A dynamic, climate-driven model of Rift Valley fever

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P.

doi:10.4081/gh.2016.394

Cited by 20 publications

(21 citation statements)

References 60 publications

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“…Mathematical models of RVF typically focus on identifying factors that can be used to forecast or mitigate the next epidemic (e.g. Leedale et al, 2016;Mpeshe et al, 2011;Pedro et al, 2016). The repeated observation of the importance of precipitation and water availability at specific locations, combined with the differentiated natural history of the main vectors, means that attempting to predict longer-term transmission of RVF under projected climate change scenarios is inherently more challenging than for a disease that has only one vector.…”

Section: Rift Valley Fever (Rvf)mentioning

confidence: 99%

“…Additional to the bioclimatic variable of importance are other factors related to the overall vulnerability of a population. This aspect of disease has been explored by Taylor et al (2016) who constructed an overall risk map of future RVF outbreaks in East Africa that comprised the deterministic RVF model of Leedale et al (2016), downscaled RCP projections and several expert-weighted indicators of social vulnerability.…”

Section: Rift Valley Fever (Rvf)mentioning

confidence: 99%

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Climate Change and the Neglected Tropical Diseases

Booth

2018

Advances in Parasitology

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Climate change is expected to impact across every domain of society, including health. The majority of the world's population is susceptible to pathological, infectious disease whose life cycles are sensitive to environmental factors across different physical phases including air, water and soil. Nearly all so-called neglected tropical diseases (NTDs) fall into this category, meaning that future geographic patterns of transmission of dozens of infections are likely to be affected by climate change over the short (seasonal), medium (annual) and long (decadal) term. This review offers an introduction into the terms and processes deployed in modelling climate change and reviews the state of the art in terms of research into how climate change may affect future transmission of NTDs. The 34 infections included in this chapter are drawn from the WHO NTD list and the WHO blueprint list of priority diseases. For the majority of infections, some evidence is available of which environmental factors contribute to the population biology of parasites, vectors and zoonotic hosts. There is a general paucity of published research on the potential effects of decadal climate change, with some exceptions, mainly in vector-borne diseases.

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Section: Rift Valley Fever (Rvf)mentioning

confidence: 99%

Section: Rift Valley Fever (Rvf)mentioning

confidence: 99%

Climate Change and the Neglected Tropical Diseases

Booth

2018

Advances in Parasitology

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“…The model was parameterized based on information gained from eastern Africa, mainly from existing published sources but also on the basis of results of surveys carried out in Ijara District in Kenya as part of HEALTHY FUTURES (Bett et al, 2013). As Leedale et al (2016) stress, eastern Africa proved an ideal site for LRVF model development, because of the relatively long history of the disease and the wide range of environmental conditions represented in the region.…”

Section: Determining Riskmentioning

confidence: 99%

“…is considered here. This is because a large spike in EIR associated with Culex spp., as the amplifying vector, likely represents an epizootic event (Leedale et al, 2016). Three time periods were simulated using LRVF and climate change data: 1980-2010 (equates to the present) and 2011-2050 (mid-century) and 2051-2099 (end of century).…”

Section: Determining Riskmentioning

confidence: 99%

“…This paper provides a preliminary assessment of the future risk of RVF within eastern Africa (more specifically, the EAC region). Leedale et al (2016) describe development of a dynamic, process-based, climate-driven model for RVF (the Liverpool RVF, or LRVF, model) through HEALTHY FUTURES. The LRVF model, described in more detail below, is used in the current paper: output from the model is in the form of climatically driven, spatially and temporally varying estimates of the entomological inoculation rate (EIR), a commonly used measure of the intensity of transmission of a VBD, for a livestock host.…”

Section: Introductionmentioning

confidence: 99%

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Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

et al. 2016

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Outbreaks of Rift Valley fever (RVF), a relatively recently emerged zoonosis endemic to large parts of sub-Saharan Africa that has the potential to spread beyond the continent, have profound health and socio-economic impacts, particularly in communities where resilience is already low. Here output from a new, dynamic disease model [the Liverpool RVF (LRVF) model], driven by downscaled, bias-corrected climate change data from an ensemble of global circulation models from the Inter-Sectoral Impact Model Intercomparison Project run according to two radiative forcing scenarios [representative concentration pathway (RCP)4.5 and RCP8.5], is combined with results of a spatial assessment of social vulnerability to the disease in eastern Africa. The combined approach allowed for analyses of spatial and temporal variations in the risk of RVF to the end of the current century. Results for both scenarios highlight the high-risk of future RVF outbreaks, including in parts of eastern Africa to date unaffected by the disease. The results also highlight the risk of spread from/to countries adjacent to the study area, and possibly farther afield, and the value of considering the geography of future projections of disease risk. Based on the results, there is a clear need to remain vigilant and to invest not only in surveillance and early warning systems, but also in addressing the socio-economic factors that underpin social vulnerability in order to mitigate, effectively, future impacts.

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Modelling the potential distribution of arbovirus vector Aedes aegypti under current and future climate scenarios in Taiwan, China

Liu

Jiao

et al. 2019

Pest Management Science

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BACKGROUND: Aedes aegypti is one of the most important mosquito species and is a common disease-transmitting pest in tropical areas. Various infectious arbovirus diseases can be transmitted by Ae. aegypti. With ongoing global climate change, we are facing an increasing public health threat from the rapid spread of disease vectors into wider geographical areas. To better understand the current ecological niche range and possible future expansion of Ae. aegypti, an ecological niche modelling approach was adopted to predict its current and future potential habitat in Taiwan, China. 30 arcsec (approx. 1 × 1 km) were made by our model. Ae. aegypti was predicted to expand its habitat in varying degrees out of its current niche range under different climate scenarios for the future 21st century. Winter temperature and dry season precipitation were considered as important predictors among climate variables. Croplands, pasture, forested lands and urban lands were important land-use variables. RESULTS: Based on observed occurrence records and environmental layers reflecting climate and land-use conditions, predictions with a high resolution of CONCLUSION:Ae. aegypti is expected to establish new habitats out of its current niche range under the trend of global climate change. The extent of habitat expansion varies under different climate scenarios. Appropriate measures should be taken to prevent its expansion to a broader scale. Our study has important strategic implications for mosquito surveillance and the prevention and control of mosquito-borne diseases.

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A dynamic, climate-driven model of Rift Valley fever

Cited by 20 publications

References 60 publications

Climate Change and the Neglected Tropical Diseases

Climate Change and the Neglected Tropical Diseases

Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

Modelling the potential distribution of arbovirus vector Aedes aegypti under current and future climate scenarios in Taiwan, China

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