Spatial Temporal Incidence and Environmental Determinants of Leptospirosis in Brazil Open Access

Wilt, Grete (2016)

Permanent URL: https://etd.library.emory.edu/concern/etds/12579s883?locale=en%255D
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Abstract

Background: Leptospirosis is a neglected tropical disease with 1.0 million cases and 59,000 deaths occurring each year. The major disease burden is placed on socio- economically depressed populations. Leptospirosis persists in an endemic state throughout Brazil, where ~3,000 cases are reported per year. Climate change in this country affects the ecology of numerous zoonotic diseases, leading to the increased risk of an outbreak.

Methods: In this study, we investigated the spatial temporal variations of leptospirosis incidence to enhance the understanding of leptospirosis patterns at a municipal scale. Additionally a general linear mixed model controlling for municipality and time was constructed to identify environmental predictors of leptospirosis.

Results: Results suggested high incidence rates of leptospirosis are spatially clustered in Southeastern Brazil. Temporal analyses indicated high seasonality, peaking from December-March, with overall trend of total cases and average cases reported increasing overtime as well. Our results suggest that increases in leptospirosis incidence were significantly associated with increases in mean monthly precipitation over time, mean monthly vegetation index score over time and year. Municipalities with lower urban populations and increased mean soil water pH and isothermality, interpreted as higher temperature evenness over the course of a year, were also significantly associated with higher leptospirosis incidence at baseline. Mean monthly temperature was not significantly associated with an increase in leptospirosis incidence in the final model.

Discussion: Our results clearly show the seasonal temporality of leptospirosis, with increases in leptospirosis observed over time. Our model illustrates an increase in leptospirosis in rural regions with high vegetation in time-periods of elevated rainfall. This approach assists in identifying spatial regions and time-periods of high potential infection risk that may lead to the development of strategies to improve targeted prevention and response.

Table of Contents

Introduction…………………………………………………………………………..1

Background……………………………………………………………………………1

Epidemiology, Environmental Predictors and Prior Research of Leptospirosis …3

A Spatial Temporal Analysis ...……………………………………………………5

Purpose of Study …………………………………………………………………….5

Methods ……………………………………………………………………………….6

Study Design …………………………………………………………………………6

Data Collection, Matching and Merging Methods……………………………7

Descriptive Analysis ………………………………………………………………..8

Spatial Data Statistics ……………………………………………………………...8

Spatial Descriptive Statistics ……………………………………………………..8

Global Autocorrelation …………………………………………………………....9

Local Spatial Autocorrelation …………………………………………………....9

Hot-Spot Analysis ………………………………………………………..…….....10

Temporal Analysis ………………………………………………………………...10

Spatial Temporal Environmental Model………………………………………12

Results ……………………………………………………………………………….13

Descriptive Analysis ………………………………………………………………13

Spatial Data Statistics ……………………………………………………………13

Spatial Descriptive Statistics ……………………………………………….….13

Global Autocorrelation ………………………………………………………....14

Local Autocorrelation ………………………………………………………..….14

Hot-Spot Analysis …………………………………………………………….....15

Temporal Analysis ………………………………………………………………..15

Spatial Temporal Environmental Model …………………………………….16

Discussion ………………………………………………………………………….18

Limitations …………………………………………………………………………21

Public Health Significance ……………………………………………………..23

Conclusions ………………………………………………………………………..25

Works Cited…………………………………………………………………………27

Appendix …………………………………………………………………………..31

Table 1: Source of independent variable data ……………………………..31

Table 2: Characteristics of sample……………………………………………32

Figure 1: Total leptospirosis cases over study years presented by municipality….33

Figure 2: Total leptospirosis incidence over study years ………………...34

Figure 3: Local indicators of spatial association ……………………….....35

Figure 4: Hotspot and Cold Spot analysis…………………………………...36

Figure 5: Total cases of leptospirosis by month…………………………...37

Figure 6: Total cases of leptospirosis by year……………………………....37

Figure 7: Time series analysis of leptospirosis cases …………………....38

Table 3: Taxonomy of multilevel models…………………………………...39

Table 4: Results of fitting taxonomic multilevel models………………..40

Table 5: Error Covariance Structure for Selected Model………………...42

Figure 8: Fitted values vs. standardized residuals ………….…………...43

Figure 9: Fixed vs. Random Residual Plot…………….…………………....43

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