{"title":"将哨点监测和气候因素结合起来，在塞内加尔不断变化的气候中加速消除疟疾","authors":"Ibrahima Mamby Keita , Mariama Diouf , Medoune Ndiop , Boly Diop , Khaly Gueye , Marianne Kouawo , Ousmane Ndiaye , Doudou Sene , Elhadji Mamadou Ndiaye , Marie Khemesse Ngom Ndiaye","doi":"10.1016/j.soh.2025.100112","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Senegal is located in a malaria-endemic zone. Malaria is a highly climate-sensitive vector-borne disease, yet its sentinel surveillance shows a weak integration of malaria morbidity data with climatic factors. Therefore, it is useful to analyse the correlation between these factors in Senegal from 2012 to 2019.</div></div><div><h3>Methods</h3><div>An analytical cross-sectional study of malaria incidence rate (MIR) with its climatic factors from 2012 to 2019 was carried out. This was followed by predictive modelling of MIR and its climatic factors from 2020 to 2023. A reconstituted database, incorporating data from National Malaria Control Program (initiated by Ministry of Health) and National Agency for Civil Aviation and Meteorology, enabled a multi-variate analysis through a vector auto regression approach using <em>Microsoft Excel 2010</em> and <em>R 3.6.1</em> software.</div></div><div><h3>Results</h3><div>MIR evolved in three phases: initially almost zero from January to May, then gradually increases with an accentuation in August–September, and finally gradually decreases from November to December. However, unlike Podor (0.11 ‰), MIR heterogeneity was seen in Kédougou (12.55 ‰) and Bakel (7.34 ‰). Apart from wind strength and mean temperature which moved in the opposite directions, all other climatic factors evolved in the same dynamics as MIR. MIR followed changes in rainfall and hygrometry with an average lag of (2.5 ± 1.0) months and (1.0 ± 0.5) months, respectively. The causal links between MIR and rainfall showed a decreasing trend in Dakar (<em>P</em> = 4.18 × 10<sup>−6</sup>), Ziguinchor (<em>P</em> = 7.95 × 10<sup>−4</sup>), Diourbel (<em>P</em> = 1.91 × 10<sup>−3</sup>), Kédougou (<em>P</em> = 4.03 × 10<sup>−3</sup>), and Bakel (<em>P</em> = 3.32 × 10<sup>−2</sup>). In Bakel, additional associations were observed between MIR and both minimum temperature (<em>P</em> = 5.87 × 10<sup>−3</sup>) and maximum temperature (<em>P</em> = 1.22 × 10<sup>−2</sup>) temperatures. Predictive modelling shows an overall downward trend for MIR from 2020 to 2023, with its climatic factors preceding MIR by an average of two months.</div></div><div><h3>Conclusion</h3><div>This study highlights the importance of synchronous, multi-sectoral, and integrated surveillance of malaria alongside climatic factors to more effectively meet pre-elimination requirements in Senegal.</div></div>","PeriodicalId":101146,"journal":{"name":"Science in One Health","volume":"4 ","pages":"Article 100112"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integration of sentinel surveillance and climate factors to accelerate malaria elimination in a changing climate of Senegal\",\"authors\":\"Ibrahima Mamby Keita , Mariama Diouf , Medoune Ndiop , Boly Diop , Khaly Gueye , Marianne Kouawo , Ousmane Ndiaye , Doudou Sene , Elhadji Mamadou Ndiaye , Marie Khemesse Ngom Ndiaye\",\"doi\":\"10.1016/j.soh.2025.100112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Senegal is located in a malaria-endemic zone. Malaria is a highly climate-sensitive vector-borne disease, yet its sentinel surveillance shows a weak integration of malaria morbidity data with climatic factors. Therefore, it is useful to analyse the correlation between these factors in Senegal from 2012 to 2019.</div></div><div><h3>Methods</h3><div>An analytical cross-sectional study of malaria incidence rate (MIR) with its climatic factors from 2012 to 2019 was carried out. This was followed by predictive modelling of MIR and its climatic factors from 2020 to 2023. A reconstituted database, incorporating data from National Malaria Control Program (initiated by Ministry of Health) and National Agency for Civil Aviation and Meteorology, enabled a multi-variate analysis through a vector auto regression approach using <em>Microsoft Excel 2010</em> and <em>R 3.6.1</em> software.