tetano
Editor, Senior Moderator
PLoS One
. 2026 Nov 10;21(11):e0360917.
doi: 10.1371/journal.pone.0360917. eCollection 2026.
Gauthier Vercher 1 2 3 , David R J Pleydell 2 3 , Lina Awada 4 , Paolo Tizzani 4 , Julien Cappelle 1 3 , Renaud Lancelot 1 3 5 , Elena Arsevska 1 3 , Carlène Trevennec 2 3
Affiliations Expand
Timely reporting of zoonotic infectious diseases allows for rapid response and mitigation by health authorities. However, little is known about the factors influencing the timeliness of disease outbreak reports. The World Animal Health Information System provides extensive data on delays that arise between first suspecting and subsequently reporting outbreaks of notifiable animal diseases. Here we analysed these report delays using a Bayesian semi-parametric survival model, to assess socio-demographic, epidemiological and cultural covariates on the timeliness of disease outbreak reports in Europe, using highly pathogenic avian influenza as a model disease. The survival model included time-varying coefficients and a penalized spline to account for temporal fluctuations in reporting rates, and parsimonious shrinkage (Bayesian model selection) was obtained using Dirichlet-Laplace priors. The results indicated that outbreaks occurring in wild birds, high outbreak notification rates, country, day of week and national holidays were all associated with delayed outbreak reporting times. Higher political stability and better corruption control, as defined by the World Bank, were also associated with longer reporting times, while high per capita gross national income and local poultry density were associated with shorter reporting delays. Better knowledge of surveillance capacities and modalities on a smaller scale could help further understand the reasons for the associations observed between these factors and reporting delays. Our results can help disease surveillance teams improve predictions of the day-to-day dynamics of epizootics and improve disease-introduction risk assessments. These results may also help inform tailored, country-specific recommendations for health authorities, delivered confidentially through international health organizations, to improve disease reporting.
. 2026 Nov 10;21(11):e0360917.
doi: 10.1371/journal.pone.0360917. eCollection 2026.
Factors influencing the timeliness of reporting highly pathogenic avian influenza outbreaks in Europe
Gauthier Vercher 1 2 3 , David R J Pleydell 2 3 , Lina Awada 4 , Paolo Tizzani 4 , Julien Cappelle 1 3 , Renaud Lancelot 1 3 5 , Elena Arsevska 1 3 , Carlène Trevennec 2 3
Affiliations Expand
- PMID: 43007994
- DOI: 10.1371/journal.pone.0360917
Abstract
Timely reporting of zoonotic infectious diseases allows for rapid response and mitigation by health authorities. However, little is known about the factors influencing the timeliness of disease outbreak reports. The World Animal Health Information System provides extensive data on delays that arise between first suspecting and subsequently reporting outbreaks of notifiable animal diseases. Here we analysed these report delays using a Bayesian semi-parametric survival model, to assess socio-demographic, epidemiological and cultural covariates on the timeliness of disease outbreak reports in Europe, using highly pathogenic avian influenza as a model disease. The survival model included time-varying coefficients and a penalized spline to account for temporal fluctuations in reporting rates, and parsimonious shrinkage (Bayesian model selection) was obtained using Dirichlet-Laplace priors. The results indicated that outbreaks occurring in wild birds, high outbreak notification rates, country, day of week and national holidays were all associated with delayed outbreak reporting times. Higher political stability and better corruption control, as defined by the World Bank, were also associated with longer reporting times, while high per capita gross national income and local poultry density were associated with shorter reporting delays. Better knowledge of surveillance capacities and modalities on a smaller scale could help further understand the reasons for the associations observed between these factors and reporting delays. Our results can help disease surveillance teams improve predictions of the day-to-day dynamics of epizootics and improve disease-introduction risk assessments. These results may also help inform tailored, country-specific recommendations for health authorities, delivered confidentially through international health organizations, to improve disease reporting.