Climate prediction of El Niño malaria epidemics in north-west Tanzania
Abstract Background Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was...
Published in: | Malaria Journal |
---|---|
Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
BMC
2007
|
Subjects: | |
Online Access: | https://doi.org/10.1186/1475-2875-6-162 https://doaj.org/article/195a3eb7bd014eed86ad2c1dc47f642f |
id |
ftdoajarticles:oai:doaj.org/article:195a3eb7bd014eed86ad2c1dc47f642f |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:195a3eb7bd014eed86ad2c1dc47f642f 2023-05-15T15:15:34+02:00 Climate prediction of El Niño malaria epidemics in north-west Tanzania Morse Andrew P Wort Ulrika Jones Anne E Hastings Ian M Gagnon Alexandre S 2007-12-01T00:00:00Z https://doi.org/10.1186/1475-2875-6-162 https://doaj.org/article/195a3eb7bd014eed86ad2c1dc47f642f EN eng BMC http://www.malariajournal.com/content/6/1/162 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-6-162 1475-2875 https://doaj.org/article/195a3eb7bd014eed86ad2c1dc47f642f Malaria Journal, Vol 6, Iss 1, p 162 (2007) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2007 ftdoajarticles https://doi.org/10.1186/1475-2875-6-162 2022-12-31T04:21:34Z Abstract Background Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was subject to widespread malaria epidemics in 1997 and 1998. This study examined the relationship between climate and malaria incidence in Kagera with the aim of determining whether seasonal forecasts may assist in predicting malaria epidemics. Methods A regression analysis was performed on retrospective malaria and climatic data during each of the two annual malaria seasons to determine the climatic factors influencing malaria incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic anomalies associated with malaria epidemics was then assessed for each malaria season. Results It was found that malaria incidence is positively correlated with rainfall during the first season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria incidence was associated with increased rainfall, but also with high maximum temperature during the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical models was tested by excluding the two epidemic years from the regression analysis. DEMETER would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic. Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone. The 1997 epidemic could have been predicted from observed temperatures in the preceding season, but the consideration of the rainfall forecasts would have improved the temperature-only forecasts over the remaining years. Conclusion These results demonstrate the potential of a seasonal forecasting system in the development of a malaria early warning system in Kagera region. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 6 1 162 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Morse Andrew P Wort Ulrika Jones Anne E Hastings Ian M Gagnon Alexandre S Climate prediction of El Niño malaria epidemics in north-west Tanzania |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Malaria is a significant public health problem in Tanzania. Approximately 16 million malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that was subject to widespread malaria epidemics in 1997 and 1998. This study examined the relationship between climate and malaria incidence in Kagera with the aim of determining whether seasonal forecasts may assist in predicting malaria epidemics. Methods A regression analysis was performed on retrospective malaria and climatic data during each of the two annual malaria seasons to determine the climatic factors influencing malaria incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic anomalies associated with malaria epidemics was then assessed for each malaria season. Results It was found that malaria incidence is positively correlated with rainfall during the first season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria incidence was associated with increased rainfall, but also with high maximum temperature during the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical models was tested by excluding the two epidemic years from the regression analysis. DEMETER would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic. Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone. The 1997 epidemic could have been predicted from observed temperatures in the preceding season, but the consideration of the rainfall forecasts would have improved the temperature-only forecasts over the remaining years. Conclusion These results demonstrate the potential of a seasonal forecasting system in the development of a malaria early warning system in Kagera region. |
format |
Article in Journal/Newspaper |
author |
Morse Andrew P Wort Ulrika Jones Anne E Hastings Ian M Gagnon Alexandre S |
author_facet |
Morse Andrew P Wort Ulrika Jones Anne E Hastings Ian M Gagnon Alexandre S |
author_sort |
Morse Andrew P |
title |
Climate prediction of El Niño malaria epidemics in north-west Tanzania |
title_short |
Climate prediction of El Niño malaria epidemics in north-west Tanzania |
title_full |
Climate prediction of El Niño malaria epidemics in north-west Tanzania |
title_fullStr |
Climate prediction of El Niño malaria epidemics in north-west Tanzania |
title_full_unstemmed |
Climate prediction of El Niño malaria epidemics in north-west Tanzania |
title_sort |
climate prediction of el niño malaria epidemics in north-west tanzania |
publisher |
BMC |
publishDate |
2007 |
url |
https://doi.org/10.1186/1475-2875-6-162 https://doaj.org/article/195a3eb7bd014eed86ad2c1dc47f642f |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 6, Iss 1, p 162 (2007) |
op_relation |
http://www.malariajournal.com/content/6/1/162 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-6-162 1475-2875 https://doaj.org/article/195a3eb7bd014eed86ad2c1dc47f642f |
op_doi |
https://doi.org/10.1186/1475-2875-6-162 |
container_title |
Malaria Journal |
container_volume |
6 |
container_issue |
1 |
container_start_page |
162 |
_version_ |
1766345939939753984 |