Modeling the Role of Land-Use Change on the Spread of Infectious Disease

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Description
Land-use change has arguably been the largest contributor to the emergence of novel zoonotic diseases within the past century. However, the relationship between patterns of land-use change and the resulting landscape configuration on disease spread is poorly understood as current

Land-use change has arguably been the largest contributor to the emergence of novel zoonotic diseases within the past century. However, the relationship between patterns of land-use change and the resulting landscape configuration on disease spread is poorly understood as current cross-species disease transmission models have not adequately incorporated spatial features of habitats. Furthermore, mathematical-epidemiological studies have not considered the role that land-use change plays in disease transmission throughout an ecosystem.

This dissertation models how a landscape's configuration, examining the amount and shape of habitat overlap, contributes to cross-species disease transmission to determine the role that land-use change has on the spread of infectious diseases. To approach this, an epidemiological model of transmission between a domesticated and a wild species is constructed. Each species is homogeneously mixed in its respective habitat and heterogeneously mixed in the habitat overlap, where cross-species transmission occurs. Habitat overlap is modeled using landscape ecology metrics.

This general framework is then applied to brucellosis transmission between elk and cattle in the Greater Yellowstone Ecosystem. The application of the general framework allows for the exploration of how land-use change has contributed to brucellosis prevalence in these two species, and how land management can be utilized to control disease transmission. This model is then extended to include a third species, bison, in order to provide insight to the indirect consequences of disease transmission for a species that is situated on land that has not been converted. The results of this study can ultimately help stakeholders develop policy for controlling brucellosis transmission between livestock, elk, and bison, and in turn, could lead to less disease prevalence, reduce associated costs, and assist in population management.

This research contributes novelty by combining landscape ecology metrics with theoretical epidemiological models to understand how the shape, size, and distribution of habitat fragments on a landscape affect cross-species disease transmission. The general framework demonstrates how habitat edge in single patch impacts cross-species disease transmission. The application to brucellosis transmission in the Greater Yellowstone Ecosystem between elk, cattle, and bison is original research that enhances understanding of how land conversion is associated with enzootic disease spread.
Date Created
2020
Agent

Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission

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Description

Background
In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually transmitted, although sustained autochthonous transmission due to sexual

Background
In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually transmitted, although sustained autochthonous transmission due to sexual transmission alone has not been observed, indicating the reproduction number (R0) for sexual transmission alone is less than 1. Critical to the assessment of outbreak risk, estimation of the potential attack rates, and assessment of control measures, are estimates of the basic reproduction number, R0.
Methods
We estimated the R0 of the 2015 ZIKV outbreak in Barranquilla, Colombia, through an analysis of the exponential rise in clinically identified ZIKV cases (n = 359 to the end of November, 2015).
Findings
The rate of exponential rise in cases was ρ = 0.076 days[superscript −1], with 95% CI [0.066,0.087] days[superscript −1]. We used a vector-borne disease model with additional direct transmission to estimate the R0; assuming the R0 of sexual transmission alone is less than 1, we estimated the total R0 = 3.8 [2.4,5.6], and that the fraction of cases due to sexual transmission was 0.23 [0.01,0.47] with 95% confidence.
Interpretation
This is among the first estimates of R0 for a ZIKV outbreak in the Americas, and also among the first quantifications of the relative impact of sexual transmission.

Date Created
2016-10-17