Luan Marca , Marco Tulio Aniceto Franca , Augusto Mussi Alvim , Evandro Tatim da Silva
{"title":"Deforestation, land use, and malaria incidence in the Brazilian Amazon: A spatial analysis","authors":"Luan Marca , Marco Tulio Aniceto Franca , Augusto Mussi Alvim , Evandro Tatim da Silva","doi":"10.1016/j.forpol.2025.103653","DOIUrl":null,"url":null,"abstract":"<div><div>This study analyzes the determinants of malaria incidence in the Brazilian Amazon, focusing on patterns of deforestation, agricultural mechanization, and their spatio-temporal dynamics. Using municipal-level panel data (2007–2020) and spatial econometric models, we identify two main findings: Deforestation increases malaria incidence in a non-linear fashion, with significant impacts lasting up to five years and a renewed peak nearly a decade later. Mechanization reduces transmission: A 1 % increase in heavy machinery (e.g., crawler tractors) is associated with a 0.67 % decrease in the incidence rate. A 1 % increase in light machinery (e.g., wheeled tractors) is associated with a 0.37 % decrease, attributable to intensified land use and habitat management. Policy implications may include targeted subsidies for light mechanization leasing in high-incidence municipalities. This strategy could simultaneously curb malaria and deforestation by leveraging degraded pasture areas as expansion zones for cultivation using light machinery, thus eliminating the need for forest invasion.</div></div>","PeriodicalId":12451,"journal":{"name":"Forest Policy and Economics","volume":"181 ","pages":"Article 103653"},"PeriodicalIF":4.6000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forest Policy and Economics","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389934125002321","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/10/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This study analyzes the determinants of malaria incidence in the Brazilian Amazon, focusing on patterns of deforestation, agricultural mechanization, and their spatio-temporal dynamics. Using municipal-level panel data (2007–2020) and spatial econometric models, we identify two main findings: Deforestation increases malaria incidence in a non-linear fashion, with significant impacts lasting up to five years and a renewed peak nearly a decade later. Mechanization reduces transmission: A 1 % increase in heavy machinery (e.g., crawler tractors) is associated with a 0.67 % decrease in the incidence rate. A 1 % increase in light machinery (e.g., wheeled tractors) is associated with a 0.37 % decrease, attributable to intensified land use and habitat management. Policy implications may include targeted subsidies for light mechanization leasing in high-incidence municipalities. This strategy could simultaneously curb malaria and deforestation by leveraging degraded pasture areas as expansion zones for cultivation using light machinery, thus eliminating the need for forest invasion.
期刊介绍:
Forest Policy and Economics is a leading scientific journal that publishes peer-reviewed policy and economics research relating to forests, forested landscapes, forest-related industries, and other forest-relevant land uses. It also welcomes contributions from other social sciences and humanities perspectives that make clear theoretical, conceptual and methodological contributions to the existing state-of-the-art literature on forests and related land use systems. These disciplines include, but are not limited to, sociology, anthropology, human geography, history, jurisprudence, planning, development studies, and psychology research on forests. Forest Policy and Economics is global in scope and publishes multiple article types of high scientific standard. Acceptance for publication is subject to a double-blind peer-review process.