02480nas a2200265   4500000000100000008004100001260003700042653005700079653004900136653002100185653002500206100001600231700001400247700001400261700003200275700001300307700001700320700001600337245015000353856009800503300001300601490000700614520157900621022001402200       2020                            d  bPublic Library of Science (PLoS)10aGeneral Biochemistry, Genetics and Molecular Biology10aGeneral Agricultural and Biological Sciences10aGeneral Medicine10aDisease surveillance1 aServadio JL1 aMachado G1 aAlvarez J1 ade Ferreira Lima Júnior FE1 aAlves RV1 aConvertino M1 aCarvalho LH00aInformation differences across spatial resolutions and scales for disease surveillance and analysis: The case of Visceral Leishmaniasis in Brazil  uhttps://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0235920&type=printable  ae02359200 v153 aNationwide 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.  a1932-6203