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Synergistic interactions of environmental degradation, socio-economic development and infectious disease dynamics in the Amazon region

Introduction

The Amazonian region of Peru and Brazil are undergoing large-scale ecological and economic changes. The goal of this project is to understand diseases transition and its spatial-explicit dynamics in the context of the land-use and socio-economic changes in this important frontier region.

Our team is investigating how these changes connect to the population dynamics of infectious diseases, especially malaria. We aim to develop an integrated model that will combine geospatial and epidemiological simulation with agent-based simulation to represent these complex socio-ecological interactions and feedback. The team is using remote sensing data, epidemiological time series, and socio-economic survey data.

We are focusing our efforts this week to conceptualize the connection between data and models.

Site: https://www.sesync.org/project/propose-a-pursuit/synergistic-interactions-of-environmental-degradation-socio-economic

Data

Survey data

  • Self-reported malaria in the last 12 months
  • Inquiry about their history of malaria infections
  • Indirect effects of malaria
  • Morbidity
  • Demographic information from the interviewee and the house mates
  • Records the ownership of objects such as appliances and vehicles
  • Records all the occupations and sources of income of the householders
  • Five blocks collect data on house construction material
  • Accessibility
  • Source of water
  • Garbage disposal
  • Electricity
  • Questions on activities and habits associated with malaria exposure and usage of bed nets as well as other mosquito deterrents are in the last blocks
  • Mobility by motivation, frequency and time spent

Remote Sensing

complete

SIVEP data

Malaria cases from 2003 to the present data were obtained from the Epidemiological Surveillance System (SIVEP) of the Ministry of Health, Brazil.

Surveyed localities in Acre

Find all surveyed localities and the urban gradient classification! https://rawgit.com/anapdalasta/Localities-of-Alto-Juru-region/master/index.html

Collaborators

  • Andres Baeza, Arizona State University
  • Mercedes Pascual, University of Chicago
  • Mauricio Santos Vega, University of Chicago
  • Raquel Lana, Fundação Oswaldo Cruz
  • Claudia Codeco, Fundação Oswaldo Cruz
  • Andrew Dobson, Princeton University
  • Andrew Bell, New York University
  • Gabriel Carrasco Escobar, Universidad Peruana Cayetano Heredia
  • Marcia Castro, Harvard University
  • Zulma Cucunuba , Imperial College London
  • Giulio de Leo, Stanford University
  • Amir Jina, University of Chicago
  • Rachel Lowe, London School of Hygiene and Tropical Medicine
  • Antonio Miguel Vieira Monteiro, Instituto Nacional de Pesquisas Espaciais
  • Ana Paula Dal'Asta, Instituto Nacional de Pesquisas Espaciais

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