Disentangling the seasonality effects of malaria transmission in the Brazilian Amazon basin

被引:0
|
作者
Valiati, Naiara C. M. [1 ]
Rice, Benjamin [2 ]
Villela, Daniel A. M. [3 ,4 ]
机构
[1] Fundacao Oswaldo Cruz, Natl Sch Publ Hlth Sergio Arouca, Rio De Janeiro, Brazil
[2] Princeton Univ, Dept Ecol & Evolutionary Biol, Princeton, NJ USA
[3] Fundacao Oswaldo Cruz, Program Sci Comp, Rio De Janeiro, Brazil
[4] Princeton Univ, Ctr Hlth & Wellbeing, Sch Publ & Int Affairs, Princeton, NJ 08544 USA
来源
ROYAL SOCIETY OPEN SCIENCE | 2024年 / 11卷 / 07期
关键词
malaria; seasonality; mathematical model; NINO SOUTHERN-OSCILLATION; EL-NINO; RAINFALL; DEFORESTATION; TEMPERATURE; DYNAMICS; IMPACT; MODEL; ENSO;
D O I
10.1098/rsos.231764
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The evidence of seasonal patterns in malaria epidemiology in the Brazilian Amazon basin indicates the need for a thorough investigation of seasonality in this last and heterogeneous region. Additionally, since these patterns are linked to climate variables, malaria models should also incorporate them. This study applies wavelet analysis to incidence data from 2003 to 2020 in the Epidemiological Surveillance System for Malaria (SIVEP-Malaria) database. A mathematical model with climate-dependent parametrization is proposed to study counts of malaria cases over time based on notification data, temperature and rainfall. The wavelet analysis reveals marked seasonality in states Amazonas and Amap & aacute; throughout the study period, and from 2003 to 2012 in Par & aacute;. However, these patterns are not as marked in other states such as Acre and Par & aacute; in more recent years. The wavelet coherency analysis indicates a strong association between incidence and temperature, especially for the municipalities of Macap & aacute; and Manaus, and a similar association for rainfall. The mathematical model fits well with the observed temporal trends in both municipalities. Studies on climate-dependent mathematical models provide a good assessment of the baseline epidemiology of malaria. Additionally, the understanding of seasonality effects and the application of models have great potential as tools for studying interventions for malaria control.
引用
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页数:15
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