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Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province

Despite various efforts and policy implementation aimed at controlling and eliminating malaria, imported malaria remains a major factor posing challenges in places that have made progress in malaria elimination. The persistence of malaria in Limpopo Province has largely been attributed to imported c...

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Autores principales: Oyegoke, Olukunle O., Adewumi, Taiye S., Aderoju, Samuel A., Tsundzukani, Ntimbane, Mabunda, Eric, Adeleke, Matthew A., Maharaj, Rajendra, Okpeku, Moses
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10261840/
https://www.ncbi.nlm.nih.gov/pubmed/37310511
http://dx.doi.org/10.1007/s00436-023-07870-y
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author Oyegoke, Olukunle O.
Adewumi, Taiye S.
Aderoju, Samuel A.
Tsundzukani, Ntimbane
Mabunda, Eric
Adeleke, Matthew A.
Maharaj, Rajendra
Okpeku, Moses
author_facet Oyegoke, Olukunle O.
Adewumi, Taiye S.
Aderoju, Samuel A.
Tsundzukani, Ntimbane
Mabunda, Eric
Adeleke, Matthew A.
Maharaj, Rajendra
Okpeku, Moses
author_sort Oyegoke, Olukunle O.
collection PubMed
description Despite various efforts and policy implementation aimed at controlling and eliminating malaria, imported malaria remains a major factor posing challenges in places that have made progress in malaria elimination. The persistence of malaria in Limpopo Province has largely been attributed to imported cases, thus reducing the pace of achieving the malaria-free target by 2025. Data from the Limpopo Malaria Surveillance Database System (2010–2020) was analyzed, and a seasonal auto-regressive integrated moving average (SARIMA) model was developed to forecast malaria incidence based on the incidence data’s temporal autocorrelation. The study found that out of 57,288 people that were tested, 51,819 (90.5%) cases were local while 5469 (9.5%) cases were imported. Mozambique (44.9%), Zimbabwe (35.7%), and Ethiopia (8.5%) were the highest contributors of imported cases. The month of January recorded the highest incidence of cases while the least was in August. Analysis of the yearly figures showed an increasing trend and seasonal variation of recorded malaria cases. The SARIMA (3,1,1) X (3,1,0) [12] model used in predicting expected malaria case incidences for three consecutive years showed a decline in malaria incidences. The study demonstrated that imported malaria accounted for 9.5% of all cases. There is a need to re-focus on health education campaigns on malaria prevention methods and strengthening of indoor residual spray programs. Bodies collaborating toward malaria elimination in the Southern Africa region need to ensure a practical delivery of the objectives.
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spelling pubmed-102618402023-06-14 Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province Oyegoke, Olukunle O. Adewumi, Taiye S. Aderoju, Samuel A. Tsundzukani, Ntimbane Mabunda, Eric Adeleke, Matthew A. Maharaj, Rajendra Okpeku, Moses Parasitol Res Research Despite various efforts and policy implementation aimed at controlling and eliminating malaria, imported malaria remains a major factor posing challenges in places that have made progress in malaria elimination. The persistence of malaria in Limpopo Province has largely been attributed to imported cases, thus reducing the pace of achieving the malaria-free target by 2025. Data from the Limpopo Malaria Surveillance Database System (2010–2020) was analyzed, and a seasonal auto-regressive integrated moving average (SARIMA) model was developed to forecast malaria incidence based on the incidence data’s temporal autocorrelation. The study found that out of 57,288 people that were tested, 51,819 (90.5%) cases were local while 5469 (9.5%) cases were imported. Mozambique (44.9%), Zimbabwe (35.7%), and Ethiopia (8.5%) were the highest contributors of imported cases. The month of January recorded the highest incidence of cases while the least was in August. Analysis of the yearly figures showed an increasing trend and seasonal variation of recorded malaria cases. The SARIMA (3,1,1) X (3,1,0) [12] model used in predicting expected malaria case incidences for three consecutive years showed a decline in malaria incidences. The study demonstrated that imported malaria accounted for 9.5% of all cases. There is a need to re-focus on health education campaigns on malaria prevention methods and strengthening of indoor residual spray programs. Bodies collaborating toward malaria elimination in the Southern Africa region need to ensure a practical delivery of the objectives. Springer Berlin Heidelberg 2023-06-13 2023 /pmc/articles/PMC10261840/ /pubmed/37310511 http://dx.doi.org/10.1007/s00436-023-07870-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Oyegoke, Olukunle O.
Adewumi, Taiye S.
Aderoju, Samuel A.
Tsundzukani, Ntimbane
Mabunda, Eric
Adeleke, Matthew A.
Maharaj, Rajendra
Okpeku, Moses
Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title_full Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title_fullStr Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title_full_unstemmed Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title_short Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
title_sort towards malaria elimination: analysis of travel history and case forecasting using the sarima model in limpopo province
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10261840/
https://www.ncbi.nlm.nih.gov/pubmed/37310511
http://dx.doi.org/10.1007/s00436-023-07870-y
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