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Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil

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July 17th, 2020

Nationwide disease surveillance at a high spatial resolution is desired for many infectious diseases, including Visceral Leishmaniasis. Statistical and mathematical models using data collected from surveillance activities often use a spatial resolution and scale either constrained by data availability or chosen arbitrarily. Sensitivity of model results to the choice of spatial resolution and scale is not, however, frequently evaluated. This study aims to determine if the choice of spatial resolution and scale are likely to impact statistical and mathematical analyses. Visceral Leishmaniasis in Brazil is used as a case study. Probabilistic characteristics of disease incidence, representing a likely outcome in a model, are compared across spatial resolutions and scales. Best fitting distributions were fit to annual incidence from 2004 to 2014 by municipality and by state. Best fits were defined as the distribution family and parameterization minimizing the sum of absolute error, evaluated through a simulated annealing algorithm. Gamma and Poisson distributions provided best
fits for incidence, both among individual states and nationwide. Comparisons of distributions using Kullback-Leibler divergence shows that incidence by state and by municipality do not follow distributions that provide equivalent information. Few states with Gamma distributed
incidence follow a distribution closely resembling that for national incidence. These results demonstrate empirically how choice of spatial resolution and scale can impact mathematical and statistical models




Servadio JL., Machado A., Alvarez J., de Ferreira Lima Junior FE., Vieira Alves R. and Convertino M.




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Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil

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Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil


Participants:

University of MinnesotaEnvironmental Health Sciences. School of Public Health. University of Minnesota (UMM).

North Carolina State UniversityDepartment of Population Health and Pathobiology. College of Veterinary Medicine. North Carolina State University (NCSU).

Universidad ComplutenseCentro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

Ministério da SaúdeSecretaria de Vigilância em Saúde. Ministério da Saúde.

University HokkaidoNexus Group. Graduate School of Information Science and Technology and GI-CoRE Station for Big-Data and Cybersecurity. University Hokkaido.







PLoS ONE
FACTOR YEAR Q
2.740 2019

NLMID: 101285081

PMID: 32678864

ISSN: 1932-6203



TITLE: Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil


JOURNAL: PLoS ONE


NUMERACIÓN: 15(7):e0235920


AÑO: 2020


PUBLISHER: Public Library Science


AUTHORS: Servadio JL., Machado A., Alvarez J., de Ferreira Lima Junior FE., Vieira Alves R. and Convertino M.


VISAVET PARTICIPANTS


Julio Álvarez Sánchez

DOI: https://doi.org/ 10.1371/journal.pone.0235920


CITE THIS PUBLICATION:

Servadio JL., Machado A., Alvarez J., de Ferreira Lima Junior FE., Vieira Alves R. and Convertino M. Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil. PLoS ONE. 15(7):e0235920. 2020. (A). ISSN: 1932-6203. DOI: 10.1371/journal.pone.0235920