Spatial and spatio-temporal analysis of malaria in the state of Acre, western Amazon, Brazil

  • Leonardo Augusto Kohara Melchior | Federal University of Acre; Faculty of Public Health, University of São Paulo, São Paulo, Brazil.
  • Francisco Chiaravalloti Neto Federal University of Acre, Brazil.


Since 2005, the State of Acre, western Amazon, Brazil, has reported the highest annual parasite incidence (API) of malaria among the Brazilian states. This study examines malaria incidence in Acre using spatial and spatio-temporal analysis based on an ecological time series study analyzing malaria cases and deaths for the time period 1992- 2014 and using secondary data. API indexes were calculated by age, sex, parasite species, ratio of Plasmodium vivax to P. falciparum malaria, malaria mortality rate and case fatality rate. SaTScan was used to detect spatial and spatio-temporal clusters of malaria cases and data were represented in the form of choropleth maps. A high-risk cluster of malaria was detected in Vale do Juruá and three low-risk clusters in Vale do Acre for both parasite species. Those younger than 19 years of age and females showed a high incidence of malaria in Vale do Juruá, but working-age males were the most affected in Vale do Acre. The malaria mortality rate showed a decreasing trend across the state, while the case fatality rate increased only in the micro-region of Rio Branco during the study period. We conclude that malaria is a focal disease in Acre showing different spatial and spatio-temporal patterns of cases and deaths that vary by age, sex, and parasite species. Malaria incidence is thought to be influenced by factors related to regional characteristics; therefore, appropriate disease and vector control strategies must be implemented at each locality.



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Original Articles
Malaria, Geographical information system, Clusters, Amazon, Brazil
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How to Cite
Kohara Melchior, L. A., & Chiaravalloti Neto, F. (2016). Spatial and spatio-temporal analysis of malaria in the state of Acre, western Amazon, Brazil. Geospatial Health, 11(3).