Mechanistic modeling of the impact of climate variability and change on malaria transmission in Africa

2016 ◽  
Author(s):  
Elfatih Eltahir
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Mechanistic Modeling ◽  
Climate Variability And Change ◽  
The Impact

scholarly journals Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

2018 ◽  
Vol 10 (1) ◽  
pp. 88-100 ◽  
Author(s):  
Gbenga J. Abiodun ◽  
Peter J. Witbooi ◽  
Kazeem O. Okosun ◽  
Rajendra Maharaj
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Principal Component ◽  
Wavelet Coherence ◽  
Human Malaria ◽  
Kwazulu Natal ◽  
The Impact ◽  
Wavelet Coherence Analysis ◽  
Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

scholarly journals Global sensitivity-based modelling approach to identify suitable Eucalyptus traits for adaptation to climate variability and change

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Elvis Felipe Elli ◽  
Neil Huth ◽  
Paulo Cesar Sentelhas ◽  
Rafaela Lorenzato Carneiro ◽  
Clayton Alcarde Alvares
Keyword(s):  
Sensitivity Analysis ◽  
Climate Variability ◽  
Global Sensitivity Analysis ◽  
Greenhouse Gas Emission ◽  
Growth And Yield ◽  
Superior Performance ◽  
Climate Variability And Change ◽  
Genetic Traits ◽  
Global Sensitivity ◽  
The Impact

Abstract Eucalyptus-breeding efforts have been made to identify clones of superior performance for growth and yield and how they will interact with global climate changes. This study performs a global sensitivity analysis for assessing the impact of genetic traits on Eucalyptus yield across contrasting environments in Brazil under present and future climate scenarios. The APSIM Next Generation Eucalyptus model was used to perform the simulations of stemwood biomass (t ha−1) for 7-year rotations across 23 locations in Brazil. Projections for the period from 2020 to 2049 using three global circulation models under intermediate (RCP4.5) and high (RCP8.5) greenhouse gas emission scenarios were performed. The Morris sensitivity method was used to perform a global sensitivity analysis to identify the influence of plant traits on stemwood biomass. Traits for radiation use efficiency, leaf partitioning, canopy light capture and fine root partitioning were the most important, impacting the Eucalyptus yield substantially in all environments under the present climate. Some of the traits targeted now by breeders for current climate will remain important under future climates. However, breeding should place a greater emphasis on photosynthetic temperature response for Eucalyptus in some regions. Global sensitivity analysis was found to be a powerful tool for identifying suitable Eucalyptus traits for adaptation to climate variability and change. This approach can improve breeding strategies by better understanding the gene × environment interactions for forest productivity.

scholarly journals Introduction: food crops in a changing climate

2005 ◽  
Vol 360 (1463) ◽  
pp. 1983-1989 ◽  
Author(s):  
Julia M Slingo ◽  
Andrew J Challinor ◽  
Brian J Hoskins ◽  
Timothy R Wheeler
Keyword(s):  
Climate Variability ◽  
Crop Production ◽  
Crop Yields ◽  
Research Priorities ◽  
Future Research ◽  
Food Crops ◽  
Climate Variability And Change ◽  
Regional Impacts ◽  
Complex Models ◽  
The Impact

Changes in both the mean and the variability of climate, whether naturally forced, or due to human activities, pose a threat to crop production globally. This paper summarizes discussions of this issue at a meeting of the Royal Society in April 2005. Recent advances in understanding the sensitivity of crops to weather, climate and the levels of particular gases in the atmosphere indicate that the impact of these factors on crop yields and quality may be more severe than previously thought. There is increasing information on the importance to crop yields of extremes of temperature and rainfall at key stages of crop development. Agriculture will itself impact on the climate system and a greater understanding of these feedbacks is needed. Complex models are required to perform simulations of climate variability and change, together with predictions of how crops will respond to different climate variables. Variability of climate, such as that associated with El Niño events, has large impacts on crop production. If skilful predictions of the probability of such events occurring can be made a season or more in advance, then agricultural and other societal responses can be made. The development of strategies to adapt to variations in the current climate may also build resilience to changes in future climate. Africa will be the part of the world that is most vulnerable to climate variability and change, but knowledge of how to use climate information and the regional impacts of climate variability and change in Africa is rudimentary. In order to develop appropriate adaptation strategies globally, predictions about changes in the quantity and quality of food crops need to be considered in the context of the entire food chain from production to distribution, access and utilization. Recommendations for future research priorities are given.

