Malaria incidence in Nairobi, Kenya and dekadal trends in NDVI and climatic variables

Fastring, Danielle; Griffith, Jerry A.

doi:10.1080/10106040802491835

Cited by 8 publications

(3 citation statements)

References 22 publications

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“…Green vegetative cover, which is prevalent in the rainy season, is positively associated with malaria incidence. Several other studies have shown vegetative cover to be a significant predictor [53,54]. Temperature plays key role in the development of malaria vectors and their activities that directly or indirectly lead to the spread of malaria.…”

Section: Discussionmentioning

confidence: 97%

Childhood malaria case incidence in Malawi between 2004 and 2017: spatio-temporal modelling of climate and non-climate factors

Chirombo

Ceccato²,

Lowe

et al. 2020

Malar J

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Background: Malaria transmission is influenced by a complex interplay of factors including climate, socioeconomic , environmental factors and interventions. Malaria control efforts across Africa have shown a mixed impact. Climate driven factors may play an increasing role with climate change. Efforts to strengthen routine facility-based monthly malaria data collection across Africa create an increasingly valuable data source to interpret burden trends and monitor control programme progress. A better understanding of the association with other climatic and non-climatic drivers of malaria incidence over time and space may help guide and interpret the impact of interventions. Methods: Routine monthly paediatric outpatient clinical malaria case data were compiled from 27 districts in Malawi between 2004 and 2017, and analysed in combination with data on climatic, environmental, socioeconomic and interventional factors and district level population estimates. A spatio-temporal generalized linear mixed model was fitted using Bayesian inference, in order to quantify the strength of association of the various risk factors with districtlevel variation in clinical malaria rates in Malawi, and visualized using maps. Results: Between 2004 and 2017 reported childhood clinical malaria case rates showed a slight increase, from 50 to 53 cases per 1000 population, with considerable variation across the country between climatic zones. Climatic and environmental factors, including average monthly air temperature and rainfall anomalies, normalized difference vegetative index (NDVI) and RDT use for diagnosis showed a significant relationship with malaria incidence. Temperature in the current month and in each of the 3 months prior showed a significant relationship with the disease incidence unlike rainfall anomaly which was associated with malaria incidence at only three months prior. Estimated risk maps show relatively high risk along the lake and Shire valley regions of Malawi. Conclusion: The modelling approach can identify locations likely to have unusually high or low risk of malaria incidence across Malawi, and distinguishes between contributions to risk that can be explained by measured risk-factors and unexplained residual spatial variation. Also, spatial statistical methods applied to readily available routine data provides an alternative information source that can supplement survey data in policy development and implementation to direct surveillance and intervention efforts.

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Section: Discussionmentioning

confidence: 97%

Childhood malaria case incidence in Malawi between 2004 and 2017: spatio-temporal modelling of climate and non-climate factors

Chirombo

Ceccato²,

Lowe

et al. 2020

Malar J

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“…C‐Lock is an interesting application in this context, facilitating the evaluation of land management impacts on soil organic carbon sequestration as well as quantification and certification of carbon emission reduction credits (Zimmerman et al ., 2005). Spatial epidemiological applications have also been growing exponentially (Ostfeld et al ., 2005), ranging from the multiscale mapping of tsetse fly habitat suitability (Cecchi et al ., 2008) to the assessment of spatio‐temporal trends in malaria incidence (Fastring and Griffith, 2009).…”

