On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis

Malar J. 2022 Feb 17;21(1):52. doi: 10.1186/s12936-021-04037-x.

Abstract

Background: Malaria incidence in Brazil reversed its decreasing trend when cases from recent years, as recent as 2015, exhibited an increase in the Brazilian Amazon basin, the area with the highest transmission of Plasmodium vivax and Plasmodium falciparum. In fact, an increase of more than 20% in the years 2016 and 2017 revealed possible vulnerabilities in the national malaria-control programme.

Methods: Factors potentially associated with this reversal, including migration, economic activities, and deforestation, were studied. Past incidences of malaria cases due to P. vivax and P. falciparum were analysed with a spatio-temporal Bayesian model using more than 5 million individual records of malaria cases from January of 2003 to December of 2018 in the Brazilian Amazon to establish the municipalities with unexpected increases in cases.

Results: Plasmodium vivax incidence surpassed the past trends in Amazonas (AM), Amapá (AP), Acre (AC), Pará (PA), Roraima (RR), and Rondônia (RO), implying a rebound of these states between 2015 and 2018. On the other hand, P. falciparum also surpassed the past trends in AM, AC, AP, and RR with less severity than P. vivax incidence. Outdoor activities, agricultural activities, accumulated deforestation, and travelling might explain the rebound in malaria cases in RR, AM, PA, and RO, mainly in P. vivax cases. These variables, however, did not explain the rebound of either P. vivax and P. falciparum cases in AC and AP states or P. falciparum cases in RR and RO states.

Conclusion: The Amazon basin has experienced an unexpected increase in malaria cases, mainly in P. vivax cases, in some regions of the states of Amazonas, Acre, Pará, Amapá, Roraima, and Rondônia from 2015 to 2018 and agricultural activities, outdoor activities, travelling activities, and accumulated deforestation appear linked to this rebound of cases in particular regions with different impact. This shows the multifactorial effects and the heterogeneity of the Amazon basin, boosting the necessity of focusing the malaria control programme on particular social, economic, and environmental conditions.

Keywords: Malaria rebound; Plasmodium falciparum; Plasmodium vivax; Spatio-temporal Bayesian model.

MeSH terms

  • Bayes Theorem
  • Brazil / epidemiology
  • Humans
  • Malaria* / epidemiology
  • Malaria, Falciparum* / epidemiology
  • Malaria, Falciparum* / prevention & control
  • Malaria, Vivax* / epidemiology
  • Malaria, Vivax* / prevention & control
  • Plasmodium falciparum
  • Plasmodium vivax
  • Spatio-Temporal Analysis