scholarly journals Climate Variability and Change Affect Crops Yield under Rainfed Conditions: A Case Study in Gedaref State, Sudan

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1680
Author(s):  
Maysoon A. A. Osman ◽  
Joshua Orungo Onono ◽  
Lydia A. Olaka ◽  
Muna M. Elhag ◽  
Elfatih M. Abdel-Rahman
Keyword(s):  
Linear Regression ◽  
Climate Variability ◽  
Crop Yield ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Simple Linear Regression ◽  
Climate Variability And Change ◽  
Crops Yield ◽  
The Impact

It is projected that, on average, annual temperature will increase between 2 °C to 6 °C under high emission scenarios by the end of the 21st century, with serious consequences in food and nutrition security, especially within semi-arid regions of sub-Saharan Africa. This study aimed to investigate the impact of historical long-term climate (temperature and rainfall) variables on the yield of five major crops viz., sorghum, sesame, cotton, sunflower, and millet in Gedaref state, Sudan over the last 35 years. Mann–Kendall trend analysis was used to determine the existing positive or negative trends in temperature and rainfall, while simple linear regression was used to assess trends in crop yield over time. The first difference approach was used to remove the effect of non-climatic factors on crop yield. On the other hand, the standardized anomaly index was calculated to assess the variability in both rainfall and temperature over the study period (i.e., 35 years). Correlation and multiple linear regression (MLR) analyses were employed to determine the relationships between climatic variables and crops yield. Similarly, a simple linear regression was used to determine the relationship between the length of the rainy season and crop yield. The results showed that the annual maximum temperature (Tmax) increased by 0.03 °C per year between the years 1984 and 2018, while the minimum temperature (Tmin) increased by 0.05 °C per year, leading to a narrow range in diurnal temperature (DTR). In contrast, annual rainfall fluctuated with no evidence of a significant (p > 0.05) increasing or decreasing trend. The yields for all selected crops were negatively correlated with Tmin, Tmax (r ranged between −0.09 and −0.76), and DTR (r ranged between −0.10 and −0.70). However, the annual rainfall had a strong positive correlation with yield of sorghum (r = 0.64), sesame (r = 0.58), and sunflower (r = 0.75). Furthermore, the results showed that a longer rainy season had significant (p < 0.05) direct relationships with the yield of most crops, while Tmax, Tmin, DTR, and amount of rainfall explained more than 50% of the variability in the yield of sorghum (R2 = 0.70), sunflower (R2 = 0.61), and millet (R2 = 0.54). Our results call for increased awareness among different stakeholders and policymakers on the impact of climate change on crop yield, and the need to upscale adaptation measures to mitigate the negative impacts of climate variability and change.

scholarly journals Strategi Peningkatan Produktivitas Kopi serta Adaptasi terhadap Variabilitas dan Perubahan Iklim melalui Kalender Budidaya

2020 ◽  
Vol 14 (2) ◽  
pp. 65
Author(s):  
Yeli Sarvina ◽  
Tania June ◽  
Elza Surmaini ◽  
Rita Nurmalina ◽  
Sutjahjo Surjono Hadi
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Adaptation Strategy ◽  
Climate Forecast ◽  
Climate Variability And Change ◽  
Coffee Production ◽  
Climate Change And Variability ◽  
Potential Strategy ◽  
Coffee Cultivation ◽  
The Impact

<p><strong>Abstrak</strong>. Rendahnya produktivitas kopi merupakan salah satu permasalahan utama dalam sistem produksi kopi Indonesia. Hal ini diantaranya disebabkan tidak adanya perawatan kopi yang optimal dengan memperhatikan fase fenologi kopi, serta dampak variabilitas dan perubahan iklim. Berbagai teknologi adaptasi kopi sudah banyak dihasilkan namun langkah adaptasi dengan memanfaatkan prakiraan iklim dalam bentuk penyesuian kegiatan budidaya dengan fase fenologi atau disebut sebagai kalender budidaya belum dikembangkan. Tulisan ini memaparkan tentang dampak variabilitas dan perubahan iklim pada tanaman kopi, teknologi adaptasi kopi yang sudah tersedia, perlunya pengembangan kalender budidaya kopi sebagai bentuk strategi adaptasi dan peningkatan produktivitas serta potensi dan tantangan pengembangan kalender budidaya kopi di Indonesia. Hasil review ini menunjukkan kalender budidaya kopi berpotensi dikembangkan sebagai strategi peningkatan produktivitas serta adaptasi terhadap variabilitas dan perubahan iklim.</p><p> </p><p><strong>Abstract</strong>. Low productivity is one of the main challenges in Indonesia's coffee production system .It is low due to cultivation management; most of the coffee farmer does not manage their plantation base on the coffee phenology phase.  Moreover climate variability and change also have important effect on coffee productivity. Various technologies on adaptation and measurement to climate change and variability have been identified. Unfortunately, the technology which use climate forecast through adjusting cultivation activity and coffee phenology called as cultivation calendar do not exist yet. This paper provides an overview on the impact of climate variability and change to coffee production, the existing adaptation strategy, and the importance of cultivation calendar as a strategy for adapting and increasing productivity, and the potential and challenges to develop cultivation calendar in Indonesia. This review reveals that coffee cultivation calendar is a potential strategy for increaseing productivity and adapting climate change and variability.</p>