Section: Potentials Of Existing Geospatial Approaches For Monitorimentioning

confidence: 99%

Integrative geospatial approaches for the comprehensive monitoring and assessment of land management sustainability: Rationale, Potentials, and Characteristics

et al. 2010

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Sustainable dryland management seeks to improve the conditions of people and ecosystems affected by degradation, but it is often unclear which land management strategies work, which ones do not and why. Monitoring and assessment (M&A) can support decision-making by providing this information. As implied by the 10-year Strategy of the United Nations Convention to Combat Desertification (UNCCD), however, M&A efforts have thus far been insufficient or inadequate. We argue that integrative geospatial approaches should be implemented to enhance dryland management decision-making. By assimilating and linking human and environmental data, qualitative and quantitative data, as well as field and remotely sensed data in a spatially explicit framework, such approaches facilitate assessments of both the complexities and place-specificities inherent to sustainability. In addition, they help represent different stakeholder perspectives, promote communication among scientists from diverse backgrounds as well as between scientific and local experts, facilitate inter-institutional knowledge sharing, and create synergy between the UNCCD and other Conventions. Due to these benefits as well as the rapid evolution and increasing availability and affordability of geospatial data and technologies in all countries, it is appropriate to begin capitalizing more fully on them now for the M&A of land management sustainability. In order for integrative geospatial approaches to become more central to M&A efforts, however, capacities and infrastructure must be improved and standards and protocols developed for the collection, analysis, and modeling of data, for the evaluation of outputs, and for the reporting of results.

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“…Nevertheless, most of these studies used low spatial resolution images or directly pre-calculated indices such as Normalized Difference Vegetation Index from MODIS images [28]. These vegetation indices have often been used as temporal indicators of seasonal fluctuations in disease [29,30] or predictors to build malaria early-warning systems [21]. Remote sensing has also been applied to study malaria ecology using high spatial resolution images to identify relationships with land cover or land use [24,31].…”

Section: Introductionmentioning

confidence: 99%

Changing Patterns of Malaria in Grande Comore after a Drastic Decline: Importance of Fine-Scale Spatial Analysis to Inform Future Control Actions

Attoumane¹,

Silai²,

Bacar³

et al. 2020

Remote Sensing

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Malaria has long been endemic in the Union of Comoros reaching an incidence of 15,045 cases for 100,000 inhabitants in 2010 (103,670 cases). Since then, strengthened control actions based on the distribution of Long-Lasting Insecticidal mosquito Nets and mass treatment have reduced malaria to a low level. However, it persists more specifically in Grande Comore, where 82% of cases were diagnosed between 2010 and 2016. This situation remains a challenge for health authorities seeking to eliminate malaria, by targeting transmission sites more precisely. In this context, this study aimed at mapping malaria at the finest scale, in order to describe its spatial distribution and identify possible environmental indicators. The National Malaria Control Program provided the 2016 data, the only year that could be mapped at the level of localities. This mapping revealed spatial autocorrelation between localities, especially in the east of the island with a major cluster around Itsinkoudi (using the Kulldorff’s spatial scan test). Secondary clusters showed that malaria remains present throughout the island in both rural and urban areas. We also analyzed satellite images (SPOT 5) with remote sensing techniques (Object-Based Image Analysis) to look for environmental indicators. Landscape analysis shows that malaria incidence is correlated across the island with low altitudes, and a larger proportion of grasslands or a fewer proportion of forested areas nearby (at less than 1km around villages). More locally in the east, malaria is linked to larger shrub areas. These relationships could be associated with the fact that lower altitude localities are more interconnected, such facilitating malaria transmission. In 2016, malaria persists in Grande Comore, showing new patterns with more cases in the eastern part of the island and the possibility of high incidences during the dry season. Precise mapping of epidemiological data and landscape analysis allow the identification of clusters and active transmission foci. They are important tools for health surveillance in order to optimize control actions on key transmission locations.

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Malaria incidence in Nairobi, Kenya and dekadal trends in NDVI and climatic variables

Cited by 8 publications

References 22 publications

Childhood malaria case incidence in Malawi between 2004 and 2017: spatio-temporal modelling of climate and non-climate factors

Childhood malaria case incidence in Malawi between 2004 and 2017: spatio-temporal modelling of climate and non-climate factors

Integrative geospatial approaches for the comprehensive monitoring and assessment of land management sustainability: Rationale, Potentials, and Characteristics

Changing Patterns of Malaria in Grande Comore after a Drastic Decline: Importance of Fine-Scale Spatial Analysis to Inform Future Control Actions

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