Using Knowledge Fusion to Analyze Avian Influenza H5N1 in East and Southeast Asia

Abstract

Highly pathogenic avian influenza (HPAI) H5N1, a disease associated with high rates of mortality in infected human populations, poses a serious threat to public health in many parts of the world. This article reports findings from a study aimed at improving our understanding of the spatial pattern of the highly pathogenic avian influenza, H5N1, risk in East-Southeast Asia where the disease is both persistent and devastating. Though many disciplines have made important contributions to our understanding of H5N1, it remains a challenge to integrate knowledge from different disciplines. This study applies genetic analysis that identifies the evolution of the H5N1 virus in space and time, epidemiological analysis that determines socio-ecological factors associated with H5N1 occurrence, and statistical analysis that identifies outbreak clusters, and then applies a methodology to formally integrate the findings of the three sets of methodologies. The present study is novel in two respects. First it makes the initiative attempt to use genetic sequences and space-time data to create a space-time phylogenetic tree to estimate and map the virus' ability to spread. Second, by integrating the results we are able to generate insights into the space-time occurrence and spread of H5N1 that we believe have a higher level of corroboration than is possible when analysis is based on only one methodology. Our research identifies links between the occurrence of H5N1 by area and a set of socio-ecological factors including altitude, population density, poultry density, and the shortest path distances to inland water, coastlines, migrating routes, railways, and roads. This study seeks to lay a solid foundation for the interdisciplinary study of this and other influenza outbreaks. It will provide substantive information for containing H5N1 outbreaks.

Different Environmental Drivers of Highly Pathogenic Avian Influenza H5N1 Outbreaks in Poultry and Wild Birds

“…In this case, areas with a higher poultry density might not necessary have a higher risk. Hence, in line with previous findings in China [17], [18], we also found that an increased poultry density did not lead to an increased risk of HPAI H5N1 outbreak. The intensive commercial poultry production systems in Europe may have a relatively high level of bio-security, in contrast to some regions where poultry are free ranging during daylight hours, such as the free-grazing poultry areas in the Danube River delta [5].…”

Modeling tuberculosis transmission flow in China

“…Previous studies indicated that per capita GDP and TB incidence at the provincial level had a negative relationship. Similar results were observed for other infectious diseases such as SARS and H5N1 [4,57]. Therefore, improving the local economy is bene cial to the control of TB in the origin.…”

Regional transport and its association with tuberculosis in the Shandong province of China, 2009–2011

“…Altitude (or elevation) has been applied as a significant predictor in a number of studies of infectious diseases, including TB (Saito et al, 2006) and avian influenza (Gilbert et al, 2008;Ge et al, 2012). In particular, altitude has a protective effect against TB in Peru in which lower disease prevalence and increased household clustering of TB was found in high altitude villages compared to those at sea level (Saito et al, 2006).…”

“…All data were converted into 1 Â 1 square kilometer lattice. This spatial resolution was chosen because it is a broadly accepted spatial unit for ecological studies (Ge et al, 2012;Qiu et al, 2014). Moreover, research have shown that an individual's activity space varies between 800 and 1000 meters and that a finer spatial resolution may cause structural clutter that affects decision-making (Lai et al, 2015).…”