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<p>Malaria continues to pose a major threat despite numerous efforts aimed at reducing its incidence and ultimately eliminating the disease. The majority of malaria cases occur in Africa. According to the World Health Organization, one of the key reasons for the continued presence of malaria is financial constraints. It is, therefore, crucial to make the most efficient use of the limited resources available. Data generated from control efforts must be thoroughly analysed to inform effective decision-making. In this context, predictive approaches can play a vital role. Predictive modelling, in particular, has proven to be a powerful and cost-effective tool for guiding policymakers and improving the impact of interventions. It was within this framework that the workshop was held with the aim of strengthening the capacity building of stakeholders involved in malaria control in Benin in data analysis and the application of modelling to support operational decision-making. This report presents a summary of the key presentations, trainings, and activities conducted during the workshop, which took place on January 17–18, 2024, at Hôtel du Lac in Cotonou, Benin.</p>

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Introducing researchers involved in vector control to modelling for operational decision-making in Benin: report of the workshop, January 17–18, 2024

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  • 出版模式：

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  • 发表日期：

    2025年9月30日

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  • Alphonse Keller Konkon,
  • David Mahouton Zoungbédji,
  • Geoffroy Yahoue,
  • Arthur Sovi,
  • Albert Sourou Salako,
  • Isidore Hoyochi,
  • Merveille Koissi Savi,
  • Jonas Doumate,
  • Filémon Tonkponnon,
  • Razacki Ossè,
  • Rock Aikpon,
  • Casimir Kpanou,
  • Come Koukpo,
  • Arsène Fasinou,
  • Juvénal Ahouandjinou,
  • Linda Towakinou,
  • Steve Zinsou Hougbe,
  • Gérard Totongnon,
  • Boulais Yovogan,
  • Constantin Adoha,
  • Hermann Sagbohan,
  • Esdras Odjo,
  • Olivier Oussou,
  • Roseric Azondekon,
  • Martin Codjo Akogbéto,
  • Germain Gil Padonou

摘要

Malaria continues to pose a major threat despite numerous efforts aimed at reducing its incidence and ultimately eliminating the disease. The majority of malaria cases occur in Africa. According to the World Health Organization, one of the key reasons for the continued presence of malaria is financial constraints. It is, therefore, crucial to make the most efficient use of the limited resources available. Data generated from control efforts must be thoroughly analysed to inform effective decision-making. In this context, predictive approaches can play a vital role. Predictive modelling, in particular, has proven to be a powerful and cost-effective tool for guiding policymakers and improving the impact of interventions. It was within this framework that the workshop was held with the aim of strengthening the capacity building of stakeholders involved in malaria control in Benin in data analysis and the application of modelling to support operational decision-making. This report presents a summary of the key presentations, trainings, and activities conducted during the workshop, which took place on January 17–18, 2024, at Hôtel du Lac in Cotonou, Benin.