A validated agent-based model to study the spatial and temporal heterogeneities of malaria incidence in the rainforest environment

Publicado en Malaria Journal, v. 14:514
Autores

Pizzitutti, F., Pan, W.K.Y., Barbieri, A.F., Miranda, J.J., Feingold, B.J., Guedes, G.R., Alarcon-Valenzuela, J. and Mena, C.F.
Año de publicación 2015
DOI https://doi.org/10.1186/s12936-015-1030-7
Afiliaciones
  •  Universidad San Francisco de Quito, Diego de Robles, s/n, Cumbayá, Ecuador.
  • Duke University, 310 Trent Drive, Room 227, Box 90519, Durham, NC 27708,USA.
  • Instituto de Geociências‑IGC Belo Horizonte, Universidade Federal de Minas Gerais, Belo Horozonte, Brazil.
  • Oswaldo Cruz Foundation (FIOCRUZ), Universidad Peruana Cayetano Heredia, Lima, Peru.
  • Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, 1 University Place GEC, 145 Rensselaer, New York, NY 12144, USA.
  • College of Economics Departamento de Demografia/FACE/ UFMG, Office 3093, Av. Antônio Carlos, 6627‑Pampulha, Belo Horizonte, Minas Gerais 31270‑901, Brazil. 
Programa

CRN3
Proyecto CRN3036
Keywords
Agent-based model
Malaria
Amazon
Low endemicity
Anopheles darlingi
Plasmodium vivax
Plasmodium falciparum

Abstract

  • Background

The Amazon environment has been exposed in the last decades to radical changes that have been accompanied by a remarkable rise of both Plasmodium falciparum and Plasmodium vivax malaria. The malaria trans‑mission process is highly influenced by factors such as spatial and temporal heterogeneities of the environment and individual-based characteristics of mosquitoes and humans populations. All these determinant factors can be simu‑lated effectively trough agent-based models.

 

  • Methods

This paper presents a validated agent-based model of local-scale malaria transmission. The model reproduces the environment of a typical riverine village in the northern Peruvian Amazon, where the malaria transmission is highly seasonal and apparently associated with flooding of large areas caused by the neighbouring river. Agents representing humans, mosquitoes and the two species of Plasmodium (P. falciparum and P. vivax) are simulated in a spatially explicit representation of the environment around the village. The model environment includes: climate, people houses positions and elevation. A representation of changes in the mosquito breeding areas extension caused by the river flooding is also included in the simulation environment.

  • Results

A calibration process was carried out to reproduce the variations of the malaria monthly incidence over a period of 3 years. The calibrated model is also able to reproduce the spatial heterogeneities of local scale malaria transmission. A &ldquowhat if&rdquo eradication strategy scenario is proposed: if the mosquito breeding sites are eliminated through mosquito larva habitat management in a buffer area extended at least 200 m around the village, the malaria transmission is eradicated from the village.

  • Conclusions

The use of agent-based models can reproduce effectively the spatiotemporal variations of the malaria transmission in a low endemicity environment dominated by river floodings like in the Amazon.