Gabriella Barratt Heitmann, Xue Wu, Anna T Nguyen, Astrid Altamirano-Quiroz, Sydney R Fine, Bryan Fernandez-Camacho, Antony Barja, Renato Cava, Verónica Soto-Calle, Hugo Rodriguez, Gabriel Carrasco-Escobar, Adam Bennett, Alejandro Llanos-Cuentas, Erin A Mordecai, Michelle S Hsiang, Jade Benjamin-Chung
{"title":"Associations between weather and Plasmodium vivax malaria in an Amazonian elimination setting: a distributed lag analysis from 2017 to 2024.","authors":"Gabriella Barratt Heitmann, Xue Wu, Anna T Nguyen, Astrid Altamirano-Quiroz, Sydney R Fine, Bryan Fernandez-Camacho, Antony Barja, Renato Cava, Verónica Soto-Calle, Hugo Rodriguez, Gabriel Carrasco-Escobar, Adam Bennett, Alejandro Llanos-Cuentas, Erin A Mordecai, Michelle S Hsiang, Jade Benjamin-Chung","doi":"10.1186/s12936-026-06010-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There is limited evidence regarding the association between weather and Plasmodium vivax (Pv), particulary in Latin America where Pv is the predominant malaria species and key challenge for countries to achieve malaria elimination.</p><p><strong>Methods: </strong>We analyzed the association between weather and Pv malaria incidence from 2017 to 2024 in 136 communities in the Peruvian Amazon. Monthly community-level incidence was calculated using Pv case data from Notiweb, the national epidemiological surveillance system, and population census data. Predictors included weekly minimum and maximum temperature and total weekly precipitation and were calculated using hourly weather from the climate dataset ERA5. Non-linear distributed lag models were fit using a lookback period of 2-16 weeks. Temperature models were adjusted for total precipitation; precipitation models were adjusted for maximum temperature. Sub-group analyses were conducted by community type (adjacent to river versus highway) and El Niño Southern Oscillation (ENSO) period.</p><p><strong>Results: </strong>Minimum temperature at the 90th percentile (23.7°C) was associated with 10% (95% CI 5-14%) higher malaria incidence compared to the 5th percentile (20.5°C) at a 7-week lag. Maximum temperature at the 90th percentile (33.7°C) was associated with 10% (95% CI 8-13%) higher malaria incidence compared to the 5th percentile (29.6°C) at a 9-week lag. Total weekly precipitation at the 90th percentile (1000 mm) was associated with 29% (95% CI 24-33%) higher malaria incidence compared to weeks with the 5th percentile (57 mm) at an 11-week lag. Incidence was higher and associations were stronger in communities adjacent to rivers versus highways. Malaria incidence was lower during El Niño periods, and there was evidence of interaction on the multiplicative scale for the association between incidence, all weather predictors, and ENSO period.</p><p><strong>Conclusions: </strong>Pv malaria incidence was positively associated with higher temperatures and precipitation in an elimination setting in Peru, particularly in riverine communities during non-El Niño years, with longer lag periods than previously reported for such associations. These findings can inform malaria elimination interventions to combat the long-lasting effects of weather on Pv transmission.</p>","PeriodicalId":18317,"journal":{"name":"Malaria Journal","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13551811/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Malaria Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12936-026-06010-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: There is limited evidence regarding the association between weather and Plasmodium vivax (Pv), particulary in Latin America where Pv is the predominant malaria species and key challenge for countries to achieve malaria elimination.
Methods: We analyzed the association between weather and Pv malaria incidence from 2017 to 2024 in 136 communities in the Peruvian Amazon. Monthly community-level incidence was calculated using Pv case data from Notiweb, the national epidemiological surveillance system, and population census data. Predictors included weekly minimum and maximum temperature and total weekly precipitation and were calculated using hourly weather from the climate dataset ERA5. Non-linear distributed lag models were fit using a lookback period of 2-16 weeks. Temperature models were adjusted for total precipitation; precipitation models were adjusted for maximum temperature. Sub-group analyses were conducted by community type (adjacent to river versus highway) and El Niño Southern Oscillation (ENSO) period.
Results: Minimum temperature at the 90th percentile (23.7°C) was associated with 10% (95% CI 5-14%) higher malaria incidence compared to the 5th percentile (20.5°C) at a 7-week lag. Maximum temperature at the 90th percentile (33.7°C) was associated with 10% (95% CI 8-13%) higher malaria incidence compared to the 5th percentile (29.6°C) at a 9-week lag. Total weekly precipitation at the 90th percentile (1000 mm) was associated with 29% (95% CI 24-33%) higher malaria incidence compared to weeks with the 5th percentile (57 mm) at an 11-week lag. Incidence was higher and associations were stronger in communities adjacent to rivers versus highways. Malaria incidence was lower during El Niño periods, and there was evidence of interaction on the multiplicative scale for the association between incidence, all weather predictors, and ENSO period.
Conclusions: Pv malaria incidence was positively associated with higher temperatures and precipitation in an elimination setting in Peru, particularly in riverine communities during non-El Niño years, with longer lag periods than previously reported for such associations. These findings can inform malaria elimination interventions to combat the long-lasting effects of weather on Pv transmission.
背景:关于天气与间日疟原虫(Pv)之间关系的证据有限,特别是在拉丁美洲,Pv是主要的疟疾物种,也是各国实现消除疟疾的主要挑战。方法:分析2017 - 2024年秘鲁亚马逊136个社区天气与Pv疟疾发病率的关系。使用来自Notiweb、国家流行病学监测系统和人口普查数据的Pv病例数据计算每月社区发病率。预测因子包括周最低和最高温度以及周总降水,并使用ERA5气候数据集的每小时天气计算。采用2-16周的回顾期拟合非线性分布滞后模型。根据总降水量调整温度模式;降水模式根据最高温度进行了调整。根据群落类型(靠近河流还是靠近公路)和El Niño南方涛动(ENSO)时期进行亚群分析。结果:与第5百分位(20.5°C)相比,第90百分位(23.7°C)的最低温度与疟疾发病率在7周延迟时高出10% (95% CI 5-14%)相关。在9周后,第90百分位数(33.7°C)的最高温度与第5百分位数(29.6°C)相比,疟疾发病率高出10% (95% CI 8-13%)。在11周的滞后时间内,第90百分位数(1000毫米)的周总降水量与第5百分位数(57毫米)的周相比,疟疾发病率高出29% (95% CI 24-33%)。与公路相邻的社区相比,河流附近的社区发病率更高,相关性更强。在El Niño期间,疟疾发病率较低,并且在发病率、所有天气预测因子和ENSO期间之间的关联的乘法尺度上存在相互作用的证据。结论:在秘鲁,Pv疟疾发病率与高温和降水呈正相关,特别是在非厄尔尼诺Niño年的河流社区,这种关联的滞后期比以前报道的要长。这些发现可以为消除疟疾干预措施提供信息,以对抗天气对光伏传播的长期影响。
期刊介绍:
Malaria Journal is aimed at the scientific community interested in malaria in its broadest sense. It is the only journal that publishes exclusively articles on malaria and, as such, it aims to bring together knowledge from the different specialities involved in this very broad discipline, from the bench to the bedside and to the field.