Near-term climate change impacts on sub-national malaria transmission

Jailos Lubinda, Ubydul Haque, Yaxin Bi, Hamainza Busiku, AJ Moore

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9 Citations (Scopus)
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The role of climate change on global malaria is often highlighted in World Health Organisation reports. We modelled a Zambian socio-environmental dataset from 2000 to 2016, against malaria trends and investigated the relationship of near-term environmental change with malaria incidence using Bayesian spatio-temporal, and negative binomial mixed regression models. We introduced the diurnal temperature range (DTR) as an alternative environmental measure to the widely used mean temperature. We found substantial sub-national near-term variations and significant associations with malaria incidence-trends. Significant spatio-temporal shifts in DTR/environmental predictors influenced malaria incidence-rates, even in areas with declining trends. We highlight the impact of seasonally sensitive DTR, especially in the first two quarters of the year and demonstrate how substantial investment in intervention programmes is negatively impacted by near-term climate change, most notably since 2010. We argue for targeted seasonally-sensitive malaria chemoprevention programmes.
Original languageEnglish
Article number751
Pages (from-to)1-13
Number of pages13
JournalScientific Reports
Issue number1
Publication statusPublished (in print/issue) - 12 Jan 2021

Bibliographical note

Funding Information:
The United Kingdom Commonwealth Scholarship Commission funded Jailos Lubinda as part of his PhD studies. Ubydul Haque was funded in part by the Emerging Pathogens Institute at the University of Florida and the College of Liberal Arts and Sciences, as part of the University of Florida Pre-eminence Initiative. All funding sources had NO involvement in the decision to write or publish this work. The opinions expressed in the manuscript are those of the authors. They do not necessarily reflect the opinions of any funders of co-authors. As the corresponding author, JL had full access to all data in the study and has final responsibility for the decision to submit for publication.

Publisher Copyright:
© 2021, The Author(s).

Copyright 2021 Elsevier B.V., All rights reserved.


  • climate change
  • Malaria
  • spatiotemporal modelling


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