Combined Phylogeographic Analyses and Epidemiologic Contact Tracing to Characterize Atypically Pathogenic Avian Influenza (H3N1) Epidemic, Belgium, 2019.

The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.

Assessing the use of animal health platforms: User's needs, preferences and constraints.

Animal health information systems or risk analysis tools are indispensable not only for animal health surveillance, but also to observe the evolution and risk of disease incursion into a disease-free area. Given the various information that can be derived from these both animal information systems and risk analysis tools, different international and national organizations have customized or created their own systems/tools to provide specific information for use by the respective countries. Moreover, with the increase of technology and data storage, they have become more accessible and widely used by professionals in animal and human health sciences. This study aimed to establish user's preferences, needs and constraints in respect of these animal information systems and risk analysis tools. An online survey was conducted and answered by 213 respondents from 132 countries. The respondents were animal health or public health professionals in different employment sectors (mostly in government, research and university institutions) and various fields of competency (highest for animal and public health). The majority of respondents used the animal health information systems frequently and on a weekly basis, with prevention measures of diseases being regarded as the most useful information. Descriptive epidemiology was more used/needed than analytical epidemiology. Risk analysis was performed by the majority of the respondents (70%), using a qualitative approach more than a quantitative or semi-qualitative. The primary objectives were to produce risk assessment and preparedness in areas involving origin and spread of animal diseases. The features most sought after in risk analysis tools were pathways of introduction and spread assessment. The level of satisfaction was higher for the platform which is most used by the respondents. Overall, these results could be taken into consideration when improving an already available platform, or when creating a new efficient tool.

Elaboration of a new framework for fine-grained epidemiological annotation.

Event-based surveillance (EBS) gathers information from a variety of data sources, including online news articles. Unlike the data from formal reporting, the EBS data are not structured, and their interpretation can overwhelm epidemic intelligence (EI) capacities in terms of available human resources. Therefore, diverse EBS systems that automatically process (all or part of) the acquired nonstructured data from online news articles have been developed. These EBS systems (e.g., GPHIN, HealthMap, MedISys, ProMED, PADI-web) can use annotated data to improve the surveillance systems. This paper describes a framework for the annotation of epidemiological information in animal disease-related news articles. We provide annotation guidelines that are generic and applicable to both animal and zoonotic infectious diseases, regardless of the pathogen involved or its mode of transmission (e.g., vector-borne, airborne, by contact). The framework relies on the successive annotation of all the sentences from a news article. The annotator evaluates the sentences in a specific epidemiological context, corresponding to the publication date of the news article.

Rapid establishment of a national surveillance of COVID-19 hospitalizations in Belgium.

BACKGROUND: In response to the COVID-19 epidemic, caused by a novel coronavirus, it was of great importance to rapidly collect as much accurate information as possible in order to characterize the public health threat and support the health authorities in its management. Hospital-based surveillance is paramount to monitor the severity of a disease in the population. METHODS: Two separate surveillance systems, a Surge Capacity survey and a Clinical survey, were set up to collect complementary data on COVID-19 from Belgium's hospitals. The Surge Capacity survey collects aggregated data to monitor the hospital capacity through occupancy rates of beds and medical devices, and to follow a set of key epidemiological indicators over time. Participation is mandatory and the daily data collection includes prevalence and incidence figures on the number of COVID-19 patients in the hospital. The Clinical survey is strongly recommended by health authorities, focusses on specific patient characteristics and relies on individual patient data provided by the hospitals at admission and discharge. CONCLUSIONS: This national double-level hospital surveillance was implemented very rapidly after the first COVID-19 patients were hospitalized and revealed to be crucial to monitor hospital capacity over time and to better understand the disease in terms of risk groups and outcomes. The two approaches are complementary and serve different needs.