The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context

Summary: Background: Since 1950, there have been increasingly atypical climatological patterns in the Amazon, some caused by El Niño-Southern Oscillation (ENSO) events (El Niño or La Niña). In 2023–2024, the region faced the most severe droughts in recorded history. These weather patterns are major...

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Main Authors: Nicholas J. Arisco, Cassio Peterka, Joel Schwartz, Marcia C. Castro
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:The Lancet Regional Health. Americas
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Online Access:http://www.sciencedirect.com/science/article/pii/S2667193X25001991
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author Nicholas J. Arisco
Cassio Peterka
Joel Schwartz
Marcia C. Castro
author_facet Nicholas J. Arisco
Cassio Peterka
Joel Schwartz
Marcia C. Castro
author_sort Nicholas J. Arisco
collection DOAJ
description Summary: Background: Since 1950, there have been increasingly atypical climatological patterns in the Amazon, some caused by El Niño-Southern Oscillation (ENSO) events (El Niño or La Niña). In 2023–2024, the region faced the most severe droughts in recorded history. These weather patterns are major drivers of malaria. Deforestation has exacerbated these impacts. This study estimates the impact of weather and ENSO events on malaria transmission in the Brazilian Amazon from 2003 to 2022. Methods: We used daily individual-level data on reported malaria cases from the Brazilian Malaria Epidemiological Surveillance Information System (Sivep-Malaria). A case-crossover approach was used to analyze the effects of lagged weather variables and ENSO events on malaria transmission at the Amazon-wide and state levels. Generalized additive quasi-Poisson models were used to assess the influence of ENSO events on malaria cases. Findings: From 2003 to 2022, 5,381,105 malaria cases were recorded in the Brazilian Amazon. Temperatures between 25.64 and 30.85 °C and precipitation >4.46 cm in the week prior to infection increased malaria infection risk up to 9% (95% CI: 8–10%) and 86% (95% CI: 35–155%), respectively. Two- and three-week lagged temperatures >25.64 °C and diurnal variation >6.75 °C reduced malaria infection risk by a maximum of 27% (95% CI: 19–33%) and 59% (95% CI: 52–69%). State-specific variations in relationships were notable. ENSO events significantly influenced weather conditions and malaria transmission, with El Niño and La Niña associated with a net reduction in malaria cases of 2179 (95% CI: 1837, 2520) and 37,258 (95% CI: 37,171, 37,345), respectively, with marked spatiotemporal heterogeneity in effect. Interpretation: This study clarifies the short- and long-term influences of weather and ENSO events on malaria transmission in the Brazilian Amazon. The results underscore the high degree of heterogeneity in the effects of weather on malaria transmission in the region, and the need for proactive and fine-scale malaria control based on weather forecasting and the development of early warning systems to achieve malaria elimination. Funding: This research was supported by the Division of Intramural Research at the National Institute of Allergy and Infectious Diseases (Award Number: 2U19AI089681-08) and the Foundation for the National Institutes of Health (Award Number: NIH/T32 AI007535).
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spelling doaj-art-710ea7ee6136466daa9a73385def7b932025-08-20T03:12:47ZengElsevierThe Lancet Regional Health. Americas2667-193X2025-09-014910118910.1016/j.lana.2025.101189The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in contextNicholas J. Arisco0Cassio Peterka1Joel Schwartz2Marcia C. Castro3Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USASuperintendência de Vigilância em Saúde do Amapá, Governo do Estado do Amapá, Macapá, AP, 68902-865, BrazilDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USADepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA; Corresponding author. Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Bldg I, Room 1102A, Boston, MA 02115, USA.Summary: Background: Since 1950, there have been increasingly atypical climatological patterns in the Amazon, some caused by El Niño-Southern Oscillation (ENSO) events (El Niño or La Niña). In 2023–2024, the region faced the most severe droughts in recorded history. These weather patterns are major drivers of malaria. Deforestation has exacerbated these impacts. This study estimates the impact of weather and ENSO events on malaria transmission in the Brazilian Amazon from 2003 to 2022. Methods: We used daily individual-level data on reported malaria cases from the Brazilian Malaria Epidemiological Surveillance Information System (Sivep-Malaria). A case-crossover approach was used to analyze the effects of lagged weather variables and ENSO events on malaria transmission at the Amazon-wide and state levels. Generalized additive quasi-Poisson models were used to assess the influence of ENSO events on malaria cases. Findings: From 2003 to 2022, 5,381,105 malaria cases were recorded in the Brazilian Amazon. Temperatures between 25.64 and 30.85 °C and precipitation >4.46 cm in the week prior to infection increased malaria infection risk up to 9% (95% CI: 8–10%) and 86% (95% CI: 35–155%), respectively. Two- and three-week lagged temperatures >25.64 °C and diurnal variation >6.75 °C reduced malaria infection risk by a maximum of 27% (95% CI: 19–33%) and 59% (95% CI: 52–69%). State-specific variations in relationships were notable. ENSO events significantly influenced weather conditions and malaria transmission, with El Niño and La Niña associated with a net reduction in malaria cases of 2179 (95% CI: 1837, 2520) and 37,258 (95% CI: 37,171, 37,345), respectively, with marked spatiotemporal heterogeneity in effect. Interpretation: This study clarifies the short- and long-term influences of weather and ENSO events on malaria transmission in the Brazilian Amazon. The results underscore the high degree of heterogeneity in the effects of weather on malaria transmission in the region, and the need for proactive and fine-scale malaria control based on weather forecasting and the development of early warning systems to achieve malaria elimination. Funding: This research was supported by the Division of Intramural Research at the National Institute of Allergy and Infectious Diseases (Award Number: 2U19AI089681-08) and the Foundation for the National Institutes of Health (Award Number: NIH/T32 AI007535).http://www.sciencedirect.com/science/article/pii/S2667193X25001991MalariaClimateExtreme eventsBrazilian Amazon
spellingShingle Nicholas J. Arisco
Cassio Peterka
Joel Schwartz
Marcia C. Castro
The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
The Lancet Regional Health. Americas
Malaria
Climate
Extreme events
Brazilian Amazon
title The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
title_full The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
title_fullStr The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
title_full_unstemmed The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
title_short The impact of weather and extreme events on malaria transmission in the Brazilian Amazon: a case-crossover and population-based studyResearch in context
title_sort impact of weather and extreme events on malaria transmission in the brazilian amazon a case crossover and population based studyresearch in context
topic Malaria
Climate
Extreme events
Brazilian Amazon
url http://www.sciencedirect.com/science/article/pii/S2667193X25001991
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