Felix K. Rubuga, Paula Moraga, Ayman Ahmed, Emmanuel Siddig, Eric Remera, Giovenale Moirano, Guéladio Cissé, Jürg Utzinger
{"title":"2012 年至 2022 年卢旺达疟疾的时空动态:特定人口分析","authors":"Felix K. Rubuga, Paula Moraga, Ayman Ahmed, Emmanuel Siddig, Eric Remera, Giovenale Moirano, Guéladio Cissé, Jürg Utzinger","doi":"10.1186/s40249-024-01237-w","DOIUrl":null,"url":null,"abstract":"Despite global efforts to reduce and eventually interrupt malaria transmission, the disease remains a pressing public health problem, especially in sub-Saharan Africa. This study presents a detailed spatio-temporal analysis of malaria transmission in Rwanda from 2012 to 2022. The main objective was to gain insights into the evolving patterns of malaria and to inform and tailor effective public health strategies. The study used yearly aggregated data of malaria cases from the Rwanda health management information system. We employed a multifaceted analytical approach, including descriptive statistics and spatio-temporal analysis across three demographic groups: children under the age of 5 years, and males and females above 5 years. Bayesian spatially explicit models and spatio scan statistics were utilised to examine geographic and temporal patterns of relative risks and to identify clusters of malaria transmission. We observed a significant increase in malaria cases from 2014 to 2018, peaking in 2016 for males and females aged above 5 years with counts of 98,645 and 116,627, respectively and in 2018 for under 5-year-old children with 84,440 cases with notable geographic disparities. Districts like Kamonyi (Southern Province), Ngoma, Kayonza and Bugesera (Eastern Province) exhibited high burdens, possibly influenced by factors such as climate, vector control practices, and cross-border dynamics. Bayesian spatially explicit modeling revealed elevated relative risks in numerous districts, underscoring the heterogeneity of malaria transmission in these districts, and thus contributing to an overall rising trend in malaria cases until 2018, followed by a subsequent decline. Our findings emphasize that the heterogeneity of malaria transmission is potentially driven by ecologic, socioeconomic, and behavioural factors. The study underscores the complexity of malaria transmission in Rwanda and calls for climate adaptive, gender-, age- and district-specific strategies in the national malaria control program. The emergence of both artemisinin and pyrethoids resistance and persistent high transmission in some districts necessitates continuous monitoring and innovative, data-driven approaches for effective and sustainable malaria control. ","PeriodicalId":13587,"journal":{"name":"Infectious Diseases of Poverty","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatio-temporal dynamics of malaria in Rwanda between 2012 and 2022: a demography-specific analysis\",\"authors\":\"Felix K. Rubuga, Paula Moraga, Ayman Ahmed, Emmanuel Siddig, Eric Remera, Giovenale Moirano, Guéladio Cissé, Jürg Utzinger\",\"doi\":\"10.1186/s40249-024-01237-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite global efforts to reduce and eventually interrupt malaria transmission, the disease remains a pressing public health problem, especially in sub-Saharan Africa. This study presents a detailed spatio-temporal analysis of malaria transmission in Rwanda from 2012 to 2022. The main objective was to gain insights into the evolving patterns of malaria and to inform and tailor effective public health strategies. The study used yearly aggregated data of malaria cases from the Rwanda health management information system. We employed a multifaceted analytical approach, including descriptive statistics and spatio-temporal analysis across three demographic groups: children under the age of 5 years, and males and females above 5 years. Bayesian spatially explicit models and spatio scan statistics were utilised to examine geographic and temporal patterns of relative risks and to identify clusters of malaria transmission. We observed a significant increase in malaria cases from 2014 to 2018, peaking in 2016 for males and females aged above 5 years with counts of 98,645 and 116,627, respectively and in 2018 for under 5-year-old children with 84,440 cases with notable geographic disparities. Districts like Kamonyi (Southern Province), Ngoma, Kayonza and Bugesera (Eastern Province) exhibited high burdens, possibly influenced by factors such as climate, vector control practices, and cross-border dynamics. Bayesian spatially explicit modeling revealed elevated relative risks in numerous districts, underscoring the heterogeneity of malaria transmission in these districts, and thus contributing to an overall rising trend in malaria cases until 2018, followed by a subsequent decline. Our findings emphasize that the heterogeneity of malaria transmission is potentially driven by ecologic, socioeconomic, and behavioural factors. The study underscores the complexity of malaria transmission in Rwanda and calls for climate adaptive, gender-, age- and district-specific strategies in the national malaria control program. The emergence of both artemisinin and pyrethoids resistance and persistent high transmission in some districts necessitates continuous monitoring and innovative, data-driven approaches for effective and sustainable malaria control. \",\"PeriodicalId\":13587,\"journal\":{\"name\":\"Infectious Diseases of Poverty\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Diseases of Poverty\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40249-024-01237-w\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Diseases of Poverty","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40249-024-01237-w","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Spatio-temporal dynamics of malaria in Rwanda between 2012 and 2022: a demography-specific analysis
Despite global efforts to reduce and eventually interrupt malaria transmission, the disease remains a pressing public health problem, especially in sub-Saharan Africa. This study presents a detailed spatio-temporal analysis of malaria transmission in Rwanda from 2012 to 2022. The main objective was to gain insights into the evolving patterns of malaria and to inform and tailor effective public health strategies. The study used yearly aggregated data of malaria cases from the Rwanda health management information system. We employed a multifaceted analytical approach, including descriptive statistics and spatio-temporal analysis across three demographic groups: children under the age of 5 years, and males and females above 5 years. Bayesian spatially explicit models and spatio scan statistics were utilised to examine geographic and temporal patterns of relative risks and to identify clusters of malaria transmission. We observed a significant increase in malaria cases from 2014 to 2018, peaking in 2016 for males and females aged above 5 years with counts of 98,645 and 116,627, respectively and in 2018 for under 5-year-old children with 84,440 cases with notable geographic disparities. Districts like Kamonyi (Southern Province), Ngoma, Kayonza and Bugesera (Eastern Province) exhibited high burdens, possibly influenced by factors such as climate, vector control practices, and cross-border dynamics. Bayesian spatially explicit modeling revealed elevated relative risks in numerous districts, underscoring the heterogeneity of malaria transmission in these districts, and thus contributing to an overall rising trend in malaria cases until 2018, followed by a subsequent decline. Our findings emphasize that the heterogeneity of malaria transmission is potentially driven by ecologic, socioeconomic, and behavioural factors. The study underscores the complexity of malaria transmission in Rwanda and calls for climate adaptive, gender-, age- and district-specific strategies in the national malaria control program. The emergence of both artemisinin and pyrethoids resistance and persistent high transmission in some districts necessitates continuous monitoring and innovative, data-driven approaches for effective and sustainable malaria control.
期刊介绍:
Infectious Diseases of Poverty is a peer-reviewed, open access journal that focuses on essential public health questions related to infectious diseases of poverty. It covers a wide range of topics and methods, including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies, and their application.
The journal also explores the impact of transdisciplinary or multisectoral approaches on health systems, ecohealth, environmental management, and innovative technologies. It aims to provide a platform for the exchange of research and ideas that can contribute to the improvement of public health in resource-limited settings.
In summary, Infectious Diseases of Poverty aims to address the urgent challenges posed by infectious diseases in impoverished populations. By publishing high-quality research in various areas, the journal seeks to advance our understanding of these diseases and contribute to the development of effective strategies for prevention, diagnosis, and treatment.