Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions
Abstract Background Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt trans...
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ftdoajarticles:oai:doaj.org/article:bbc57ae469124aa28873cc8d063847a3 2023-05-15T15:13:24+02:00 Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions Teklehaimanot Hailay D Schwartz Joel Teklehaimanot Awash Lipsitch Marc 2004-11-01T00:00:00Z https://doi.org/10.1186/1475-2875-3-44 https://doaj.org/article/bbc57ae469124aa28873cc8d063847a3 EN eng BMC http://www.malariajournal.com/content/3/1/44 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-3-44 1475-2875 https://doaj.org/article/bbc57ae469124aa28873cc8d063847a3 Malaria Journal, Vol 3, Iss 1, p 44 (2004) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2004 ftdoajarticles https://doi.org/10.1186/1475-2875-3-44 2022-12-31T07:17:05Z Abstract Background Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Methods Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4 th -degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. Results The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10–25% more cases at a given sensitivity in cold districts than in hot ones. Conclusions The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 3 1 44 |
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Directory of Open Access Journals: DOAJ Articles |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Teklehaimanot Hailay D Schwartz Joel Teklehaimanot Awash Lipsitch Marc Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Methods Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4 th -degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. Results The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10–25% more cases at a given sensitivity in cold districts than in hot ones. Conclusions The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems. |
format |
Article in Journal/Newspaper |
author |
Teklehaimanot Hailay D Schwartz Joel Teklehaimanot Awash Lipsitch Marc |
author_facet |
Teklehaimanot Hailay D Schwartz Joel Teklehaimanot Awash Lipsitch Marc |
author_sort |
Teklehaimanot Hailay D |
title |
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
title_short |
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
title_full |
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
title_fullStr |
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
title_full_unstemmed |
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
title_sort |
weather-based prediction of plasmodium falciparum malaria in epidemic-prone regions of ethiopia ii. weather-based prediction systems perform comparably to early detection systems in identifying times for interventions |
publisher |
BMC |
publishDate |
2004 |
url |
https://doi.org/10.1186/1475-2875-3-44 https://doaj.org/article/bbc57ae469124aa28873cc8d063847a3 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 3, Iss 1, p 44 (2004) |
op_relation |
http://www.malariajournal.com/content/3/1/44 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-3-44 1475-2875 https://doaj.org/article/bbc57ae469124aa28873cc8d063847a3 |
op_doi |
https://doi.org/10.1186/1475-2875-3-44 |
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Malaria Journal |
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3 |
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1 |
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44 |
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1766343957182152704 |