Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana

Improved prediction, prevention, and control of epidemics is a key technical element of the Roll Back Malaria partnership. We report a methodology for assessing the importance of climate as a driver of inter-annual variability in malaria in Botswana, and provide the evidence base for inclusion of climate information in a national malaria early warning system. The relationships of variability in rainfall and sea surface temperatures (SSTs) to malaria incidence are assessed at the national level after removing the impact of non-climatic trends and a major policy intervention. Variability in rainfall totals for the period December–February accounts for more than two-thirds of the inter-annual variability in standardized malaria incidence in Botswana (January–May). Both rainfall and annual malaria anomalies in December–February are significantly related to SSTs in the eastern Pacific, suggesting they may be predictable months in advance using seasonal climate forecasting methodologies

Sixth Report (Months 31-40)

This is the sixth, and final, issue of the progress reports for this project. It recognizes changes in the project amendment agreements: the first on January 1, 2009, which removed any reliance on the expected 50% joint project funding from the Gordon and Betty Moore Foundation (GBMF), and where, as a result, it was agreed that the geographical scale of the project would be scaled back from regional to national with a focus on Ethiopia; the second on March 30, 2010 following required shifts in effort to IRI and University of Reading staff given the repeated failures to secure both UK and US visas for some Ethiopian trainees that lead to greater emphasis on training in region. While the primary geographical focus of activity has centered on Ethiopia the final months of the project have placed additional emphasis on travel in order to ensure project completion, maximum visibility and dissemination of project outcomes., to maximize regional awareness/impact where available

Raised temperatures over the Kericho Tea Estates: revisiting the climate in the East African highlands malaria debate: Supplemental Information

Supplemental information to a study examining a time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, for the 30-year period 1 January 1979 to 31 December 2009

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

<p>Abstract</p> <p>Background</p> <p>Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region.</p> <p>Methods</p> <p>Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed.</p> <p>Results</p> <p>An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations.</p> <p>Conclusion</p> <p>This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.</p

Use of whole-genus genome sequence data to develop a multilocus sequence typing tool that accurately identifies Yersinia isolates to the species and subspecies levels

The genus Yersinia is a large and diverse bacterial genus consisting of human-pathogenic species, a fish-pathogenic species, and a large number of environmental species. Recently, the phylogenetic and population structure of the entire genus was elucidated through the genome sequence data of 241 strains encompassing every known species in the genus. Here we report the mining of this enormous data set to create a multilocus sequence typing-based scheme that can identify Yersinia strains to the species level to a level of resolution equal to that for whole-genome sequencing. Our assay is designed to be able to accurately subtype the important human-pathogenic species Yersinia enterocolitica to whole-genome resolution levels. We also report the validation of the scheme on 386 strains from reference laboratory collections across Europe. We propose that the scheme is an important molecular typing system to allow accurate and reproducible identification of Yersinia isolates to the species level, a process often inconsistent in nonspecialist laboratories. Additionally, our assay is the most phylogenetically informative typing scheme available for Y. enterocolitica

Impact of Climate Variability on Infectious Disease in West Africa

The importance of infectious disease as a determinant (as well as an outcome) of poverty has recently become a prominent argument for international and national investment in the control of infectious disease, as can be seen in the recently articulated United Nations (UN) Millennium Development Goals (MDGs). Climate variability and land use change have an enormous impact on health in West Africa, and may yet undermine the potential for achieving the MDGs, in certain economic-ecological zones. However, their underlying role in determining the burden of disease in the region on a yearly or decadal basis has never been systematically studied. In order to improve our understanding of the future impacts of climate change, it may be more effective to start by investigating the impact of inter-annual climate variability, and short-term shifts in climate (e.g., decadal), on disease transmission dynamics. This information may inform both current and future policy decisions with regard to prediction, prevention, and management of adverse climate-related health outcomes. This article reviews current knowledge of changes in the epidemiology of infectious diseases associated with climate variability in West Africa over the last 40 years. Selected examples are considered from bacterial (meningococcal meningitis), protozoan (malaria), and filarial (onchocerciasis and lymphatic filariasis) infections where spatial and temporal disease patterns have been directly influenced by seasonal, interannual, or decadal changes in climate

Environmental Risk and Meningitis Epidemics in Africa

Epidemics of meningococcal meningitis occur in areas with particular environmental characteristics. We present evidence that the relationship between the environment and the location of these epidemics is quantifiable and propose a model based on environmental variables to identify regions at risk for meningitis epidemics. These findings, which have substantial implications for directing surveillance activities and health policy, provide a basis for monitoring the impact of climate variability and environmental change on epidemic occurrence in Africa

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

Report on the forecast quality of seasonal predictions of malaria incidence in Botswana over the period 1982-2005

The ability of Stream 2 ENSEMBLES models to predict climate variability that is known to be related to annual variability in malaria over Botswana is tested. The ENSEMBLES multi-model is shown to have no clear difference in predictive skill compared to that for DEMETER models, but an ability to distinguish between high- and low-malaria years remains evident. More detailed analyses of the influence of observed climate variability on malaria incidence in Botswana were conducted. Evidence for district-scale climate signals is weak, as is an influence of seasonal temperature variability on malaria incidence, and so the ability of the ENSEMBLES models to predict these aspects was not considered. Real-time forecasts were communicated to the region during the duration of the project

Health and Climate–Needs

This paper describes the needs for climate risk management and information services for the health sector to serve research, educational and operational needs of ministries of health and their partners, those agencies that support broader public health service provision as well as respond to epidemics and emergencies. While climate information is considered highly relevant to helping guide improvements in public health provision, to date this information is largely underutilized. We explore some of the gaps in satisfying these needs, and we make recommendations to help fill the identified gaps