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

Author

Listed:
  • Joseph L Servadio
  • Gustavo Machado
  • Julio Alvarez
  • Francisco Edilson de Ferreira Lima Júnior
  • Renato Vieira Alves
  • Matteo Convertino

Abstract

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.

Suggested Citation

  • Joseph L Servadio & Gustavo Machado & Julio Alvarez & Francisco Edilson de Ferreira Lima Júnior & Renato Vieira Alves & Matteo Convertino, 2020. "Information differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.
    • Handle: RePEc:plo:pone00:0235920
    DOI: 10.1371/journal.pone.0235920
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    References listed on IDEAS

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    1. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
    2. Francisco Rogerlândio Martins-Melo & Mauricélia da Silveira Lima & Alberto Novaes Ramos Jr & Carlos Henrique Alencar & Jorg Heukelbach, 2014. "Mortality and Case Fatality Due to Visceral Leishmaniasis in Brazil: A Nationwide Analysis of Epidemiology, Trends and Spatial Patterns," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    3. Eduardo A Undurraga & Yara A Halasa & Donald S Shepard, 2013. "Use of Expansion Factors to Estimate the Burden of Dengue in Southeast Asia: A Systematic Analysis," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 7(2), pages 1-15, February.
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