scholarly journals ASSESSING THE IMPACT OF CLIMATE VARIABILITY AND CHANGE ON WATER RESOURCES IN BAMENDA METROPOLIS, NORTH WEST REGION OF CAMEROON

2021 ◽  
Vol 9 (10) ◽  
pp. 1-17
Author(s):  
Gordin Bah Ndah Anyang ◽  
Ngwa Martin Ngwabie ◽  
Samuel Ndonwi Ayonghe
Keyword(s):  
Water Resources ◽  
Climate Variability ◽  
Management Practice ◽  
Climatic Variability ◽  
Water Shortage ◽  
Climatic Data ◽  
Climate Variability And Change ◽  
North West ◽  
Standardised Precipitation Index ◽  
The Impact

Water resources within Bamenda continue to face climate related stress. This paper sought to assess the impact of climate variability and change on water resources in Bamenda metropolis. Questionnaires, field study and historic climatic data were used to evaluate effects of climatic variability and changes on water resources. Two Representative Concentration Pathway (RCP 2.6 and RCP 8.5) scenarios were used to project climatic data. Standardised Precipitation Index (SPI) was used to determine drought. Irregular rainfall and water shortage were the foremost challenges experienced by the population. Historic data showed an annual decrease in precipitation and increase in temperature. Precipitation shift and a low R-squared values (0.04 - 0.47) for precipitation indicated climatic variation. Decrease precipitation (gradient -11.84) coincided with the periods of droughts (1993 - 2019) given by the negative values of SPI (up to -3). The hydrological changes realised were 23 springs and 13 streams dry off and 27 springs and 16 streams have become seasonal. Projected data showed increase in precipitation and temperature, leaving Bamenda with the challenge of poor water quality that negatively affects public health and development. This study highlights the need to adopt current water and drought management practice in this area.

scholarly journals Climate-proofing a malaria eradication strategy

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Hannah Nissan ◽  
Israel Ukawuba ◽  
Madeleine Thomson
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Malaria Risk ◽  
World Health ◽  
Advisory Group ◽  
Climate Projections ◽  
Climate Variability And Change ◽  
Eradication Strategy ◽  
Malaria Eradication

AbstractTwo recent initiatives, the World Health Organization (WHO) Strategic Advisory Group on Malaria Eradication and the Lancet Commission on Malaria Eradication, have assessed the feasibility of achieving global malaria eradication and proposed strategies to achieve it. Both reports rely on a climate-driven model of malaria transmission to conclude that long-term trends in climate will assist eradication efforts overall and, consequently, neither prioritize strategies to manage the effects of climate variability and change on malaria programming. This review discusses the pathways via which climate affects malaria and reviews the suitability of climate-driven models of malaria transmission to inform long-term strategies such as an eradication programme. Climate can influence malaria directly, through transmission dynamics, or indirectly, through myriad pathways including the many socioeconomic factors that underpin malaria risk. These indirect effects are largely unpredictable and so are not included in climate-driven disease models. Such models have been effective at predicting transmission from weeks to months ahead. However, due to several well-documented limitations, climate projections cannot accurately predict the medium- or long-term effects of climate change on malaria, especially on local scales. Long-term climate trends are shifting disease patterns, but climate shocks (extreme weather and climate events) and variability from sub-seasonal to decadal timeframes have a much greater influence than trends and are also more easily integrated into control programmes. In light of these conclusions, a pragmatic approach is proposed to assessing and managing the effects of climate variability and change on long-term malaria risk and on programmes to control, eliminate and ultimately eradicate the disease. A range of practical measures are proposed to climate-proof a malaria eradication strategy, which can be implemented today and will ensure that climate variability and change do not derail progress towards eradication.

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