Social and environmental determinants of leptospirosis transmission in informal settings
Lead Research Organisation:
Lancaster University
Department Name: Medicine
Abstract
This project addresses the social and environmental determinants of zoonotic leptospirosis transmission in informal settlements in Salvador, Brazil, in collaboration with FioCruz. It is embedded within an ongoing collaborative programme of research on the eco-epidemiology of leptospirosis in the Brazilian city of Salvador, in which Lancaster (CHICAS) leads on the development and application of statistical methods for spatio-temporally referenced data. Specific aims include: estimating the impact of Leptospira reservoir (Rattus Norvegicus) population control measures; developing a typology of urban environments for risk-classification.
People |
ORCID iD |
| Emanuele Giorgi (Primary Supervisor) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/R502200/1 | 01/10/2017 | 31/03/2021 | |||
| 1964635 | Studentship | MR/R502200/1 | 01/10/2017 | 30/09/2021 |
| Title | A geostatistical model for joint modelling of human infection risk and animal/vector abundance |
| Description | The risk of human infection with zoonotic and vector-borne pathogens is driven by the relative abundance of vector and reservoir populations. Understanding the role of these animals in transmission is therefore important for effective control. There are often multiple ways to imperfectly measure relative abundance, but currently no methods exist which allow these different measures to be combined together within a single joint geostatistical model in a principled manner or used to predict human infection risk. We have developed a multivariate geostatistical model which allows us to jointly model multiple indices for relative abundance and human seroprevalence. We then apply this model to the case of leptospirosis, a prevalent zoonotic disease transmitted to humans by rat populations, combining data for three indices of rat abundance and human Leptospira seroprevalence data collected in a vulnerable urban community in Brazil. We show how 'rattiness', our relative abundance process, can be used to predict human Leptospira seroprevalence and make inferences about important risk factors. This methodology can be used to directly model the role of vector/reservoir abundance in the transmission of a wide range of zoonotic and vector-borne infections. This is currently unpublished, but will be submitted soon and made publicly available. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | This is in the process of being written up and will be submitted as two articles (one for the joint vector/animal abundance model) and another for the complete abundance and human infection model. |
| Description | Brazil leptospirosis study |
| Organisation | Federal University of Bahia |
| Country | Brazil |
| Sector | Academic/University |
| PI Contribution | I have helped to develop tools for analysis and carry out analyses for a long-term longitudinal leptospirosis cohort study, a cross-sectional leptospirosis study and a longitudinal Leptospira antibody study. I have also contributed in the study design for a new large grant, which was successfully funded. |
| Collaborator Contribution | Conception and organisation of the studies, data collection and collaborative work in the analysis and interpretation of the results. |
| Impact | Multiple scientific articles - none of which have been completed and submitted yet. |
| Start Year | 2018 |
| Description | Brazil leptospirosis study |
| Organisation | Oswaldo Cruz Foundation (Fiocruz) |
| Country | Brazil |
| Sector | Public |
| PI Contribution | I have helped to develop tools for analysis and carry out analyses for a long-term longitudinal leptospirosis cohort study, a cross-sectional leptospirosis study and a longitudinal Leptospira antibody study. I have also contributed in the study design for a new large grant, which was successfully funded. |
| Collaborator Contribution | Conception and organisation of the studies, data collection and collaborative work in the analysis and interpretation of the results. |
| Impact | Multiple scientific articles - none of which have been completed and submitted yet. |
| Start Year | 2018 |