Capturing individual-level parameters of influenza A virus dynamics in wild ducks using multistate models
- 2016
-
Ingår i: Journal of Applied Ecology. - : Wiley. - 0021-8901 .- 1365-2664. ; 53:4, s. 1289-1297
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 2. |
- Bengtsson, Daniel, et al.
(författare)
-
Does influenza A virus infection affect movement behaviour during stopover in its wild reservoir host?
- 2016
-
Ingår i: The Royal Society. - : The Royal Society. - 2054-5703. ; 3:2
-
Tidskriftsartikel (refereegranskat)abstract
- The last decade has seen a surge in research on avian influenza A viruses (IAVs), in part fuelled by the emergence, spread and potential zoonotic importance of highly pathogenic virus subtypes. The mallard (Anas platyrhynchos) is the most numerous and widespread dabbling duck in the world, and one of the most important natural hosts for studying IAV transmission dynamics. In order to predict the likelihood of IAV transmission between individual ducks and to other hosts, as well as between geographical regions, it is important to understand how IAV infection affects the host. In this study, we analysed the movements of 40 mallards equipped with GPS transmitters and three-dimensional accelerometers, of which 20 were naturally infected with low pathogenic avian influenza virus (LPAIV), at a major stopover site in the Northwest European flyway. Movements differed substantially between day and night, as well as between mallards returning to the capture site and those feeding in natural habitats. However, movement patterns did not differ between LPAIV infected and uninfected birds. Hence, LPAIV infection probably does not affect mallard movements during stopover, with high possibility of virus spread along the migration route as a consequence.
|
|
| 3. |
- Latorre-Margalef, Neus, et al.
(författare)
-
How Does Sampling Methodology Influence Molecular Detection and Isolation Success in Influenza A Virus Field Studies?
- 2016
-
Ingår i: Applied and Environmental Microbiology. - 0099-2240 .- 1098-5336. ; 82:4, s. 1147-1153
-
Tidskriftsartikel (refereegranskat)abstract
- Wild waterfowl are important reservoir hosts for influenza A virus (IAV) and a potential source of spillover infections in other hosts, including poultry and swine. The emergence of highly pathogenic avian influenza (HPAI) viruses, such as H5N1 and H5N8, and subsequent spread along migratory flyways prompted the initiation of several programs in Europe, North America, and Africa to monitor circulation of HPAI and low-pathogenicity precursor viruses (low-pathogenicity avian influenza [LPAI] viruses). Given the costs of maintaining such programs, it is essential to establish best practice for field methodologies to provide robust data for epidemiological interpretation. Here, we use long-term surveillance data from a single site to evaluate the influence of a number of parameters on virus detection and isolation of LPAI viruses. A total of 26,586 samples (oropharyngeal, fecal, and cloacal) collected from wild mallards were screened by real-time PCR, and positive samples were subjected to isolation in embryonated chicken eggs. The LPAI virus detection rate was influenced by the sample type: cloacal/fecal samples showed a consistently higher detection rate and lower cycle threshold (Ct) value than oropharyngeal samples. Molecular detection was more sensitive than isolation, and virus isolation success was proportional to the number of RNA copies in the sample. Interestingly, for a given Ct value, the isolation success was lower in samples from adult birds than in those from juveniles. Comparing the results of specific real-time reverse transcriptase (RRT)-PCRs and of isolation, it was clear that coinfections were common in the investigated birds. The effects of sample type and detection methods warrant some caution in interpretation of the surveillance data.
|
|