</div></div><div><h3>Results</h3><div>MIR evolved in three phases: initially almost zero from January to May, then gradually increases with an accentuation in August–September, and finally gradually decreases from November to December. However, unlike Podor (0.11 ‰), MIR heterogeneity was seen in Kédougou (12.55 ‰) and Bakel (7.34 ‰). Apart from wind strength and mean temperature which moved in the opposite directions, all other climatic factors evolved in the same dynamics as MIR. MIR followed changes in rainfall and hygrometry with an average lag of (2.5 ± 1.0) months and (1.0 ± 0.5) months, respectively. The causal links between MIR and rainfall showed a decreasing trend in Dakar (<em>P</em> = 4.18 × 10<sup>−6</sup>), Ziguinchor (<em>P</em> = 7.95 × 10<sup>−4</sup>), Diourbel (<em>P</em> = 1.91 × 10<sup>−3</sup>), Kédougou (<em>P</em> = 4.03 × 10<sup>−3</sup>), and Bakel (<em>P</em> = 3.32 × 10<sup>−2</sup>). In Bakel, additional associations were observed between MIR and both minimum temperature (<em>P</em> = 5.87 × 10<sup>−3</sup>) and maximum temperature (<em>P</em> = 1.22 × 10<sup>−2</sup>) temperatures. Predictive modelling shows an overall downward trend for MIR from 2020 to 2023, with its climatic factors preceding MIR by an average of two months.</div></div><div><h3>Conclusion</h3><div>This study highlights the importance of synchronous, multi-sectoral, and integrated surveillance of malaria alongside climatic factors to more effectively meet pre-elimination requirements in Senegal.</div></div>\",\"PeriodicalId\":101146,\"journal\":{\"name\":\"Science in One Health\",\"volume\":\"4 \",\"pages\":\"Article 100112\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science in One Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949704325000095\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science in One Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949704325000095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of sentinel surveillance and climate factors to accelerate malaria elimination in a changing climate of Senegal
Background
Senegal is located in a malaria-endemic zone. Malaria is a highly climate-sensitive vector-borne disease, yet its sentinel surveillance shows a weak integration of malaria morbidity data with climatic factors. Therefore, it is useful to analyse the correlation between these factors in Senegal from 2012 to 2019.
Methods
An analytical cross-sectional study of malaria incidence rate (MIR) with its climatic factors from 2012 to 2019 was carried out. This was followed by predictive modelling of MIR and its climatic factors from 2020 to 2023. A reconstituted database, incorporating data from National Malaria Control Program (initiated by Ministry of Health) and National Agency for Civil Aviation and Meteorology, enabled a multi-variate analysis through a vector auto regression approach using Microsoft Excel 2010 and R 3.6.1 software.
Results
MIR evolved in three phases: initially almost zero from January to May, then gradually increases with an accentuation in August–September, and finally gradually decreases from November to December. However, unlike Podor (0.11 ‰), MIR heterogeneity was seen in Kédougou (12.55 ‰) and Bakel (7.34 ‰). Apart from wind strength and mean temperature which moved in the opposite directions, all other climatic factors evolved in the same dynamics as MIR. MIR followed changes in rainfall and hygrometry with an average lag of (2.5 ± 1.0) months and (1.0 ± 0.5) months, respectively. The causal links between MIR and rainfall showed a decreasing trend in Dakar (P = 4.18 × 10−6), Ziguinchor (P = 7.95 × 10−4), Diourbel (P = 1.91 × 10−3), Kédougou (P = 4.03 × 10−3), and Bakel (P = 3.32 × 10−2). In Bakel, additional associations were observed between MIR and both minimum temperature (P = 5.87 × 10−3) and maximum temperature (P = 1.22 × 10−2) temperatures. Predictive modelling shows an overall downward trend for MIR from 2020 to 2023, with its climatic factors preceding MIR by an average of two months.
Conclusion
This study highlights the importance of synchronous, multi-sectoral, and integrated surveillance of malaria alongside climatic factors to more effectively meet pre-elimination requirements in Senegal.
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