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      Climate drivers of vector-borne diseases in Africa and their relevance to control programmes

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          Abstract

          Background

          Climate-based disease forecasting has been proposed as a potential tool in climate change adaptation for the health sector. Here we explore the relevance of climate data, drivers and predictions for vector-borne disease control efforts in Africa.

          Methods

          Using data from a number of sources we explore rainfall and temperature across the African continent, from seasonality to variability at annual, multi-decadal and timescales consistent with climate change. We give particular attention to three regions defined as WHO-TDR study zones in Western, Eastern and Southern Africa. Our analyses include 1) time scale decomposition to establish the relative importance of year-to-year, decadal and long term trends in rainfall and temperature; 2) the impact of the El Niño Southern Oscillation (ENSO) on rainfall and temperature at the Pan African scale; 3) the impact of ENSO on the climate of Tanzania using high resolution climate products and 4) the potential predictability of the climate in different regions and seasons using Generalized Relative Operating Characteristics. We use these analyses to review the relevance of climate forecasts for applications in vector borne disease control across the continent.

          Results

          Timescale decomposition revealed long term warming in all three regions of Africa – at the level of 0.1–0.3 °C per decade. Decadal variations in rainfall were apparent in all regions and particularly pronounced in the Sahel and during the East African long rains (March–May). Year-to-year variability in both rainfall and temperature, in part associated with ENSO, were the dominant signal for climate variations on any timescale. Observed climate data and seasonal climate forecasts were identified as the most relevant sources of climate information for use in early warning systems for vector-borne diseases but the latter varied in skill by region and season.

          Conclusions

          Adaptation to the vector-borne disease risks of climate variability and change is a priority for government and civil society in African countries. Understanding rainfall and temperature variations and trends at multiple timescales and their potential predictability is a necessary first step in the incorporation of relevant climate information into vector-borne disease control decision-making.

          Electronic supplementary material

          The online version of this article (10.1186/s40249-018-0460-1) contains supplementary material, which is available to authorized users.

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          Most cited references36

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          Malaria early warnings based on seasonal climate forecasts from multi-model ensembles.

          The control of epidemic malaria is a priority for the international health community and specific targets for the early detection and effective control of epidemics have been agreed. Interannual climate variability is an important determinant of epidemics in parts of Africa where climate drives both mosquito vector dynamics and parasite development rates. Hence, skilful seasonal climate forecasts may provide early warning of changes of risk in epidemic-prone regions. Here we discuss the development of a system to forecast probabilities of anomalously high and low malaria incidence with dynamically based, seasonal-timescale, multi-model ensemble predictions of climate, using leading global coupled ocean-atmosphere climate models developed in Europe. This forecast system is successfully applied to the prediction of malaria risk in Botswana, where links between malaria and climate variability are well established, adding up to four months lead time over malaria warnings issued with observed precipitation and having a comparably high level of probabilistic prediction skill. In years in which the forecast probability distribution is different from that of climatology, malaria decision-makers can use this information for improved resource allocation.
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            Paramount Impact of the Indian Ocean Dipole on the East African Short Rains: A CGCM Study

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              • Article: not found

              Climate and climatic variability of rainfall over eastern Africa

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                Author and article information

                Contributors
                mthomson@iri.columbia.edu
                agmunoz@iri.columbia.edu
                remic@iri.columbia.edu
                jshumake-guillemot@wmo.int
                Journal
                Infect Dis Poverty
                Infect Dis Poverty
                Infectious Diseases of Poverty
                BioMed Central (London )
                2095-5162
                2049-9957
                10 August 2018
                10 August 2018
                2018
                : 7
                : 81
                Affiliations
                [1 ]ISNI 0000000419368729, GRID grid.21729.3f, International Research Institute for Climate and Society (IRI), Earth Institute, , Columbia University, ; New York, USA
                [2 ]ISNI 0000000419368729, GRID grid.21729.3f, Mailman School of Public Health Department of Environmental Health Sciences, , Columbia University, ; New York, USA
                [3 ]IRI-World Health Organization (WHO) Collaborating Centre (US 430) on Early Warning Systems for Malaria and other Climate Sensitive Diseases, New York, USA
                [4 ]ISNI 0000 0001 2097 5006, GRID grid.16750.35, Atmospheric and Oceanic Sciences, , Princeton University, ; Princeton, NJ USA
                [5 ]ISNI 0000 0000 9791 0836, GRID grid.426193.b, World Health Organization- World Meteorological Organization Joint Climate and Health Office, WMO, ; Geneva, Switzerland
                [6 ]ISNI 0000 0000 9175 9928, GRID grid.473157.3, International Research Institute for Climate and Society, LDEO, ; Palisades, New York, 10964 USA
                Author information
                http://orcid.org/0000-0002-3564-6421
                Article
                460
                10.1186/s40249-018-0460-1
                6085673
                30092816
                2ed3fb3e-c6ad-4b75-ac57-84d6fb6f881d
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 November 2017
                : 11 July 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004423, World Health Organization;
                Award ID: PO 21353027
                Award ID: 201487225
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                vector-borne diseases,climate variability,climate change,el niño southern oscillation,climate services,adaptation,africa

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