Spatio-temporal magnitude and direction of highly pathogenic avian influenza (H5N1) outbreaks in Bangladesh

TY - JOUR

T1 - Spatio-temporal magnitude and direction of highly pathogenic avian influenza (H5N1) outbreaks in Bangladesh

AU - Ahmed, Syed Sayeem Uddin

AU - Ersbøll, Annette Kjær

AU - Biswas, Paritosh K.

AU - Christensen, Jens Peter

AU - Toft, Nils

PY - 2011/9/9

Y1 - 2011/9/9

N2 - Background: The number of outbreaks of HPAI-H5N1 reported by Bangladesh from 2007 through 2011 placed the country among the highest reported numbers worldwide. However, so far, the understanding of the epidemic progression, direction, intensity, persistence and risk variation of HPAI-H5N1 outbreaks over space and time in Bangladesh remains limited. Methodology/Principal Findings: To determine the magnitude and spatial pattern of the highly pathogenic avian influenza A subtype H5N1 virus outbreaks over space and time in poultry from 2007 to 2009 in Bangladesh, we applied descriptive and analytical spatial statistics. Temporal distribution of the outbreaks revealed three independent waves of outbreaks that were clustered during winter and spring. The descriptive analyses revealed that the magnitude of the second wave was the highest as compared to the first and third waves. Exploratory mapping of the infected flocks revealed that the highest intensity and magnitude of the outbreaks was systematic and persistent in an oblique line that connects south-east to north-west through the central part of the country. The line follows the Brahmaputra-Meghna river system, the junction between Central Asian and East Asian flyways, and the major poultry trading route in Bangladesh. Moreover, several important migratory bird areas were identified along the line. Geostatistical analysis revealed significant latitudinal directions of outbreak progressions that have similarity to the detected line of intensity and magnitude. Conclusion/Significance: The line of magnitude and direction indicate the necessity of mobilizing maximum resources on this line to strengthen the existing surveillance.

AB - Background: The number of outbreaks of HPAI-H5N1 reported by Bangladesh from 2007 through 2011 placed the country among the highest reported numbers worldwide. However, so far, the understanding of the epidemic progression, direction, intensity, persistence and risk variation of HPAI-H5N1 outbreaks over space and time in Bangladesh remains limited. Methodology/Principal Findings: To determine the magnitude and spatial pattern of the highly pathogenic avian influenza A subtype H5N1 virus outbreaks over space and time in poultry from 2007 to 2009 in Bangladesh, we applied descriptive and analytical spatial statistics. Temporal distribution of the outbreaks revealed three independent waves of outbreaks that were clustered during winter and spring. The descriptive analyses revealed that the magnitude of the second wave was the highest as compared to the first and third waves. Exploratory mapping of the infected flocks revealed that the highest intensity and magnitude of the outbreaks was systematic and persistent in an oblique line that connects south-east to north-west through the central part of the country. The line follows the Brahmaputra-Meghna river system, the junction between Central Asian and East Asian flyways, and the major poultry trading route in Bangladesh. Moreover, several important migratory bird areas were identified along the line. Geostatistical analysis revealed significant latitudinal directions of outbreak progressions that have similarity to the detected line of intensity and magnitude. Conclusion/Significance: The line of magnitude and direction indicate the necessity of mobilizing maximum resources on this line to strengthen the existing surveillance.

KW - Animals

KW - Bangladesh

KW - Bayes Theorem

KW - Disease Outbreaks

KW - Geography

KW - Influenza A Virus, H5N1 Subtype

KW - Influenza in Birds

KW - Longevity

KW - Poultry

KW - Time Factors

U2 - 10.1371/journal.pone.0024324

DO - 10.1371/journal.pone.0024324

M3 - Journal article

C2 - 21931683

SN - 1932-6203

VL - 6

SP - e24324

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 9

ER -